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A simple radiometric correction model to improve automatic mapping of vegetation from multispectral satellite data
Abstract
A simplified model for radiometric corrections has been used to improve nonsupervised classification of vegetation cover in a hilly area near Barcelona, Spain. A digital elevation model and standard parameters for exoatmospheric solar irradiance, atmospheric optical depth, and sensor calibration are the only inputs required. Radiometric classes obtained by cluster classification of Landsat TM images from nonradiometrically corrected images include several classes related to terrain illumination, but not to vegetation or thematic cover differences. The use of radiometric correction allows identifying all radiometric classes obtained as vegetation or thematic classes with 83.3% global accuracy. Classes obtained include Pinus halepensis, Quercus ilex, and Quercus cerrioides forests, shrublands, grasslands, urban areas with vegetation, urban areas without vegetation, and denuded areas. Radiometric correction helps in estimating surfaces and spectral features of these classes. The results are discussed considering botanical composition, date (phenology), and vegetation dynamics.
... Reaching a higher level of precision, a typical Landsat-like optical sensor measures spectral radiance (L sλ ; W m −2 sr −2 µm −1 ), including both the land surface-reflected radiance, which is our main interest, and the atmospheric spectral radiance (L atmλ ), composed by the upwelling spectral radiance and the reflection of the downwelling spectral radiance of the atmosphere. Atmospheric spectral total optical depth (τ 0λ ; dimensionless) weakens the downwelling solar spectral irradiance (E 0λ ; W m −2 µm −1 ) and the upwelling surface-reflected radiance [24]. ...
... The total matching area of the L8 198031 scene and the S2 R051 TCG tile was 1,204,945 ha, and the masked area was 111,562 ha (9.26% of the common area) (Figure 8). The CorRad algorithm was designed in 1994 to correct the topographic and atmospheric effects of Landsat-like imagery [24]. The topographic corrections followed a cosine-correction approach. ...
... The atmospheric correction followed a dark object subtraction (DOS) [66] approach to resolve the atmospheric path radiance, while the atmospheric total optical depth was assumed to be constant (wavelength-dependent). In 2014, Pons et al. [46] presented an automatic method designed to The CorRad algorithm was designed in 1994 to correct the topographic and atmospheric effects of Landsat-like imagery [24]. The topographic corrections followed a cosine-correction approach. ...
The main objective of this research is to apply unmanned aerial system (UAS) data in synergy with field spectroradiometry for the accurate radiometric correction of Landsat-8 (L8) and Sentinel-2 (S2) imagery. The central hypothesis is that imagery acquired with multispectral UAS sensors that are well calibrated with highly accurate field measurements can fill in the scale gap between satellite imagery and conventional in situ measurements; this can be possible by sampling a larger area, including difficult-to-access land covers, in less time while simultaneously providing good radiometric quality. With this aim and by using near-coincident L8 and S2 imagery, we applied an upscaling workflow, whereby: (a) UAS-acquired multispectral data was empirically fitted to the reflectance of field measurements, with an extensive set of radiometric references distributed across the spectral domain; (b) drone data was resampled to satellite grids for comparison with the radiometrically corrected L8 and S2 official products (6S-LaSRC and Sen2Cor-SNAP, respectively) and the CorRad-MiraMon algorithm using pseudo-invariant areas, such as reflectance references (PIA-MiraMon), to examine their overall accuracy; (c) then, a subset of UAS data was used as reflectance references, in combination with the CorRad-MiraMon algorithm (UAS-MiraMon), to radiometrically correct the matching bands of UAS, L8, and S2; and (d) radiometrically corrected L8 and S2 scenes obtained with UAS-MiraMon were intercompared (intersensor coherence). In the first upscaling step, the results showed a good correlation between the field spectroradiometric measurements and the drone data in all evaluated bands (R2 > 0.946). In the second upscaling step, drone data indicated good agreement (estimated from root mean square error, RMSE) with the satellite official products in visible (VIS) bands (RMSEVIS < 2.484%), but yielded poor results in the near-infrared (NIR) band (RMSENIR > 6.688% was not very good due to spectral sensor response differences). In the third step, UAS-MiraMon indicated better agreement (RMSEVIS < 2.018%) than the other satellite radiometric correction methods in visible bands (6S-LaSRC (RMSE < 2.680%), Sen2Cor-SNAP (RMSE < 2.192%), and PIA-MiraMon (RMSE < 3.130%), but did not achieve sufficient results in the NIR band (RMSENIR < 7.530%); this also occurred with all other methods. In the intercomparison step, the UAS-MiraMon method achieved an excellent intersensor (L8-S2) coherence (RMSEVIS > 1%). The UAS-sampled area involved 51 L8 (30 m) pixels, 143 S2 (20 m) pixels, and 517 S2 (10 m) pixels. The drone time needed to cover this area was only 10 minutes, including areas that were difficult to access. The systematic sampling of the study area was achieved with a pixel size of 6 cm, and the raster nature of the sampling allowed for an easy but rigorous resampling of UAS data to the different satellite grids. These advances improve human capacities for conventional field spectroradiometry samplings. However, our study also shows that field spectroradiometry is the backbone that supports the full upscaling workflow. In conclusion, the synergy between field spectroradiometry, UAS sensors, and Landsat-like satellite data can be a useful tool for accurate radiometric corrections used in local environmental studies or the monitoring of protected areas around the world.
... Atmospheric conditions (water vapour, aerosols, etc.) and different illumination caused by the solar position according to the acquisition date and time, location on Earth and relief (cast shadows, etc.) may cause undesired artefacts in remote sensing images. It is therefore very important to apply the process known as radiometric correction (Pons and Solé-Sugrañes, 1994;Richards and Jia, 2005;Janzen et al., 2006). Radiometric correction is a set of techniques designed to convert the digital values captured by a sensor to physical quantities of interest, such as radiance, reflectance or surface temperature (Pons and Arcalís, 2012). ...
... Several proposals have been made to overcome, at least partially, the difficulties involved in applying radiometric correction in a general way, from the simplest dark-object methods (Chavez, 1988) to other, more complete methods that integrate several factors but keep general feasibility as a basic principle (e.g., Pons and Solé-Sugrañes, 1994, among many others). Nevertheless, times have changed. ...
... The aim of this work is to revise and improve a previous radiometric (atmospheric, dark-object based, and topographic) correction method (Pons and Solé-Sugrañes, 1994), which has been widely used with Landsat imagery, by using rigorous metadata management that allows automatic radiometric correction of most Landsat imagery while being highly consistent with the Terra-MODIS daily reflectance products. The atmospheric part of the method is improved by accounting for more realistic atmospheric conditions by using pseudoinvariant areas, PIA (Hadjimitsis et al., 2009), generated with 10-year series of Terra-MODIS imagery and polynomial fitting of atmospheric optical depth using MOD-TRAN simulations, although it would also be possible to use other radiative transfer models currently in use (e.g., 6S, Kotchenova et al., 2006). ...
... In all three approaches, some sophistications make use of Digital Elevation Models (DEM) to consider the terrain effects on the illumination angle, and therefore, improve the accuracy by accounting for the amount of energy the surface receives per unit surface [18]. ...
... Pseudoinvariant Area (PIA) radiometric correction method [43] is a 2014 improvement of a simpler model that is published in Pons and Solé-Sugrañes [18] and implemented in the MiraMon software [86] from 1994 to retrieve surface reflectance from TOA radiance, accounting for TOD, atmospheric radiance, and topography (including self and cast-shadows, TOD dependency on height, etc.). The method consists of fitting the model on the basis of reference reflectance values that are saved in PIAs. ...
The use of Pseudoinvariant Areas (PIA) makes it possible to carry out a reasonably robust and automatic radiometric correction for long time series of remote sensing imagery, as shown in previous studies for large data sets of Landsat MSS, TM, and ETM+ imagery. In addition, they can be employed to obtain more coherence among remote sensing data from different sensors. The present work validates the use of PIA for the radiometric correction of pairs of images acquired almost simultaneously (Landsat-7 (ETM+) or Landsat-8 (OLI) and Sentinel-2A (MSI)). Four pairs of images from a region in SW Spain, corresponding to four different dates, together with field spectroradiometry measurements collected at the time of satellite overpass were used to evaluate a PIA-based radiometric correction. The results show a high coherence between sensors (r2 = 0.964) and excellent correlations to in-situ data for the MiraMon implementation (r2 > 0.9). Other methodological alternatives, ATCOR3 (ETM+, OLI, MSI), SAC-QGIS (ETM+, OLI, MSI), 6S-LEDAPS (ETM+), 6S-LaSRC (OLI), and Sen2Cor-SNAP (MSI), were also evaluated. Almost all of them, except for SAC-QGIS, provided similar results to the proposed PIA-based approach. Moreover, as the PIA-based approach can be applied to almost any image (even to images lacking of extra atmospheric information), it can also be used to solve the robust integration of data from new platforms, such as Landsat-8 or Sentinel-2, to enrich global data acquired since 1972 in the Landsat program. It thus contributes to the program’s continuity, a goal of great interest for the environmental, scientific, and technical community.
... Згідно з моделлю Ламберта [8,18,21] освітлен ня поверхні тест ділянки формується в основ ному із двох складових -прямого та дифузного сонячного світла. Дифузна складова за певних умов може бути потрактована як сталий адитив ний член до прямого сонячного освітлення [7]. ...
... Із рис. 2 видно, що водна поверхня має най нижчу яскравість в області червоного краю. Згідно з методом віднімання темного об'єкта [7,18] атмосферна корекція даних рівня 1 в оптич ному та NIR діапазоні сенсора «Hyperion» здійс нюється для кожного піксела за формулами . ...
... Afterwards, evaluation of the performance of different Vegetation Indexes (NDVI, SAVI, ARVI) (Huete, 1988;Kaufman and Tanré, 1992) by field survey was attempted so as to minimize the different atmospheric and soil effects on the vegetation response after the fire. Also an atmospheric correction procedure (Pons, 1994) was applied, but it is still on research. ...
... -use of easy and simple atmospheric correction models, such as the mentioned model of Pons and Solé (1994). ...
... An example of atmospheric correction in the thermal infrared (TIR) using a single-channel algorithm proposed by Pons and Solé-Sugrañes (1994) and Pons et al. (2014) using Landsat-5 TM data is shown in Figure 8.4. In remote areas such as Alaska (US), the collection of atmospheric data is challenging because of remoteness, winter conditions, and the high costs of maintaining groundbased measurement sensors (Cristóbal et al., 2012). ...
The increasing access to remote sensing data from different platforms, acquired at different spatial, spectral, and temporal resolutions, is continuously widening the scope of applications of these datasets. Parallel advancements in computational science and technology have led to the development of more sophisticated data processing and analysis tools. While early remote sensing studies focused on detecting a feature or phenomenon, the current practice is to conduct multitemporal studies and time series analyses based on multiple data sources, including optical, microwave, and thermal imagery. There are several calibration and normalization issues that need to be resolved before these more complex monitoring and change detection studies can be accomplished.
... Atmospheric correction was essential for eliminating the impact of the atmosphere on the images, while radiometric correction helped adjust for sensor calibration changes over time. For a more comprehensive understanding of these corrections, readers are advised to refer to Pons and Solé-Sugrañes (1994), Hadjimitsis et al. (2010), and Prieto-Amparan et al. (2018). Following the corrections, the study area was extracted from the Landsat images. ...
Forests are vital in combating climate change by storing and sequestrating CO2 from the atmosphere. Measuring the influence of land use/land cover (LULC) changes on the capacity of carbon storage (CS) within forest ecosystems presents a significant challenge. This study employs remote sensing techniques to examine the changes in spatiotemporal patterns of CS in the Chittagong Hill Tracts (CHT), resulting from LULC alterations between 1996 and 2021. LULC change patterns were identified for six different years utilizing the Google Earth Engine (GEE). The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model was combined with GEE to evaluate the changing patterns of CS. The study discovered that the CHT region experienced a loss of 21.65 × 106 Mg of CS, owing to a 21% reduction in vegetation cover (2862.85 km^2) during the study period. The central city area (Chittagong) accounted for the most significant loss of CS (7.99 × 106 Mg), while the suburban areas of Khagrachari (0.92 × 106 Mg) and Rangamati (3.53 × 106 Mg) contributed the least. The multiple regression model revealed that elevation and vegetation characteristics significantly influenced CS. The findings underscore the importance of developing policies and strategies that mitigate the adverse effects of land cover change on CS, and advocate for sustainable forest management practices that strike a balance between ecological, social, and economic concerns.
... The main concept is that the spectral reflectance of a sample surface is the same in directplus-diffuse illumination conditions as in diffuse illumination conditions (what is variable is the spectral irradiance) [2,3]. Additionally, there is a need to account for atmospheric radiance contributions to the at-sensor spectral radiance [4,5]. These principles can be applied using an empirical line approach, among others [41][42][43]. ...
This study focuses on the recovery of information from shadowed pixels in RGB or multispectral imagery sensed from unmanned aerial vehicles (UAVs). The proposed technique is based on the concept that a property characterizing a given surface is its spectral reflectance, i.e., the ratio between the flux reflected by the surface and the radiant flux received by the surface, and this ratio is usually similar under direct-plus-diffuse irradiance and under diffuse irradiance when a Lambertian behavior can be assumed. Scene-dependent elements, such as trees, shrubs, man-made constructions, or terrain relief, can block part of the direct irradiance (usually sunbeams), in which part of the surface only receives diffuse irradiance. As a consequence, shadowed surfaces comprising pixels of the image created by the UAV remote sensor appear. Regardless of whether the imagery is analyzed by means of photointerpretation or digital classification methods, when the objective is to create land cover maps, it is hard to treat these areas in a coherent way in terms of the areas receiving direct and diffuse irradiance. The hypothesis of the present work is that the relationship between irradiance conditions in shadowed areas and non-shadowed areas can be determined by following classical empirical line techniques for fulfilling the objective of a coherent treatment in both kinds of areas. The novelty of the presented method relies on the simultaneous recovery of information in non-shadowed and shadowed areas by the in situ spectral reflectance measurements of characterized Lambertian targets followed by smoothing of the penumbra area. Once in the lab, firstly, we accurately detected the shadowed pixels by combining two well-known techniques for the detection of the shadowed areas: (1) using a physical approach based on the sun’s position and the digital surface model of the area covered by the imagery; and (2) the image-based approach using the histogram properties of the intensity image. In this paper, we present the benefits of the combined usage of both techniques. Secondly, we applied a fit between non-shadowed and
shadowed areas by using a twin set of spectrally characterized target sets. One set was placed under direct and diffuse irradiance (non-shadowed targets), whereas the second set (with the same spectral characteristics) was placed under diffuse irradiance (shadowed targets). Assuming that the reflectance of the homologous targets of each set was the same, we approximated the diffuse incoming irradiance through an empirical line correction. The model was applied to all detected shadowed areas in the whole scene. Finally, a smoothing filter was applied to the penumbra transitions. The presented empirical method allowed the operational and coherent recovery of information from shadowed areas, which is very common in high-resolution UAV imagery.
... The scenes of November 2016 were considered to be appropriate for current analysis as they had negligible cloud cover (0.20%). The imageries were radio-metrically corrected using the top of the atmosphere (ToA) correction method (Pons & Solé-Sugrañes, 1994). ...
Grasslands are the world’s most extensive terrestrial ecosystem, which provides a variety of services for humans, such as carbon storage, food production, crop pollination, pest regulation, and are a major feed source for livestock. However, grasslands are today one of the most endangered ecosystems due to land-use change, agricultural intensification, land abandonment, as well as climate change. Grasslands are an integral part of human societies across the globe, which are broadly known as tropical savannah and temperate grasslands. In the Himalayan region, grasslands are found in more than 55% of the area and different climatic conditions lead to different varieties of grasslands like Danthonia grasslands, kobresia sedge meadow, etc. Grasslands deal with the spatial and temporal distribution of heterogeneous landscapes, which support a high diversity of various species. Owing to very rugged terrain and inaccessibility, the information on the extent of alpine grassland and percent grass cover (%) across the meadows is limited. Therefore, the present attempt was made to assess the current status of grassland in the alpine region of Uttarakhand above 3000 m asl. LANDSAT-8 (OLI and TIRS sensors) satellite data were used to delineate the grasslands using normalized difference vegetation indices (NDVIs) of the alpine region with the help of over 179 ground truth points out of which 50 points are testing points and 129 points are training points. Grass covers (%) were also assessed in the whole alpine region of Western Himalaya of Uttarakhand which nearly consists of over 75 meadows by using random plots (1 × 1 m, total 10 per site) in each meadow. Overall, 89.52% accuracy was achieved based on 50 randomly selected testing points. A total of 4949.25 sq. km area is under the different percentage of grass cover in the alpine region of Uttarakhand, Western Himalaya. Danthonia grasslands below 4000 m and Kobresia sedge meadows above 4000 m elevation are dominant in the state. In the alpine region, over 1056 sq. km grassland area have less than 10% grass cover indicating higher degraded and cold desert areas and only 565.69 sq. km area have more than 60% grass cover, which is highly favorable for rich biodiversity and grazing.
... Many studies have shown the wide application of Landsat images being used for land cover mapping and the creation of vegetation inventories at different spatial scale information on the earth's surface characteristics [70,71], despite the existence of limitations in the use of Landsat data for multi-temporal studies because of problems in obtaining homogeneous time series. Efforts have been made in the past to reduce non-surface noise in Landsat images and to calibrate the sensor to correct radiometric trends [72] and reduce the influence of topography [73,74]. According to Schroeder et al. [75], other studies have shown that the application of accurate sensor calibrations and complex atmospheric corrections does not guarantee the multi-temporal homogeneity of Landsat datasets because complete atmospheric properties are difficult to quantify, and simplifications are commonly assumed. ...
Irrigated agriculture has a major impact on the environment, especially soil degradation. Soil salinity is a critical environmental problem, which has great impact on soil fertility and overall agricultural productivity. Since, soil salinity processes are highly dynamic, the methods of detecting soil salinity hazards should also be dynamic. Remote sensing data are modern tools that provide information on variation over time essential for environmental monitoring and change detection, as they also help in the reduction of conventional time-consuming and expensive field sampling methods, which is the traditional method of monitoring and assessment. This chapter thus reviewed the concepts and applications of remote sensing, GIS-assisted spatial analysis and modelling of the salinity issue in irrigation fields. Generally, compared to the labour, time and money invested in field work devoted to collecting soil salinity data and analysis, the availability and ease of acquiring satellite imagery data and analysis made this concept very attractive and efficient.
... Las imágenes Landsat-5 TM y Landsat-7 ETM+ han sido corregidas geométricamente, a una resolución espacial de 120 m i 60 m, respectivamente, obteniéndose un RMSE inferior a un píxel de 30m, y radiométricamente (Pons y Solé-Sugrañes, 1994). Las imágenes TERRA-MODIS se han reproyectado al sistema de coordenadas UTM-30N a una resolución espacial de 1 km. ...
Energy fluxes computing (actual evapotranspiration, net radiation, sensible heat and soil heat flux) are essential to improve the knowledge of the hydrological cycle, especially in natural vegetation covers. In this paper, we present the first results of the energy fluxes modeling by means of the TSEB model and using five Landsat-5 TM and Landsat-7 ETM + in 2010, in an experimental plot of juniper tree of the Doñana Biological Reserve and the validation with Eddy-Covariance data. TSEB method showed acceptable results in the measurement of the different energy fluxes taking into account the high heterogeneity of this type of vegetation. In the case of actual evapotranspiration, net radiation, sensible heat flux and soil heat flux were obtained an average RMSE of 60, 42, 60 and 53 W·m-2 , respectively. Future improvements in leaf area index determination and the inclusion of more images and Eddy-Covariance stations would help to implement and improve the TSEB model in this type of vegetation.
... Reanalysis data can also provide atmospheric inputs for atmospheric correction; however, its current spatial resolution is still too coarse to be applied to medium or coarse resolution imagery. An example of atmospheric correction in the thermal infrared (TIR) using a single-channel algorithm proposed by Pons and Solé-Sugrañes (1994) and Pons et al. (2014) using Landsat-5 TM data is shown in Figure 5.4. In remote areas such as Alaska (US), collection of atmospheric data is challenging because of remoteness, winter conditions and the high costs of maintaining ground-based measurement sensors (Cristóbal et al., 2012). ...
... La corrección radiométrica se ha llevado a cabo mediante el método propuesto por Pons y Solé [5]. La conversión de DN a radiancias se ha realizado mediante la lectura de los datos incluidos en la cabecera de cada imagen. ...
... Éste umbral es diferente para cada imagen, dependiendo del tipo y superficie de la cubierta nubosa, según la fecha en que haya sido tomada, y según la cubierta subyacente. Un segundo método es el utilizado por Irish [2], en el que se utilizan dos bandas del visible, la verde y la roja, y el infrarrojo cercano, el medio y el térmico, corregidas radiométricamente mediante el método propuesto por Pons y Solé [7]. Consta de 2 procesos. ...
En este artículo se presenta la aplicación de tres métodos semiautomáticos para la detección de nubes y otro método para la detección de las sombras producidas por éstas, en imágenes Landsat-7 ETM+ y Landsat-5 TM, con el objetivo de establecer cuál de estos métodos es el óptimo. El primer método se basa en el establecimiento de un umbral de temperatura a partir de la temperatura aparente de brillo para cada una de las imágenes, usando el canal infrarrojo térmico. Se ha utilizado un total de 124 imágenes durante el período 2002-2003 y 2005 que cubren Cataluña (órbita y fila 197-31, 198-31-32). El segundo método está basado en la metodología propuesta por Irish [2], teniendo como base 8 filtros que utilizan diferentes bandas del visible, y también el infrarrojo cercano, medio y térmico. Este método se ha utilizado en dos imágenes representativas de la variabilidad estacional anual, una correspondiente a mayo (Landsat-7 ETM+) y otra a febrero (Landsat-5 TM), y ambas de órbita y fila 197-31. Aunque el resultado de la detección de las nubes es correcto, existen errores de comisión de otras cubiertas. A estas imágenes se les ha aplicado un tercer método que propone una mejora sobre el anterior introduciendo otro filtro a partir de un umbral superior a 0.6 de albedo, que disminuye notablemente esta comisión. El método propuesto para la detección de sombras se basa en una clasificación no supervisada. Mediante la comparación de los métodos, se llega a la conclusión de que con el método Irish [2] mejorado, se obtienen los mejores resultados, aunque no detecta las nubes de escaso espesor y el tiempo de procesado es diez veces superior al del primer método. En estos casos, la combinación de esta metodología y el método de umbrales de temperatura resuelven el problema.
... Radiometric correction (non-thermal bands): Radiometric correction has been done following the methodology proposed by Pons and Solé (1994) which allows to reduce the number of undesired artifacts that are due to the effects of the atmosphere or to the differential illumination which is, in turn, due to the time of the day, the location in the Earth and the relief (zones being more illuminated than others, shadows, etc). Digital number to radiance conversion has been done by means of image header conversion parameters taking into account the considerations exposed by Cristóbal et al. (2003). ...
Evapotranspiration monitoring has important implications on global and regional climate modelling, as well as in the knowledge of the hydrological cycle and to assess environmental stress that affects forest and agricultural ecosystems. Nowadays, Remote Sensing and Geographical Information Systems (GIS) are the most important techniques allowing the scientific community to compute the actual evapotranspiration at a regional and global scale in a feasible way. In this study, we present the preliminary results in daily actual evapotranspiration (ETd) at a regional scale (Catalonia, NorthWest of Spain) by means of eleven Landsat-7 ETM+ images and GIS tools during 2002-2003 period. The result of this analysis consists of a set of ETd GIS layers having 60 meters of spatial resolution with an almost monthly temporal resolution. The methodology proposed by Seguin and Itier (1989) and Vidal and Perrier (1992) has been used, requiring three main variables to compute the ETd: land surface temperature, air temperature and net radiation. Land surface temperature has been obtained by means of the Landsat-7 ETM+ thermal band emissivity correction (Hurtado et al., 1996; Valor et al. 2000). Air temperature has been computed by multiple regression analysis and spatial interpolation from meteorological ground stations at satellite pass (Ninyerola et al., 2000). Net radiation has been calculated by means of the radiative balance. These preliminary results are very interesting due to the difficulty in obtaining forest and crop ETd data and to the high spatial and temporal resolution used, not usually combined together.
... La corrección radiométrica permite reducir la presencia de artefactos no deseados debidos a los efectos de la atmosfera o a la iluminación diferencial provocada por la hora del día, el día del año, la posición terrestre y el relieve (zonas más o menos iluminadas, ocultas, sombras proyectadas, etc.). Esencialmente, la corrección convierte una imagen de valores (DN) proporcionales a la radiancia recibida por el sensor en una imagen en que los valores son reflectancias [5]. El programa considera, entre otros factores, el relieve (ángulo de incidencia y sombras proyectadas), la posición solar, la distancia Tierra-Sol en el momento de la toma de la imagen, la atenuación atmosférica en el camino de ida y retorno de la radiación y parámetros estándar, para cada canal, de densidad óptica atmosférica, irradiancia exoatmosférica solar y calibración del sensor. ...
Actualmente, la gran disponibilidad y diversidad de imágenes de satélite así como su posterior explotación e integración en un Sistema de Información Geográfica (SIG), configura la Teledetección como una herramienta necesaria en la gestión de los recursos hídricos a escalas subregionales y regionales. En esta comunicación se presenta una metodología robusta para la integración de un gran número de imágenes de Teledetección en la gestión diaria de los recursos hídricos de Cataluña desarrollada entre la Agencia Catalana del Agua y la Universitat Autònoma de Barcelona a partir de imágenes Landsat-7 ETM+, Landsat-5 TM y SPOT-5 HRG. Desde enero del 2002, se ha consolidado un protocolo para el procesado de todas las imágenes disponibles, con especial énfasis en el tratamiento y almacenaje de los metadatos y en la corrección geométrica y radiométrica, obteniéndose un banco de ortoimágenes de media resolución para el seguimiento de las necesidades hídricas de los cultivos, de la cubierta nival y de la calidad del agua litoral de Cataluña. Los productos resultantes incluyen un mapa de cultivos anual con una detallada leyenda, la disponibilidad de índices de vegetación (NDVI) y de humedad, mapas de cubierta nival, índices de cubierta nival (NDSI) y evapotranspiración real diaria. 1. Introducción y objetivos La gestión y planificación de recursos hídricos en un área como la de Cataluña precisa, como es lógico, de un buen conocimiento de dichos recursos. Tal conocimiento debe ineludiblemente conseguirse, en algunos casos, a través de la captación primaria en el campo, sea mediante un desplazamiento físico de personal, sea mediante redes automáticas. La Agencia Catalana del Agua utiliza tales procedimientos para recabar parte de tales conocimientos, pero resulta evidente que en muchos casos el tipo de dato a recoger y/o el coste que supondría recogerlo de forma estadísticamente significativa sobre todo el territorio hacen inviable la recogida a través de esos procedimientos. En muchos de estos campos, como pueden ser la innivación o el consumo hídrico de los cultivos, otras aproximaciones pueden resultar enormemente útiles y valiosas, y entre ellas la Teledetección ocupa un lugar destacado. En efecto, el uso de las imágenes de satélite ha experimentado en los últimos años un importante auge con la aparición de nuevos sensores de mayor resolución temporal, espacial y radiométrica. Este hecho permite, por ejemplo, el seguimiento de fenómenos naturales (incendios forestales, etc.) o del impacto ambiental de las actividades humanas (construcción de vías de comunicación, etc.) con una precisión anteriormente inimaginable [1]. El objetivo de esta comunicación es la presentación de un protocolo para la integración masiva de imágenes de satélite, fruto de una suscripción anual, así como de sus aplicaciones, en concreto las relacionadas con el seguimiento de la cobertura nival y de las área agrícolas irrigadas de Cataluña desarrolladas para la Agencia Catalana del Agua. En este sentido, la incorporación de los productos visuales y resultados analíticos obtenidos al Sistema de Información Geográfica (SIG) corporativo de la Agencia comporta un enriquecimiento en la gestión diaria así como en la planificación y toma de decisiones a corto y medio plazo. En definitiva, la integración de la Teledetección y de los SIG es hoy una herramienta imprescindible para cualquier administración con implantación territorial. La comunicación resume el tipo de imágenes utilizadas y modo de adquisición, la conversión de los datos originales e integración de los metadatos, las correcciones geométricas y radiométricas, el navegador de imágenes de satélite y los productos elaborados hasta la fecha: mapas e índices de la cubierta nival de Cataluña, mapas de cultivos con una detallada leyenda, mapas de evapotranspiración real diaria, entre otros.
... Corrección radiométrica de las imágenes (canales no térmicos): la corrección radiométrica se ha llevado a cabo mediante el método propuesto por [21]. El objetivo de este método es reducir la presencia de artefactos no deseados provocados por los efectos de la atmósfera o de la iluminación diferencial provocada por la hora del día, el día del año, la posición de la Tierra y el relieve (zonas más o menos iluminadas, ocultas, sombras proyectadas, etc). ...
Evapotranspiration monitoring has important implications on global and regional climate modelling, as well as in the knowledge of the hydrological cycle and to assess environmental stress that affects forest and agricultural ecosystems. Nowadays, Remote Sensing and Geographical Information Systems (GIS) are the most important techniques allowing the scientific community to compute the actual evapotranspiration at a regional and global scale in a feasible way. In this study, we present the preliminary results in daily actual evapotranspiration (AETd) at a regional scale (Catalonia, NorthWest of Spain) by means of eleven Landsat-7 ETM+ images and GIS tools during 2002-2003 period. The result of this analysis consists of a set of AETd GIS layers having 60 meters of spatial resolution with an almost monthly temporal resolution. The methodology proposed by Seguin and Itier [24] and Vidal and Perrier [29] has been used, requiring three main variables to compute the AETd: land surface temperature, air temperature and net radiation. Land surface temperature has been obtained by means of the Landsat-7 ETM+ thermal band emissivity correction [9, 28]. Air temperature has been computed by multiple regression analysis and spatial interpolation from meteorological ground stations at satellite pass [17]. Net radiation has been calculated by means of the radiative balance. These preliminary results are very interesting due to the difficulty in obtaining forest and crop AETd data and to the high spatial and temporal resolution used, not usually combined together.
... Corrección radiométrica de las imágenes (canales no térmicos): la corrección radiométrica se ha llevado a cabo mediante el método propuesto por Pons y Solé (1994). El objetivo de este método es reducir la presencia de artefactos no deseados provocados por los efectos de la atmósfera o de la iluminación diferencial provocada por la hora del día, el día del año, la posición de la Tierra y el relieve (zonas más o menos iluminadas, ocultas, sombras proyectadas, etc). ...
Evapotranspiration monitoring has important implications on global and regional climate modelization, as well as in the hydrological cycle and to assess about environmental stress that affect forest and agricultural ecosystems. Nowadays, Remote Sensing and Geographical Information Systems (GIS) are the most important techniques allowing the scientific community to compute the actual evapotranspiration in a feasible way. In this study we present the preliminary results in daily actual evapotranspiration (ETd) at a regional scale (North-West of Spain) by means of eleven Landsat-7 ETM+ images and GIS tools during the 2002-2003 period. The result of this analysis consists on a set of ETd GIS layers having 60 meters of spatial resolution (total area of 3600 m2) with an almost monthly temporal resolution. The methodology proposed by Seguin and Itier (1989) and Vidal and Perrier (1992) has been used, requiring three main variables to compute the ETd: land surface temperature, air temperature and net radiation. Land surface temperature has been obtained by means of the Landsat-7 ETM+ thermal band emissivity correction (Hurtado et al., 1996; Valor et al. 2000). Air temperature has been computed by multiple regression analysis and spatial interpolation from meteorological ground stations at satellite pass (Ninyerola et al., 2000). Net radiation has been calculated by means of the raditive balance. These preliminary results are very interesting due to the difficulty in obtaining forest and crop ETd data and to the high spatial and temporal resolution used, not usual in such combination.
... Secondly, there is compensation for the different values of the exo-atmospheric solar irradiance arising from spectral band differences; and thirdly, the variation (geographically or temporal) in the Earth-Sun distance between different image acquisition dates is corrected (Chander et al., 2009). The equation that was first proposed by Pons and Solè-sugrañès (1994), later modified in Salvador et al. (1996) and then recommended by Chander et al. (2009), was used to convert at-sensor radiance to at-satellite ...
... Image and/or sensor differences within and between scenes were normalized by converting the brightness values of each pixel (Digital Number (DN) to actual reflectance (Top of Atmosphere Reflectance (TOA)), in order to obtain the actual ground reflectance [35]. Topographic normalization is a crucial part of atmospheric correction [36][37][38] as it enhances representation of the original image, hence improving spectral signatures, classification and overall accuracy [35,39]. ...
Land use and land cover (LULC) changes can pose profound impacts on wildlife habitats, abundance and distribution and on human-dominated landscapes. We investigated LULC changes in the Greater Serengeti ecosystem, Tanzania, for a period of 41 years from 1975 to 2015. Specifically, we mapped LULC types for 1975, 1995 and 2015 and assessed the corresponding changes during 1975-1995, 1995-2015 and 1975-2015. We used the random forest classification algorithm to classify Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper Plus (+ETM) and Operational Land Imager (OLI) into eight main classes. We obtained accuracies of 88.4%, 90.6% and 93.4% with Kappa Indices of Agreement (KIA) of 0.86, 0.87 and 0.91 for 1975, 1995 and 2015, respectively. Grassland, shrubland and woodland were the major LULC types throughout 1975-2015 with percentage coverages of 50.6%, 23.7% and 20.9% for 1975; 54.2%, 23.5% and 15.9% for 1995; and 57.0%, 23.8% and 8.9% for 2015, respectively. Overall, woodland cover (-11.1%) was converted to most of the other cover types during 1975-2015. The loss of woodland cover is due to increasing human population size, agriculture, settlements and policy changes fires and elephant browsing. Effective conservation policies and regulation of socioeconomic activities in the ecosystem and its buffer area are essential to ameliorate declining vegetation cover, especially along the protected areas boundaries.
... To deal with errors that occur in the field, we should not only focus on promoting the accuracy of instruments [39,40] and improve the authenticity of models [41,42], but also pay attention to the distribution of errors. Overall, our error assessment method has two advantages over other models: (a) error assessment is conducted before measurement which will give surveyors an expectation of error distribution, (b) the method has its adaptability and flexibility as theoretical error distribution for each study area is calculated by its vegetation distribution. ...
To verify large-scale vegetation parameter measurements the average value of sampling points from small-scale data are typically used. However, this method undermines the validity of the data due to the difference in scale or an inappropriate number of sampling points. A robust universal error assessment method for measuring ground vegetation parameters is therefore needed. Herein, we simulated vegetation scenarios and measurements by employing a normal distribution function and the Lindbergh-Levi theorem to deduce the characteristics of the error distribution. We found that the small-and large-scale error variation was similar among the theoretically deduced Leaf Area Index (LAI) measurements. Additionally, LAI was consistently normally distributed regardless of which systematic error or accidental error was applied. The difference between observed and theoretical errors was highest in the low-density scenario (7.6% at <3% interval) and was lowest in the high-density scenario (5.5% at <3% interval) while the average ratio between deviation and theoretical error of each scenario was 2.64% (low-density), 2.07% (medium-density) and 2.29% (high-density). Further, the relative difference between theoretical and empirical error was highest in the high-density scenario (20.0% at <1% interval) and lowest in the low-density scenario (14.9% at <1% interval), respectively. These data show the strength of a universal error assessment method and we recommend that existing large-scale data of the study region are used to build a theoretical error distribution. Such prior work in conjunction with the models outlined in this paper could reduce measurement costs and improve the efficiency of conducting ground measurements.
... Due to radiometric distortions arising from differences in illumination conditions and sensor characteristics, the radiation observed by the imaging system may not coincide with the emitted or re ected energy from the objects of interest (e.g., Duggin and Piwinski, 1984;Schott et al., 1988;Song et al., 2001;Du et al., 2002;Teillet et al., 2007). In order to attain radiometric consistency among different remotely sensed images, radiometric inconsistencies and distortions should be accurately addressed prior to further image interpretation and analysis; processes to remove these radiometric distortions are referred to as radiometric corrections (Pons and Solé-Sugrañes, 1994;Yang and Lo, 2000;Janzen et al., 2006;Pons et al., 2014). ...
... The HSI was calibrated with a radiometric correction in order to provide spectra high quality reflectance mosaics [34]. The radiometric algorithm includes atmospheric correction and correction for illumination changes [35]. ...
It is known that a typical hyper-spectral image consists of a sequence of wavelength bands and each wavelength band illustrates a two-dimensional image. This paper presents a HSI classification method including two approaches. The first approach is a probabilistic algorithm for object classification based on the image illustrated by single hyper-spectral wavelength bands, respectively, which generate a sequence of registered object images. Since hyper-spectral images (HSIs) obtained by air-borne or satellite-borne remote sensors has limited size, which may affect the classification accuracy, especially for small objects due to lack of pixels. The second approach investigates the hyper-spectral characteristics for a specific object in terms of uniformed hyper-spectrum energy function in wavelength domain. The hyper-spectral characteristics are applied to object verification, especially for objects which are difficult to distinguish from each other using classic classification methods, so that the accuracy is improved. The classification accuracy for the proposed object-oriented characterization method is evaluated in terms of producer accuracy (PA) and Kappa coefficient based on hyper-spectral images obtained from air-borne or satellite-borne remote sensors, respectively. The numerical results demonstrate that the proposed method can effectively identify and verify objects in hyper-spectral image, especially for those objects that are difficult to be distinguished from each other by classic methods. Furthermore, the proposed object classification method based on hyper-spectral characteristics is compared to conventional methods, including spectral information divergence (SID) method and multiple spectral angle mapper-Markov random fields (MSAM-MRF) method. It can be seen that the accuracy of object classification achieved by the proposed method can be up to 20% higher than that of classic methods.
... Location of the study area.T.Dube et al. Physics and Chemistry of the Earth xxx (xxxx) xxx-xxx Radiometric correction was conducted following the method by X.Pons et al. (2014) and XavierPons and Solé-Sugrañes (1994). Landsat images were acquired in Digital Number (DN) value format and then calibrated to radiance [Wm −2 sr −1 μm −1 ], based on the method byChander et al. (2009). ...
... The differences in the trends observed within different altitudes in the study zone are not a new find because, in the Mediterranean mountains and, generally, in other parts of the world, the vegetation succession processes and, thus, the vegetation distribution, are dependent on spatial and topographic patterns such as altitude or slope and orientation. Iterations between topographic effects on hydrological processes are some of the factors most widely used in differentiating vegetation patterns [68][69][70][71][72][73] for that reason. ...
Currently, there exists growing evidence that warming is amplified with elevation resulting in rapid changes in temperature, humidity and water in mountainous areas. The latter might result in considerable damage to forest and agricultural land cover, affecting all the ecosystem services and the socio-economic development that these mountain areas provide. The Mediterranean mountains, moreover, which host a high diversity of natural species, are more vulnerable to global change than other European ecosystems. The protected areas of the mountain ranges of peninsular Spain could help preserve natural resources and landscapes, as well as promote scientific research and the sustainable development of local populations. The temporal statistical trends (2001–2016) of the MODIS13Q1 Normalized Difference Vegetation Index (NDVI) interannual dynamics are analyzed to explore whether the NDVI trends are found uniformly within the mountain ranges of mainland Spain (altitude > 1000 m), as well as in the protected or non-protected mountain areas. Second, to determine if there exists a statistical association between finding an NDVI trend and the specific mountain ranges, protected or unprotected areas are studied. Third, a possible association between cover types in pure pixels using CORINE (Co-ordination of Information on the Environment) land cover cartography is studied and land cover changes between 2000 and 2006 and between 2006 and 2012 are calculated for each mountainous area. Higher areas are observed to have more positive NDVI trends than negative in mountain areas located in mainland Spain during the 2001–2016 period. The growing of vegetation, therefore, was greater than its decrease in the study area. Moreover, differences in the size of the area between growth and depletion of vegetation patterns along the different mountains are found. Notably, more negatives than expected are found, and fewer positives are found than anticipated in the mountains, such as the Cordillera Cantábrica (C.Cant.) or Montes de Murcia y Alicante (M.M.A). Quite the reverse happened in Pirineos (Pir.) and Montes de Cádiz y Málaga (M.C.M.), among others. The statistical association between the trends found and the land cover types is also observed. The differences observed can be explained since the mountain ranges in this study are defined by climate, land cover, human usage and, to a small degree, by land cover changes, but further detailed research is needed to get in-depth detailed conclusions. Conversely, it is found that, in protected mountain areas, a lower NDVI pixels trend than expected (>20%) occurs, whereas it is less than anticipated in unprotected mountain areas. This could be caused by management and the land cover type.
... Nevertheless, there exist limitations in using Landsat data for multitemporal studies because of problems in obtaining homogeneous time series. Efforts have been made in the past to reduce non-surface noise in Landsat images and also to calibrate the sensor to correct radiometric trends (Teillet et al., 2004;de Vries et al., 2007) and also reduce the influence of topography (Gu and Gillespie, 1998;Pons and Solé, 1994). According to Schroeder et al. (2006) other studies have shown that the application of accurate sensor calibrations and complex atmospheric corrections does not guarantee the multitemporal homogeneity of Landsat datasets because complete atmospheric properties are difficult to quantify and simplifications are commonly assumed. ...
Irrigation induced soil salinity is a critical environmental problem which has great impact on soil fertility and overall agricultural productivity. Satellite remote sensing (SRS) and GIS are modern tools that provide information on salinity variation over time essential for environmental monitoring and change detection. SRS and GIS can also help in the reduction of conventional time and labour expended by the expensive traditional method of field sampling techniques presently in use in South Africa. The overall objective of this study was, therefore, the mapping and modeling of the spatio-temporal trend of soil surface salinity and land use / land cover pattern in Vaal Harts irrigation scheme (VHS) located in Jan Kempdrop, Northern Cape province of South Africa for sustainable land management and development that is eco-friendly.
The temperature, rainfall and relative humidity data of VHS were collected from South Africa Weather Service. Mean, variance, standard deviation and coefficient of variation including Spearman correlation coefficient and the autocorrelation coefficient were determined from the data. A Topographic/base map (scale: 1: 150 000), soil map and the flood line data, acquired in map form from the Agricultural Research Council and South Africa Department of Agriculture, were converted to JPEG in the form of point data in a GIS environment. Baseline surveys were conducted and structured questionnaires were administered among selected 40 farmers and a project manager in order to access other necessary information on VHS. In achieving the main study objective, Landsat (TM and ETM+) images data of VHS acquired for three Epochs; 1991, 2001 and 2005 totaling 15 years were obtained from the Global Land Cover Facility (GLCF) hosted by the University of Maryland, USA. Ground-truthing of the SRS data using a Garmin handheld GPS with a receiver accuracy of 2 m was used to obtain geographical coordinate of salt affected area. GIS assisted spatial analysis and modeling of the data collected (field and SRS) were carried out through data preprocessing of images clipped in ArcGIS 9.2 and ERDAS IMAGINE softwares, also image classifications were done using maximum likelihood method and Markov change prediction algorithm developed in IDRISI for the models.
There were 12 observations for each of three variables considered; temperature, rainfall and relative humidity. The average yearly temperature of the study area increases insignificantly by a constant of about 0.1168444. Coefficient of variation (CV) for temperature was found to be about 29.59 while the variance of this set of observations is 26.63. The involvement of non-zero values in the serial correlation indicated the significance of the deterministic component in the data. The Pearson correlation coefficient was used to test for the relationship between rainfall and temperature in order to determine their effect on the buildup of soil salinity. Their relationship is significantly negative with P < 0.05. The analyses of water samples from main, northern and western canals of VHS indicated corresponding average electrical conductivities of 0.009, 0.012 and 0.011 mmho/cm and mean SARs of 3.53, 3.00 and 3.89 respectively for the three canals. Electrical conductivity (EC) and total dissolved solids obtained are indicators of salinity. All the three water samples gave adjustable RNA of 0.12 to 0.17, thus indicating a medium to high salinity and sodium hazard tendencies in the scheme. The static land use / land cover distribution pattern of VHS for the year 1991 to 2005 revealed a drastic change in the normal course of cultivated land. The year 2005 showed a remarkable increase of area of fallow land depicting a scenario of a likelihood of salinity problem. The overall percentage of fallow land has increased by 37.86 %; settlement or built-up area decreased by 18.97 %, water bodies decreased by 0.48 % and cultivated / irrigated land area also decreased by 18.21 %. The land use / land-cover map was classified with an overall accuracy of 93.14 %.
The temporal trend showed that there has been an increase in the area occupied by salt between 1991 and 2005. It was shown that the area covered by salt increased from 7,077.97 Km2 in 1991 to 7,117.61 Km2 in 2001 and to 12,651.52 Km2 in 2005. This means an increase of 39,642 Km2 were actually covered between 1991 and 2001 while this increased significantly to 5,533.91 Km2 between 2001 and 2005. It was observed during the modeling, that there is the probability that much of the community area will show visible sign of salt (surface salinity) cover of 46% over the next fifteen years (2005 to 2020).
An overall conclusion drawn from this study is that the results obtained have shown the feasibility of using SRS (Landsat ET and ETM+) data and GIS to estimate soil salinity trend in VHS. Maps and model developed on salinity in this study are of great importance to planners, project engineers and managers in monitoring the consequences of land use change on the scheme. Based on this result, there is, therefore, an urgent need for management programme to be initiated in order to control the spread of salinity and reclaim the damaged land in order to make the scheme more economically viable.
... altitud, pendiente, radiación solar o la influencia de la topografía en los procesos hidrológicos, son algunas de las más utilizadas en el análisis de los patrones de la vegetación (Pons y Solé-Sugrañes 1994, Florinsky y Kuryakova 1996, Serra-Díaz et al 2011). El factor climático es bien conocido como determinante, y la dinámica del clima es responsable de la dinámica y transiciones entre especies en muchas partes del planeta (Kelly y Goulden 2008). ...
La eficacia de la vegetación en la colonización del espacio depende de la influencia que los factores del medio tienen sobre las distintas especies. Analizar la sucesión o los patrones de cambio forestales puede ayudar a predecir nuevas situaciones y a definir protocolos más eficaces en la gestión del medio natural. Aquí presentamos algunos resultados de un estudio más amplio en el que se analiza la dinámica de la vegetación en la Península Ibérica. El ámbito del presente trabajo es el cuadrante nororiental de la Península. El avance que presentamos se centra en la sucesión a estratos forestales de tres grupos de vegetación en función de una serie variables. Los patrones de cambio se han obtenido a partir de la clasificación de imágenes de satélite Landsat. Para determinar las variables más importantes y de qué manera éstas influyen en la dinámica de la vegetación, se ha empleado el método Boosted Regression Trees. La influencia de variables como la radiación solar y la recurrencia de sequías ha sido clave en la comparación entre diferentes transiciones. Especies mediterráneas y sub-mediterráneas del género Quercus se han mostrado tolerantes a la sequía mientras que se ha encontrado una asociación negativa entre las transiciones a coníferas y la recurrencia de sequías.
ABSTRACT:
Precise knowledge of the factors driving vegetation dynamics is essential in order to understand the natural landscape configuration. Moreover, this information can be very useful for planning and management strategies. In this paper we present results of a broader study that aims to identify the conditions that drive succession stages and vegetation shifts in the Iberian Peninsula. The study area of the present work is located in the NE Peninsula. As a preliminary report, three vegetation transitions (to mature stages) have been analyzed by relating them to several variables. Land-covers were classified from three Landsat scenes for the period 1987-2012. Boosted regression trees were used to identify the most important variables and describe the relationships between the vegetation dynamics and key factors. Topography derived variables (such as solar radiation) and drought have been shown to be key factors when comparisons are made between vegetation groups. Successions from shrubland towards Mediterranean and sub-Mediterranean Quercus spp. forests are driven by drought tolerance, but under favorable topo-climatic conditions of water availability. In contrast, shifts to conifers species take place at sites with less drought severity.
... The spatial pattern derived from the topography is a structural factor that explains much of the vegetation distribution. Interactions between topography-derived variables, such as altitude, slope, solar radiation or topographic effect on hydrological processes, are some of the factors most widely used in differentiating vegetation patterns (Pons and Solé-Sugrañes, 1994;Florinsky and Kuryakova, 1996;Burrough et al., 2001;Allen et al., 2004;Bennie et al., 2006;Serra-Díaz et al., 2011;Moeslund et al., 2013). The role of fire occurrence is another important issue for analyzing vegetation spatial-patterns and stability of certain plant communities (Diaz-Delgado and Pons, 2001;Salvador et al., 2005;Pausas and Keely, 2009). ...
In southern Europe, climate trends are expected to be characterized by an increase in temperatures and less water availability. Analyzing the role of structural factors and the influence of a changing climate provides insights into the evolution of forest ecosystems in regions with similar environmental conditions. The Mediterranean fringe of the Iberian Peninsula is of particular interest due to its diverse topo climatic conditions and the increase in drought episodes during the last decades. This work studies forest dynamics in large areas of this geographical region by analyzing nine forest transitions. Vegetation covers were classified from three Landsat scenes for the period 1987-2012, and sub-periods 1987-2002 and 2002-2012. Conditions were described by topography derived variables, human factors and drought-occurrence variables. Boosted regression trees were used to identify the most important variables and describe the relationships between the forest dynamics and key factors. Variables such as solar radiation, topographic wetness index and tolerance to drought have been shown to be key factors in forest succession and when comparisons are made between vegetation groups. Main findings: The transition rate to Mediterranean and sub-Mediterranean broadleaf forests has increased during the analyzed period, while the transition rate to coniferous forests has decreased; Transitions to Mediterranean and sub-Mediterranean broadleaf forests are positively associated with drought occurrence while transitions to conifers are negatively affected by drought; Transitions from shrublands to forest stages are more vulnerable to factors controlling water availability; Important interactions between topography derived variables and drought have been found. The study provides robust evidence that drought occurrence plays an important role in the decline of conifers and the expansion of broadleaves, which could become the dominant species in many areas of the Mediterranean if climate model forecasts are met.
... The spatial resolution of the SPOT images made them highly suitable for mapping land surface properties and monitoring natural environments at a local scale. To aid in the interpretation, the images were radiometrically corrected as described in Pons and Solé-Sugrañes (1994) using the ENVI (Exelis Visual Information Solutions, USA) image processing software. Colour infrared (CIR) band combination was used for the visual identification of the hydrologic landscapes through the detection of areas with different hydrological and ecological properties and the presence of human-made structures. ...
Coastal wetlands rank among the most endangered ecosystems since they are affected by the sea level rise and by anthropogenic activities. The continued loss and degradation of these valuable environments requires that a great deal of attention be given to groundwater–surface water exchange, as the ecological function of coastal wetlands greatly depends on it. Hydrological research carried out in the lower part of the Samborombón Bay coastland (Río de la Plata estuary, Argentina) by remote sensing revealed the presence of a meandering channel system, which does not appear in modern maps. The analysis of SPOT satellite images, the interpretation of historical maps and in situ surveys confirmed that this structure is part of an ancient river system, the palaeo-Rincón de Ajó River, at present almost completely silted up. In addition, multispectral satellite data provided the information to develop a conceptual hydrological model, as well as evidence that a significant hydrologic landscape shift occurred due to man-made interventions. The palaeo-Rincón de Ajó River disappeared because the water flow in its upper course was intercepted by man-made canals, and in its lower course the embankments built for the construction of roads and to prevent the flooding of the wetlands from the Río de la Plata estuary excluded the surface flow from the estuary to the mainland and vice versa. The silting up in the lower course and in the vicinity of the mouth cancelled the original structure of the ancient river.
... Radiometric correction allows for the reduction of environmental variables and allows for consistent extraction of reflectance values (Pons and Sole-Sugranes 1994;Edirisinghe, Louis, and Chapman 1999;Karpouzli and Malthus 2003;Kelcey and Lucieer 2012). We used empirical linear regression to radiometrically correct images from our camera. ...
Open source, low cost sensors, and robotic systems have developed to the point of being able to produce meaningful, repeatable results in real-life applications. We developed a low-cost, open source multispectral camera mounted on a small custom-built robotic rover. We compared the performance of our camera with a commercial multispectral camera and a laboratory spectrometer using minerals commonly found on Mars that exhibited different reflectance values in visible and near-infrared wavelengths. Our camera performed favourably when compared to the commercial instruments. It is a very cost effective solution for operating in extreme situations, where damage to instruments is possible. Our total system of rover and sensor would, therefore, be very useful for operating in delicate and inaccessible environments where damage to the area under investigation and to human observers is of concern.
... Images were then atmospherically corrected and transformed into reflectance values using the Pons and Solé-Sugrañes [46] method based on the dark object model [47]. No topographic correction was applied since in the study area relief is negligible (the study area range being less than 10 m a.s.l.). ...
This paper presents a semi-automatic procedure to discriminate seasonally flooded areas in the shallow temporary marshes of Doñana National Park (SW Spain) by using a radiommetrically normalized long time series of Landsat MSS, TM, and ETM+ images (1974-2014). Extensive field campaigns for ground truth data retrieval were carried out simultaneous to Landsat overpasses. Ground truth was used as training and testing areas to check the performance of the method. Simple thresholds on TM and ETM band 5 (1.55-1.75 μm) worked significantly better than other empirical modeling techniques and supervised classification methods to delineate flooded areas at Doñana marshes. A classification tree was applied to band 5 reflectance values to classify flooded versus non-flooded pixels for every scene. Inter-scene cross-validation identified the most accurate threshold on band 5 reflectance (ρ{variant} < 0.186) to classify flooded areas (Kappa = 0.65). A joint TM-MSS acquisition was used to find the MSS band 4 (0.8 a 1.1 μm) threshold. The TM flooded area was identical to the results from MSS 4 band threshold ρ{variant} < 0.10 despite spectral and spatial resolution differences. Band slicing was retrospectively applied to the complete time series of MSS and TM images. About 391 flood masks were used to reconstruct historical spatial and temporal patterns of Doñana marshes flooding, including hydroperiod. Hydroperiod historical trends were used as a baseline to understand Doñana's flooding regime, test hydrodynamic models, and give an assessment of relevant management and restoration decisions. The historical trends in the hydroperiod of Doñana marshes show two opposite spatial patterns. While the north-western part of the marsh is increasing its hydroperiod, the southwestern part shows a steady decline. Anomalies in each flooding cycle allowed us to assess recent management decisions and monitor their hydrological effects.
... The effect of the relief of the land surface was taken into account by using a digital elevation model (Palà and Pons, 1995), and a mean RMSE less than 15 m was obtained. Radiometric correction was carried out following the methodology proposed by Pons and Solé-Sugrañes (1994), which allows us to reduce the number of undesired artifacts due to the atmospheric effects or differential illumination that are results of the time of day, the location on the Earth and the relief (zones being more illuminated than others, shadows, etc). The digital numbers were converted to radiances by means of image header parameters, taking into account the considerations 15 presented by Cristóbal et al. (2004) andChander et al. (2009). ...
Evapotranspiration monitoring allows us to assess the environmental stress on forest and agricultural ecosystems. Nowadays, Remote Sensing and Geographical Information Systems (GIS) are the main techniques used for calculating evapotranspiration at catchment and regional scales. In this study we present a methodology, based on the energy balance equation (B-method), that combines remote sensing imagery with GIS climate modelling to estimate daily evapotranspiration (ETd) for several dates between 2003 and 2005. The three main variables needed to compute ETd were obtained as follows: (i) Land surface temperature by means of the Landsat-5 TM and Landsat-7 ETM+ thermal band, (ii) air temperature by means of multiple regression analysis and spatial interpolation from meteorological ground stations data at satellite pass, and (iii) net radiation by means of the radiative balance. We calculated ETd using remote sensing data at different spatial and temporal scales (TERRA/AQUA MODIS and Landsat-5 TM/Landsat-7 ETM+) and combining three different approaches to calculate the B parameter. We then compared these estimates with sap flow measurements from a Scots pine ( Pinus sylvestris L. ) stand in a Mediterranean mountain area. This procedure allowed us to better understand the limitations of ETd modelling and how it needs to be improved, especially in heterogeneous forest areas. The method using Landsat data resulted in a good agreement, with a mean RMSE value of about 0.6 mm day−1 and an estimation error of ±30%. The poor agreement obtained using MODIS data reveals that ETd retrieval from coarse resolution remote sensing data is troublesome in these heterogeneous areas, and therefore further research is necessary on this issue.
... Scenes used were geometrically corrected following Palà and Pons methodology [9] implemented on CorrGeom module of the MiraMon software [10]. Radiometric correction was carried out with CorRad MiraMon module, following Pons and Solé-Sugrañes methodology [11]. A mask obtained from the Mapa de Cobertes del Sòl de Catalunya (Land Cover Map of Catalonia) was applied over the original images (after they had been geometrically and radiometrically orthocorrected) in order to classify only the areas of vegetation land cover (see Figure 2). ...
This study measures how lossy image compression affects digital classification of natural areas. A mixed classification method comprising satellite images and topoclimatic variables for mapping vegetation land cover was used. The results contribute interesting new data about the influence of compression on the quality of the cartography produced, both from a "by pixel" perspective and also regarding the homogeneity of the polygons obtained. When classifications were carried out only with radiometric variables the area classified increases with CR, although the increase is smaller for JPEG2000 formats, especially in fragmented areas. On the other hand, the area classified decreases in classifications which also take into account topoclimatic variables. Overall image accuracy diminishes at high compression levels, although the point of inflection occurs in different places depending on the compression format (highest accuracy for JPEG and fragmented images occurs at lower compression levels). As a rule, the JPEG2000 format gives better results both quantitatively (accuracy and area classified) and visually (images with less "salt and pepper" effect).
The weighted contribution of ground-reflected component of light emissions from artificial sources gradually
increases as the transitioning from bad-shielded to modernized light sources with low or zero direct uplight takes
place in cities or towns. In this work, we demonstrate that the modeling of reflected light on a large domain for
Lambertian flat surfaces does not require information about the height of the light sources and directional distribution of photons their produce. This kind of "invariance principle" becomes invalid when the homogeneity
condition for the surface albedo is violated. However, we have shown that an analytical solution exists also for
position-dependent albedo and even for angle-dependent reflectance which is the effect we now include to the
light pollution models for the first time. This effect is known from the observation of sunbeams entering uneven
surfaces at different zenith angles. Here in analogy with that daylight model we derive formulae for ground
surfaces illuminated by artificial lights located at different heights above the surrounding terrain
The dieback on the Juniperus Phoenicea in Al-Jabal Al-Akhdar north east of Libya was reported without proof of disease causative in 2014 and 2016. This investigation carried out to reveal the cause of the disease. The spatial statistics method was used to determine the relationship between disease and other environmental variables (Land surface temperature, elevation, slope, rainfall, and the distance from coast). Random sampling of the trees branches were taken from most of the forests of the region. The study indicated that the isolated microorganism of the dieback on the Phoenician Juniper recognized a fungal infection of Diplodia Africana by analyzing culture, morphological, and PCR of genomic TSI and 1-alpha gene. The result shows that the most infected sit is that the closer to the coast which was confirmed with strong negative correlation (-0.583), furthermore the relation with the elevation showed same direction with (-0.604), while the LST presented positive correlations (0.367) thus confirming the significant effect of temperature in increasing these diseases.
Wildlife Corridor, Wildlife Connectivity, Distance Sampling, Aerial Survey, Human Activity
Estimating the resilience time of an ecosystem may lead to different values depending on the compartment or function of interest and the measurement method. We sought to estimate the resilience of a cork oak (Quercus suber L.) stand – a typical west Mediterranean forest type – 8 years after a wildfire, using three independent indicators. Each represents a function or a characteristic of the ecosystem: (i) the Normalized Difference Vegetation Index (NDVI), a remote sensing-based proxy of photosynthetic activity, (ii) the vegetation profile, based on an estimation of the vegetation cover at different heights above ground, and (iii) the avifauna composition, a component of animal biodiversity. The NDVI seems to have recovered a value close to its pre-fire value about 9 years after the fire. Recovering a vertical vegetation profile similar to that before the fire requires a longer time, tentatively estimated to not less than a dozen years. Recovery of the pre-fire avifauna is likely to require an even longer time, which could not be estimated from our 8-year monitoring period. The indicator based on avifauna appears to be the most discriminating indicator, among the three compared here, for estimating the time required for full recovery of the ecosystem over the long term.
Based on Monteith's model (1972), growing biomass (∆ANPP) can be calculated as a function of photosynthetically active radiation absorbed by green vegetation (APAR) and conversion efficiency of radiation into biomass (LUE). Above-ground biomass (g m-2) and the fraction of photosynthetically active radiation absorbed by vegetation (fPAR) were measured on meadows and pastures in Vall Fosca (Catalan Pyrenees) over six field campaigns taking place in late spring-summer, 2009. Landsat-5 and SPOT-4 imagery were used to determine NDVI effectiveness to predict fPAR, as an indirect method for calculating APAR. Increase in above-ground biomass was related to APAR in two ways. First, by considering LUE an invariable factor, and secondly, by calculating LUE from field measures and analyzing its variability in relation to precipitation and temperature (both measured by an experimental weather station). fPAR was found to fit well with NDVI (R 2 around 0.8), so was the fit between APAR and ∆ANPP (R 2 around 0.7).
Grassland availability in meadows and pastures strongly determines extensive stockbreeding in Catalan Pyrenees. Satellite images together with on-site data sampling are used to quantify the resource in terms of biomass production. Several vegetation indexes-NDVI, EVI, Greenness-and wetness indexes-NDWI, Wetness-have been calculated from Landsat-5 TM images. They have been then related to grass production variables ("fresh weight", "dry weight") sampled along five different field campaigns by means of a multiple regression model. Model's predictors have been selected on the basis of Mallows' Cp. As a result, biomass maps have been obtained for every sampling date within the areas of interest, that is, meadows and pastures. Results from statistical analysis are not uniform. R 2 values range from 0.32 to 0.90 for the "fresh weight" variable and from 0.26 to 0.67 for the "dry weight" class. This reflects the variation in both environmental and vegetation conditions.
La determinació de la superfície nival és essencial per calcular el volum d'aigua que drena cap a les conques hidrològiques procedent de la fusió nival. El coneixement d'aquesta coberta es pot abordar a partir de la presa de dades puntuals durant campanyes de camp i la seva posterior interpolació, tot i aquesta darrera via no acostuma a proporcionar una cobertura espacial i temporal de prou detall i qualitat. Altrament, i precisament per la seva resolució espacial i temporal, la Teledetecció pot proporcionar una bona estimació de la coberta. En aquest article s'exposa la metodologia utilitzada per la detecció de la coberta nival de Catalunya mitjançant l'ús d'imatges Landsat-7 ETM+ i Landsat-5 TM durant el període 2002-2006.
Monitoring real daily evapotranspiration by means of Remote Sensing and geographical information systems: the case of the Foix basin Monitoring evapotranspiration has major implications for the global and regional modelling of the climate and knowledge of the hydrological cycle, as well as for advising on the environmental stress which affects agricultural and forestry systems. Moreover, evapotranspiration is related to phenomena of great interest in the management of natural areas such as fire prevention and the net primary production of ecosystems. Teledetection and geographical information systems (GIS) are the only technologies today that can provide the necessary measurements for calculating real evapotranspiration globally and in an economically feasible way. This work presents the first results of the modelisation of daily actual evapotranspiration (ET d) on a regional scale of the Foix basin, by means of a temporal series of 17 images from the Landsat-7 ETM+ satellite and geographical information systems over the period 2002-2003. The result is a set of 17 digital maps with a spatial resolution of 60 m and an almost monthly temporal resolution of ET d. For the determination of ET d the semiempirical method proposed by Seguín and Itier (1989) has been used, for which three variables have to be calculated: the temperature of the land surface, the temperature of the air and net radiation, obtained by the combined use of the information from the satellite images and modelisation with the GIS. The results obtained have been of great value in obtaining ET d data for forestry and agricultural occupation and for the high spatial and temporal resolution of the cartography produced.
Actual Daily Evapotranspiration through Remote Sensing and Geographic Information Systems: the Case of Montseny Natural Park Monitoring evapotranspiration provides contributions to global and regional climate modelling and the knowledge of the hydrological cycle, as well as for assessing the environmental stress affecting agricultural and forestry ecosystems. In addition, evapotranspiration is related to phenomena of high interest for the management of natural areas, such as forecasting fire and the net primary production of ecosystems. Remote sensing and Geographic Information Systems (GIS) are currently the only technologies capable of providing the measurements for calculating actual evapotranspiration in a global and economically feasible manner. This paper presents the first results of modelling of actual daily evapotranspiration (AET d) on a regional scale, namely for the Montseny Natural Park, through eleven images taken at different times by the Landsat-7 ETM+ satellite and geographic information systems during the 2002-2003 period, the results being a series of seventeen digital maps with a spatial resolution of 60 m and a nearly monthly temporal resolution of AET d. To determine the AET d , the semi-empiric method employed was that proposed by Seguin and Itier (1989), which requires the calculation of three variables: the temperature of the land surface, the temperature of the air and net radiation, obtained by the combined use of the information from satellite images and GIS modelling. The results obtained were of great value due to the difficulty of obtaining AET data for forest and agricultural land covers and the high spatial and temporal resolution of the maps obtained.
Spatiotemporal change analysis of semiarid regions is vital for understanding major threats to the ecosystem. This study examines land use and land cover (LULC) changes using multitemporal satellite imagery for the period 1972–2010. Supervised classification algorithm using support vector machines (SVM) was employed to monitor LULC transformations. A cross-tabulation matrix was used to assess the total change of land categories based on net change and swap change. The major land use change in this dynamic region were conversion of about 52 % woodlands to intensive land uses such as cropland in the period 1972–2010. The net change of woodland accounts for over 61 % and net-gain of cropland and grassland were about 53 % and 9 % respectively. Based on the socio-ecological field survey expansion of croplands, population pressure as well as overharvesting of trees, respectively, are major drivers of change. This significant change in land use is mainly due to accelerated human impact and subsequent agricultural land expansion.The result of this study provides a vital monitoring basis for continuous investigations of changes in the natural vegetation of semiarid environments.
p>Mapping fire severity is determinant to understand landscape evolution after a wildfire and provides useful information for decision making during post fire management. Quantitative fire severity mapping from relative changes in Normalized Burn Ratio index (RdNBR) is not actually being incorporated into decision making processes, being more useful the categorization in severity levels (high, moderate and low). However, the most common mapping severity methodologies based on the definition of RdNBR thresholds from field information are not always possible due to lack of field data or because the published thresholds are unsatisfactory in new regions. The boom in the use of UAVs (Unmanned Aerial Vehicle) has raised these platforms as potential tools for validation of remote sensing data. This paper presents the potential of UAVs as ground truth information in forest fires. From the photointerpretation of high resolution RGB images, the Aerial Severity Proportion Index (ASPI) has been created. Non-linear regression models between RdNBR and ASPI allows to delimitate of thresholds for the classification of Landsat images and to obtain qualitative severity maps. Validation with random points presents a kappa index of 0,5 and a relative accuracy of 70,8%. Therefore, UAV images become a very useful tool for wildfire severity mapping and for fill the gap between remote sensing information and expensive field ground campaigns</p
A comparative analysis is presented for empirical topographic normalization of Landsat Thematic Mapper (TM) data in varied forest and topographic settings. The paired study included rugged areas of Glacier National Park, Montana, Linville Gorge Wilderness, North Carolina, and Green Mountains, Vermont, U.S.A. Empirical models of topographic bias achieved significant corrections in the Montana and Vermont sites. Relative homogeneity of forest structure offset rugged topography in Montana to yield the highest success of normalization. Significant models could not be derived for Linville Gorge. Topographic normalization is most successful when canopy complexity and altitudinal zonation are low to moderate. Atmospheric pollution and geologic control in ridge-valley alignment are important considerations when undertaking topographic normalization in mountain environments.
Vegetation recovery from fire has been widely studied at the stand level in many types of terrestrial ecosystems, but factors controlling regeneration at the landscape scale are less well known. Over large areas, fire history, climate, topography, and dominant type of vegetation may affect postfire response. Increased fire frequency, as is occurring in some mediterranean-type ecosystems, may reduce ecosystem resilience, i.e., the ability to recover the pre-disturbance state. We used the Normalized Difference Vegetation Index (NDVI) from Landsat imagery to monitor vegetation recovery after successive fires in a 32 100-km2 area of Catalonia (northeastern Spain) between 1975 and 1993. In areas burned twice, NDVI patterns indicated that regrowth after 70 mo was lower after the second fire than after the first. This trend was observed several years after burning, but not immediately following fire. Green biomass after the second fire significantly increased with longer intervals of time between fires. There was also a positive correlation between postfire NDVI and mean rainfall, whereas a negative correlation was found between NDVI and solar radiation. Forests dominated by resprouting Quercus spp. were more resilient to fire, but they showed a larger decrease in resilience after the second fire than did forests dominated by Pinus spp. that regenerate from seed. We conclude that the use of time series satellite images may help to gain further insights in postfire vegetation dynamics over large regions and long time periods.
This paper analyses the urban heat island in Zaragoza (Spain) and its spatial patterns. Moreover, the main structural and urban factors that affect this phenomenon are analysed. We created a data base of air temperature by means of urban transects. The data was used to develop air temperature maps of 27 days. We analysed the relationships between the spatial patterns of the urban heat island, the main geographic-urban factors within the city and the role of surface winds on spatial variability of the urban heat island. The results indicate an important influence of topography, edification density, vegetation cover and reflectivity of materials to explain the spatial distribution of urban heat island. Moreover, the differences in the spatial patterns of the urban heat island are explained by dominant winds of NW and SE direction.
The Alt Empordà plain (north-east of Catalonia) in the 1970s presented an intensely humanized and diversified landscape as a result of human action over the centuries. The use of remote sensing for land use location of 1977 and 1993 allows us to detect and analyse the produced changes, during these years, in the study area: intensification of certain herbaceous crops, increase of urban surface and tendency to the homogenisation of the landscape. The methodology used for available digital images classification has taken into account plot fragmentation, typical of Mediterranean landscape, and the high temporal dynamics of herbaceous crops, predominant in the area.
A main problem encountered in radiometric calibration of satellite image data is correcting for atmospheric effects. Without this correction, an image digital number (DN) cannot be converted to a surface reflectance value. In this paper the accuracy of a calibration procedure, which includes a correction for atmospheric scattering, is tested. Two simple methods, a stand-alone and an in situ sky radiance measurement technique, were used to derive the HAZE DN values for each of the six reflectance Thematic Mapper (TM) bands. The DNs of two Landsat TM images of Phoenix, Arizona were converted to surface reflectances. -from Author
Studies that use multitemporal images require the conversion of original digital data into the corresponding physical magnitudes. Atmospheric correction is one of the most important steps in this process, which is usually undertaken using atmospheric radiative transfer models. The main difficulty in these models is the need of atmospheric input data which are not usually available. An alternative approach to atmospheric correction is proposed in this Letter. It is based on the idea that the atmospheric effects over two or more dates can be determined in a relative way, by using the apparent reflectance values of surfaces whose ground reflectance can be considered unchangeable with time. This method has been applied to correct Landsat-5 Thematic Mapper images and satisfactory results have been obtained in comparison with those obtained by a traditional model.
Digital analysis of remotely sensed data has become an important component of many earth-science studies. These data are often processed through a set of preprocessing or “clean-up” routines that includes a correction for atmospheric scattering, often called haze. Various methods to correct or remove the additive haze component have been developed, including the widely used dark-object subtraction technique. A problem with most of these methods is that the haze values for each spectral band are selected independently. This can create problems because atmospheric scattering is highly wavelength-dependent in the visible part of the electromagnetic spectrum and the scattering values are correlated with each other. Therefore, multispectral data such as from the Landsat Thematic Mapper and Multispectral Scanner must be corrected with haze values that are spectral band dependent. An improved dark-object subtraction technique is demonstrated that allows the user to select a relative atmospheric scattering model to predict the haze values for all the spectral bands from a selected starting band haze value. The improved method normalizes the predicted haze values for the different gain and offset parameters used by the imaging system. Examples of haze value differences between the old and improved methods for Thematic Mapper Bands 1, 2, 3, 4, 5, and 7 are 40.0, 13.0, 12.0, 8.0, 5.0, and 2.0 vs. 40.0, 13.2, 8.9, 4.9, 16.7, and 3.3, respectively, using a relative scattering model of a clear atmosphere. In one Landsat multispectral scanner image the haze value differences for Bands 4, 5, 6, and 7 were 30.0, 50.0, 50.0, and 40.0 for the old method vs. 30.0, 34.4, 43.6, and 6.4 for the new method using a relative scattering model of a hazy atmosphere.
Mapping of snow and estimation of snow characteristics from satellite remote sensing data require that we distinguish snow from other surface cover and from clouds and compensate for the effects of the atmosphere and rugged terrain. The spectral signature of the snowpack is calculated from a radiative transfer model, accounting for scattering and absorption by the ice grains, water inclusions, and particulates. In interpreting the spectral reflectance measured from the Thematic Mapper, or from any other satellite, we need to account for topographic effects without requiring that satellite data be precisely registered to digital elevation data, because the poor quality of most digital elevation data introduces considerable noise into calculations of slope and azimuth. For a range of snow types, atmospheric profiles, and topographic illumination conditions, I estimate typical spectral signatures for the Landsat Thematic Mapper. TM images of the southern Sierra Nevada are analyzed to distinguish several classes of snow from other surface covers. Snow can be reliably distinguished from other surfaces and from clouds at all sun angles encountered in the mid-latitudes. In TM Band 1 or 2, snow is brighter than other natural surfaces, and in Band 5 clouds are usually much more reflective than snow. Therefore, the intersection of the following criteria maps the snow cover: planetary reflectance Rp in TM Band 1 is greater than about 0.16; Rp (TM5) is less than about 0.2; the normalized Band 2 – 5 difference, [Rp(TM2) − Rp(TM5)] / [Rp(TM2) + Rp(TM5)], is greater than about 0.4. Large surface grain sizes can be distinguished from areas where the grain size is finer at the snow surface, using TM Bands 2, 4 and 5. Because of saturation in TM Band 1, estimation of the degree of contamination by absorbing aerosols is not feasible. [Rp(TM2) − Rp(TM5)]/[Rp(TM2) + Rp(TM5)], is
An algorithm is developed for calculating the horizons for each point in a digital terrain grid in order N iterations, whereas all previous methods seem to be of O(N2) time complexity. The new method makes horizon computations reasonable, and ought to improve the accuracy of surface climate models in rugged terrain.
It appears that the development of machine vision may benefit from a detailed understanding of the imaging process. The reflectance map, showing scene radiance as a function of surface gradient, has proved to be helpful in this endeavor. The reflectance map depends both on the nature of the surface layers of the objects being imaged and the distribution of light sources. Recently, a unified approach to the specification of surface reflectance in terms of both incident and reflected beam geometry has been proposed. The reflecting properties of a surface are specified in terms of the bidirectional reflectance-distribution function (BRDF). Here we derive the reflectance map in terms of the BRDF and the distribution of source radiance. A number of special cases of practical importance are developed in detail. The significance of this approach to the understanding of image formation is briefly indicated.
In the solar reflective region (0.4 - 3 μm) the signal of satellite sensors viewing mountaineous terrain strongly depends on topographic effects, solar illumination, and atmospheric parameters. The proposed correction algorithm calculates the surface reflectance for each pixel of an image employing a digital terrain model and the altitude profile of atmospheric data (standard atmosphere or measured data, e.g. radiosonde). As a final step the adjacency effect can be accounted for in an approximate manner. Results are presented for a Landsat TM scene of the Black Forest in Germany. -Authors
Described are field measurements of daylight radiation reflected upward from the crowns of six tree species in visible and near-infrared frequencies of the electromagnetic spectrum. A portable mast and two permanent towers provided platforms for a spectroradiometer at a height of 3 to 5 m above the tree canopy. Each site was measured on at least two different dates to account for variations in species' phenological stages during the summer season. In addition, some of the species were measured in two different locations. Described are the instruments used for the measurement of incident and reflected daylight radiation, the field measurement technique and computational procedure.
Describes the current knowledge of, and mathematical treatment for, the interaction mechanisms of electromagnetic radiation with terrain elements at optical wavelengths. A brief discussion of the scene radiation dynamic processes and modelling perspectives in the optical region is introduced. Then, a detailed mathematical framework with some examples for these energy processes and their relationships to remote sensing is discussed. Finally, applications of these relationships to terrain-feature response are presented.-M.Alam
The complexities and detail of urban scenes make it imperative that atmospheric effects are removed from satellite remotely sensed data prior to analysis. A study of atmospheric theory allows a simplified procedure to be developed for correction of multitemporal LANDSAT MSS scenes. Examples in the visible and near infrared, from a summer and winter scene, illustrate how disparate count values can be brought to good agreement as percentage reflectance.
A simple geometrical model has been proposed for a citrus canopy. We assume the citrus orchard to be a lattice structure, with the trees positioned at its points and where the composite-scene reflectance is the sum of the reflectance of its individual components as weighted by their respective surfaces within a unit area. The model has been used to analyse the citrus spectral response obtained from Landsat-5 TM images for winter and summer, where the status of the orchard is different. The correlations between spectral and geometrical data show the influence of per cent crop cover, shadows and background in the composite scene reflectance. We conclude that the summer images could be more useful than the winter ones for parcel classification according to per cent crop cover.
Remote sensing of the Earth may be traced back to the first prehistoric explorer who climbed a nearby hill to study the lay of the land. But it was not until 150 years ago that Louis Jacques Mande Daguerre and Joseph Nicéphore Niepce invented the daguerreotype, which provided the foundation for modern photography and, through it, a means to record a remotely sensed image. Twenty years later, in 1859, Gaspard Félix Tournachon Clateu (later known in the literature as Félix Nadar) took the first known aerial image from a balloon. That set the stage for the use of balloon‐based cameras by Union troops to photograph Confederate defenses around Richmond, Virginia, during the Civil War. Kites were also used as platforms for early photography. A particularly notable example is a very‐large‐format image (1.4×2.4 m ) taken by G. R. Lawrence after the 1906 San Francisco earthquake and fire. A cluster of 17 kites flown from a ship in the bay carried the camera aloft. The first known photos from an aircraft were taken in 1909 in Italy by a passenger in a plane piloted by Wilbur Wright. Aerial photography was used for reconnaissance during World War I and was further developed for that purpose during World War II, resulting in the creation of special cameras and films, including color and color infrared film for detecting camouflage. Space‐based and aerial images can provide information about Earth resources, agricultural conditions, weather patterns and a host of other phenomena that would be impossible to observe from the ground.
Techniques were applied to alleviate topographic influences on a TM scene prior to land-cover classification for mobility modeling. Illumination models were created using two different resolutions of DEM data. These illumination models were based on linear regression of the two parts (cosine and sine) of the equation for the incidence angle of the solar beam with the first principal component of the TM data. A topographic normalization procedure was applied to correct the TM data utilizing the derived models. The near IR band required a completely different model because of high correlation between areas of high relief and vigorously growing vegetation. Results are presented showing improved utility for visual interpretation and land-cover classification on the corrected data.
Plant scientists are finding considerable use for false color aerial photography with Ektachrome Infrared Aero Film to distinguish vegetation types and to assess plant vigor. The basis for differences in the colored imagery of healthy and damaged plants on this infrared- and visible-sensitive film is their difference in reflectance in these spectral regions. Healthy leaves have a high infrared reflectance and a low visible reflectance, the latter due to a strong pigment absorption. The high infrared reflectance of leaves appears to be determined by their cellular and subcellular structure, but direct experimental evidence for the precise mechanism of internal reflectance is lacking. Any physiological disturbance to a leaf nearly always results in an increase in the visible reflectance, but the changes in infrared reflectance are variable. In addition to being dependent on the reflectance characteristics of individual leaves, the quantity and quality of energy reflected from vegetation surfaces is a function of the spectral distribution of incident solar radiation, the plant or crop geometry, and the relative amount of foliage and other reflecting surfaces. (Author)
Information on grassland quality is required to assess the impact of agricultural policy in Europe. Field methods are time-consuming and local in scope, but may provide a basis from which to extrapolate using remotely sensed data. For thirty-eight fields in the Lorraine region of France floristic descriptions, agricultural observations, biomass, ground radiometric data and SPOT HRV data were collected during June, July and September 1986 and April 1987. Agronomical and phytosociological classifications of grassland management type and by inference grassland quality, yielded similar results but the phytosociological method was preferred as it could be quantified. Ground radiometric data and SPOT HRV data for all four seasons were used successfully to discriminate grassland quality but stratification by grassland quality did not increase the degree of correlation between remotely sensed data and vegetation amount. This research highlights the potential that exists for using SPOT HRV data, in conjunction with a phytosociological classification of grassland quality, to classify and then monitor, the quality of grasslands in Europe.
Research actions carried out by the Mercantour National Park include natural environment inventories and management actions. Their aim is to reconcile protection of the environment, rehabilitation of abandoned agricultural land and the actual development potential of these low-value but high-potential areas. Among the available tools, a computerized geographical information system for the whole park seemed most useful and a survey is currently being carried out. Indeed, the geographical information sensing including remote-sensing data as a favoured variable is the answer to many of the problems of resource managers (storage, and retrieval of inventories, impact studies, assessment of time series). Work has been carried out combining SPOT imagery with a geographical information system covering the Mercantour National Park. Results are given in the following three areas; adaptation and usefulness of the two data sources; land-use mapping using SPOT data (by supervised classification); and monitoring of phytosanitary phenomena.
Landsat Thematic Mapper data, collected over central Michigan in the U.S.A., in October 1982, were digitally analysed to determine qualitatively and quantitatively their utility and potential to classify nine natural resources categories (e.g. red pine, jack pine, scotch pine, low conifers, hardwoods, grassland, water, wetland and other). Supervised classification with a maximum likelihood decision rule was employed to 22 especially selected single-, two-, three-, four- and six-band combinations (thermal band was excluded).Analysis of the six-band combination indicated an overall classification accuracy of 92.4 per cent. The producer's classification accuracy of individual categories was 79.7 per cent (scotch pine), 80.7 per cent (lowland conifers), 80.8 per cent (red pine), 88.7 per cent (jack pine), 92.8 per cent (wetland), 96.3 per cent (grassland), 96.6 per cent (hardwoods), 78.5 per cent (other) and 1000 per cent (water). After aggregation of pine categories the accuracy of the new category became 94.9 per cent and the overall 95.9 per cent. Three (3,4,5/2, 3, 4/2,4,5)-band combinations yielded very encouraging overall accuracies (88.9, 85.6 and 85.2 per cent respectively). The poorest results were obtained from analysis of two or three visible-band combinations. Single-band 5 yielded the best overall results, but band 4 seems to be the most useful, as it appeared in the best of each category of the three-band combinations.It was found conclusively that six-band combination of untransformed Thematic Mapper data was quite useful and successful for natural resources classification. However, certain three-band combinations gave very promising results that were acceptable for similar applications.
To study the interaction between the land surface and the atmosphere with satellite observations, terms of the surface energy balance must be determined with the support of field observations. Particularly, the determination of actual evaporation under hyperarid conditions requires that net radiation at the land surface be accurately known. Since net radiation is largely in excess of latent heat flux, the equilibrium temperature of the land surface depends more on net radiation than on latent heat flux. Net radiation depends basically on surface reflectance. In this paper a new approach is presented to obtain surface reflectance values with Thematic Mapper data by taking into account the dependence of surface reflectance on sun altitude, surface type, and the dew deposition— evaporation daily cycles. Surface-dependent formulae are obtained with ground measurements of hemispherical reflectance. Reflectance measurements have been collected in the Western Desert of Egypt at a number of sites with solarimeters in the spectral range 0.3–2.8 μm. By means of regression analysis relationships have been obtained to describe the reflectance characteristics of a number of land surface types which are characteristics of playas. Such relationships have been applied to a Thematic Mapper image of the depression of Siwa to obtain a hemispherical reflectance image relating to prespecified reference conditions. Mean values of reference hemispherical reflectance for each land surface type compared well with the values obtained with field measurements.
The estimability of all the canopy parameters for a vegetation canopy using only canopy reflectance (CR) data and the SAIL model is investigated, using techniques described earlier (Goel and Thompson, 1984a). It is shown that in principle such an estimation is possible, i.e., the SAIL model is mathematically totally invertible. An analysis of the sensitivity of the calculated values to changes in the CR data is presented. This analysis suggests that, given the expected accuracy of CR measurements and the accuracy of the SAIL model in representing CR in the infrared region, the agronomic parameters, leaf area index, and leaf angle distribution, can be estimated fairly accurately using ancillary data on spectral parameters.
The technique described earlier (Goel and Thompson, 1984b) for estimating agronomic parameters from bidirectional crop reflectance data is applied to a fully covered soybean canopy, using data measured in the field. This technique employs the inversion of a canopy reflectance model. It is shown that using the SAIL model one can estimate leaf area index (LAI) as well as average leaf angle (ALA) quite well, provided that the other canopy parameters (leaf reflectance and transmittance, soil reflectance, and fraction of diffused skylight) are known. Some suggestions are made for improving the SAIL model. This should improve the accuracy of estimation of not only LAI and ALA but should also allow the estimation of the complete leaf angle distribution.
Remotely sensed data are generally analyzed assuming flat terrain. As the spectral signature of the ground depends upon the orientation of the surface slope, the topography has to be considered for efficient radiometric corrections in mountainous regions. In this paper, we present a modelization of the atmospheric downward radiance at the ground level which gives us the relative contributions of the direct solar beam and of the diffused radiation for different atmospheric turbidities and different solar incidence angles. Lastly, we estimate the influence of the topography on these contributions to show up which effects can be neglected.
Digital numbers in SPOT-1 HRV multispectral imagery were transformed to reflectance factor values. This approach is based on a simplified-scene radiance equation that is developed in this paper. The values of some parameters needed in the equation such as path radiance, total normal optical thickness, and diffuse spectral irradiance were estimated by using multiple linear regression in a small test site of homogeneous ground cover, located within the study area. The calculated values of reflectance factors were presented by dimensionless digital numbers ranging from 0 to 255, which corresponds respectively to the values of reflectance factors from 0 to 1. The feasibility of this approach has been tested against the SPOT-1 HRV multispectral imagery above a canopy of Picaussel Forest of the Quillan region in the eastern pyrenean mountain in France.
In response to the need for a simple atmospheric correction method and the consequent verification of such a method, an experiment was conducted to acquire a data set suitable for testing atmospheric correction procedures under a variety of atmospheric conditions. Several procedures, including radiative transfer codes (RTCs) with simulated atmospheres, image-based procedures and dark-object subtraction (DOS), were evaluated by comparing surface reflectance factors derived from Landsat Thematic Mapper (TM) digital data with low-altitude, aircraft-based measurements for seven dates over a 1-year period. Acceptable results, approximately ± 0.02 reflectance (1 σ RMS), were achieved based on an RTC with appropriate simulated atmospheres. The DOS technique was the least accurate method and, in fact, produced greater error in estimations of near-IR reflectance than no correction at all. Two hybrid approaches, which combined the image-based nature of DOS with the precision of an RTC, provided sufficient accuracy and simplicity to warrant consideration for use on an operational basis. Though these results were probably site-specific (characterized by relatively low aerosol levels and low humidity), they illustrate the feasibility of simple atmospheric correction methods and the usefulness of a diverse data set for validation of such techniques.
Substantially revised and expanded, this new edition includes a
discussion of the radiative transfer equation, atmospheric sounding
techniques and interferometric radar, an expanded list of problems (with
solutions), and a discussion of the Global Positioning System (GPS).
This book forms the basis of an introductory course in remote sensing.
The main readership will be students and researchers in remote sensing,
geography, cartography, surveying, meteorology, earth sciences and
environmental sciences generally, as well as physicists, mathematicians
and engineers.
Incluye bibliografía e índice
The relative net photosynthetic activity of crop, grass and woodland areas was estimated from airborne eddy correlation carbon dioxide flux density measurements for various transects within a 100 km by 300 km agricultural region in southern Manitoba. Landsat Multispectral Scanner (MSS) data were used to estimate the density and vegetation class boundaries associated with these measurements. The airborne carbon dioxide flux measurements were made during good growing conditions, namely with soil moisture reserves (> 50 per cent field capacity), high radiation (950 W/m), cloudless skies and warm air temperature (> 25°C). The carbon dioxide flux ranged from (a) -20 to -35 kg CO2 ha h for the heavy crop canopies of the cereal and oilseed growing areas located on the clay and clay loam soils, (b) -12 to -25kg CO2 ha h for the mixed crop grassland and dense woodlands on loam to sandy loam soils and (c) -8 to - 15 kg CO2 ha h for the mixed grassland areas on sandy loam to sandy soils. Indices calculated from Landsat bands 5 and 6 (red and near-infrared) were used to quantify the distribution of green vegetation. A large area relative photosynthetic index (LARPS), which is a measure of the carbon dioxide flux per vegetative greenness unit, is proposed as a parameter which represents the effectiveness of chlorophyll's ability to absorb carbon dioxide.
Based on solar irradiance data published by Neckel and Labs (1984) and Iqbal (1983), the solar exoatmospheric irradiances for Thematic Mapper (TM) bands 1, 2, 3, and 4 have been calculated. Results vary by up to 1 percent from previous published values, which were based on the earlier data of Neckel and Labs. For TM bands 5 and 7, integrated solar exoatmospheric irradiances have also been recalculated using solar irradiance data published by Labs and Neckel (1968), Arvesen et al. (1969), and Iqbal (1983). These irradiances vary by up to 6 percent from previously published results, which were based on data published by Thekaekara (1972).
It is difficult to interpret multispectral Landsat earth resources data in areas of rugged and mountainous terrain because of the topographic effect on the sensor response. The objectives of this study were to examine and quantify the topographic effect on the sensor response from a uniform sand surface, to assess a simple theoretical incidence model for modeling the radiance from the surface, and to simulate Landsat sensor response due to the topographic effect. A field experiment was designed to collect data from a large range of slope angles and aspects at a range of solar elevations, using a hand-held radiometer. Analysis of these data showed that the magnitude of the topographic effect varied as a function of the solar elevation, the azimuthal orientation of the slope, and the slope inclination. The field measured variations in spectral response were found to have generally strong correlations with the theoretical model, and it was shown that the applicability of the Lambertian assumption varied within and between data sets. It is concluded that if slope angle, aspect, and solar zenith angle and azimuth are known, a technique incorporating a model to reduce the topographic effect prior to multispectral classification may be developed.
Spectral hemispherical-conical reflectances of a nadir looking sensor were taken throughout the day for a lodgepole pine and two grass canopies. Mathematical simulations of both spectral hemispherical-conical and bi-hemispherical reflectances were performed for two theoretical canopies of contrasting geometric structure. These results and comparisons with literature studies showed a great amount of variability of vegetation canopy reflectances as a function of solar zenith angle. Explanations for this variability are discussed and recommendations for further measurements are proposed.
The need for accurate radiometric data for the verification and use of scene radiation models is emphasized. The radiometric problems associated with reflectance and atmospheric correction field measurements and sensor calibration are reviewed. Estimates are made of the attainable accuracy in each case under favorable conditions. The loss in radiometric accuracy by resampling procedures in digital imagery processing is discussed. Copyright © 1985 By The Institute of Electrical and Electronics Engineers, Inc.
Simulation of the Satellite Signal in the Solar Spectrum (5S), Laboratoire d'Optique Atmosph6rique Combination of digital elevation models with SPOT-I HRV multispectral imagery for re-flectance factor mapping
- D Tanr
- C Deroo
- P Duhaut
- M Herman
- J J Morcrette
- J Perbos
- P Y Deschamps
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Geometric model simulations of conifer canopy reflectance
- Cavayas
Cavayas, F., and Teillet, P. M. (1988), Geometric model simulations of conifer canopy reflectance, in Proc. of the 3rd
International Colloquium on Spectral Signatures of Objects
in Remote Sensing, Les Arcs, France, 16-20 Dec., ESA
SP-247, pp. 183-189.
El tratamiento de im~igenes TM como ayuda para la actualizaci6n de mapas de usos del territorio, Communicaciones de la Segunda Reuni6n Nacional del Grupo de Trabajo en Teledetecci6n
- J M Moreira
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- F Otero
- J M Martinez
Moreira, J. M., Lobato, A., Ramos, A., Otero, F., and Martinez,
J. M. (1987), El tratamiento de im~igenes TM como ayuda
para la actualizaci6n de mapas de usos del territorio,
Communicaciones de la Segunda Reuni6n Nacional del
Grupo de Trabajo en Teledetecci6n, Valencia, Spain, 17-18 Dec., Asociaci6n Espafiola de Teledetecci6n, Madrid,
pp. 289-302.
Funcionalisme i Ecologia d'Algunes Comunitats Vegetals Barcelonines, Institut d'Estudis Catalans
- M A Cardona
Cardona, M. A. (1980), Funcionalisme i Ecologia d'Algunes
Comunitats Vegetals Barcelonines, Institut d'Estudis Catalans, Barcelona, pp. 27-120.
Influence de la topographie et de l'atmosphère sur les mesures radiometriques en region montagneuse-test d'un model d'inversion du signal sur des TM
- Proy
Proy, C., and Leprieur, C. (1985), Influence de la topographic
et de l'atmosphbre sur les mesures radiometriques en
region montagneuse-test d'un model d'inversion du signal sur des TM, in Proc. of the 3rd International Colloquium on Spectral Signatures of Objects in Remote Sensing,
Les Arcs, France, 16-20 Dec., ESA SP-247, Noordwijk,
pp. 191-197.
Remote sensing of the Earth: a synoptic view
- J R Sehott
Sehott, J. R. (1989), Remote sensing of the Earth: a synoptic view, Physics Today 89(Sep.):72-79.
Utilització d'un model de correcció radiomètrica sobre imatges de satèl·lit per a la millora de la cartografia automàtica de la vegetació
- Pons
Pons, X. (1990), Utilitzaci6 d'un model de correcci6 radiom~t-rica sobre imatges de sat~l'lit per a la millora de la
cartografia autom~ttica de la vegetaci6, Masters thesis,
Facultat de Ci~ncies, Universitat Autbnoma de Barcelona,
Barcelona, pp. 68-74.
Fundamentos de Teledetecci6n Espacial
- E Chuvieco
Chuvieco, E. (1990), Fundamentos de Teledetecci6n Espacial,
Rialp, Madrid, pp. 245-253.
- J R Eastman
Eastman, J. R. (1992), Idrisi. Technical Reference, Clark University, Worcester, pp. 16-17.
La serrade Collserola
- M Julivert
- J Soldevila
- H Duran
Julivert, M., Soldevila, J., and Duran, H. (1986), La serrade
Collserola, in Histbria Natural dels Pa~sos Catalans, Geologia I (P. Santanach, Ed.), Fundaci6 Enciclopbdia Catalana, Barcelona, pp. 176-185.
El pla especial d'ordenació i protecció del medi natural
- Sodupe i Roure
Sodupe i Roure, M. (1990), El pla especial d'ordenaci6 i
protecci6 del medi natural, Barcelona Metrbpolis Med.
14:96-100.
Funcionalisme i Ecologia d'Algunes Comunitats Vegetals Barcelonines
- Cardona
Atmospheric, Solar, and M.T.F. Corrections for ERTS Digital Imagery
- Chavez
El Paisaje Vegetal Barcelonés, Fac. de Filosofía y Letras
- de Bolòs
Idrisi Technical Reference
- Eastman
La serrade Collserola
- Julivert