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International Journal of Applied Earth Observation and Geoinformation 04/2007; 9:224-224. · 1.74 Impact Factor
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ABSTRACT: The study shows that leaf area index (LAI), leaf chlorophyll content (LCC) and canopy chlorophyll content (CCC) can be mapped in a heterogeneous Mediterranean grassland from canopy spectral reflectance measurements. Canopy spectral measurements were made in the field using a GER 3700 spectroradiometer, along with concomitant in situ measurements of LAI and LCC. We tested the utility of univariate techniques involving narrow band vegetation indices and the red edge inflection point, as well as multivariate calibration techniques, including stepwise multiple linear regression and partial least squares regression. Among the various investigated models, CCC was estimated with the highest accuracy (, ). All methods failed to estimate LCC (), while LAI was estimated with intermediate accuracy ( values ranged from 0.49 to 0.69). Compared with narrow band indices and red edge inflection point, stepwise multiple linear regression generally improved the estimation of LAI. The estimations were further improved when partial least squares regression was used. When a subset of wavelengths was analyzed, it was found that partial least squares regression had reduced the error in the retrieved parameters. The results of the study highlight the significance of multivariate techniques, such as partial least squares regression, rather than univariate methods such as vegetation indices in estimating heterogeneous grass canopy characteristics.
ISPRS Journal of Photogrammetry and Remote Sensing.
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ABSTRACT: The main objective was to determine whether partial least squares (PLS) regression improves grass/herb biomass estimation when compared with hyperspectral indices, that is normalised difference vegetation index (NDVI) and red-edge position (REP). To achieve this objective, fresh green grass/herb biomass and airborne images (HyMap) were collected in the Majella National Park, Italy in the summer of 2005. The predictive performances of hyperspectral indices and PLS regression models were then determined and compared using calibration (n = 30) and test (n = 12) data sets. The regression model derived from NDVI computed from bands at 740 and 771 nm produced a lower standard error of prediction (SEP = 264 g m−2) on the test data compared with the standard NDVI involving bands at 665 and 801 nm (SEP = 331 g m−2), but comparable results with REPs determined by various methods (SEP = 261 to 295 g m−2). PLS regression models based on original, derivative and continuum-removed spectra produced lower prediction errors (SEP = 149 to 256 g m−2) compared with NDVI and REP models. The lowest prediction error (SEP = 149 g m−2, 19% of mean) was obtained with PLS regression involving continuum-removed bands. In conclusion, PLS regression based on airborne hyperspectral imagery provides a better alternative to univariate regression involving hyperspectral indices for grass/herb biomass estimation in the Majella National Park.
International Journal of Applied Earth Observation and Geoinformation.
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ABSTRACT: Radiative transfer models have seldom been applied for studying heterogeneous grassland canopies. Here, the potential of radiative transfer modeling to predict LAI and leaf and canopy chlorophyll contents in a heterogeneous Mediterranean grassland is investigated. The widely used PROSAIL model was inverted with canopy spectral reflectance measurements by means of a look-up table (LUT). Canopy spectral measurements were acquired in the field using a GER 3700 spectroradiometer, along with simultaneous in situ measurements of LAI and leaf chlorophyll content. We tested the impact of using multiple solutions, stratification (according to species richness), and spectral subsetting on parameter retrieval. To assess the performance of the model inversion, the normalized RMSE and R2 between independent in situ measurements and estimated parameters were used. Of the three investigated plant characteristics, canopy chlorophyll content was estimated with the highest accuracy (R2 = 0.70, NRMSE = 0.18). Leaf chlorophyll content, on the other hand, could not be estimated with acceptable accuracy, while LAI was estimated with intermediate accuracy (R2 = 0.59, NRMSE = 0.18). When only sample plots with up to two species were considered (n = 107), the estimation accuracy for all investigated variables (LAI, canopy chlorophyll content and leaf chlorophyll content) increased (NRMSE = 0.14, 0.16, 0.19, respectively). This shows the limits of the PROSAIL radiative transfer model in the case of very heterogeneous conditions. We also found that a carefully selected spectral subset contains sufficient information for a successful model inversion. Our results confirm the potential of model inversion for estimating vegetation biophysical parameters at the canopy scale in (moderately) heterogeneous grasslands using hyperspectral measurements.
Remote Sensing of Environment.
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ABSTRACT: Amongst many ongoing initiatives to preserve biodiversity, the Millennium Ecosystem Assessment again shows the importance to slow down the loss of biological diversity. However, there is still a gap in the overview of global patterns of species distributions. This paper reviews how remote sensing has been used to assess terrestrial faunal diversity, with emphasis on proxies and methodologies, while exploring prospective challenges for the conservation and sustainable use of biodiversity. We grouped and discussed papers dealing with the faunal taxa mammals, birds, reptiles, amphibians, and invertebrates into five classes of surrogates of animal diversity: (1) habitat suitability, (2) photosynthetic productivity, (3) multi-temporal patterns, (4) structural properties of habitat, and (5) forage quality. It is concluded that the most promising approach for the assessment, monitoring, prediction, and conservation of faunal diversity appears to be the synergy of remote sensing products and auxiliary data with ecological biodiversity models, and a subsequent validation of the results using traditional observation techniques.
International Journal of Applied Earth Observation and Geoinformation.
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ABSTRACT: Within the framework of ESA's Earth Observation Program, the Medium Resolution Imaging Spectrometer (MERIS) is being developed as one of the payload components of the ENVISAT-1. Although MERIS is a fully programmable imaging spectrometer, a standard 15 channel band set will be transmitted for each 300 m pixel (over land) covering the visible and near-infrared wavelength range. Since MERIS is a multidisciplinary sensor providing data that can be input into ecosystem models at various scales, we studied MERIS' performance for mineral mapping relative to the scale of observation using simulated data sets degraded to various resolutions in the range of 10 m to 300 m. Algorithms to simulate MERIS data using airborne imaging spectrometer data sets are presented using data from HyMAP acquired on 2 June 1999 over the Tabernas area of southern Spain (Almeria province). A spectral library of mineral spectra was examined to identify potential mappable mineral suites at the MERIS spectral resolution and band setting. A total of 74 (out of 160) minerals have absorption features in the MERIS wavelengths; most of them represent ore (or related) minerals not likely to be “seen” by the sensor given it's FOV. The study thus focused on goethite and hematite mapping. The HyMAP data was used to simulate MERIS data at various resolutions. Mineral maps were produced using the cross correlogram spectral mapping (CCSM) approach. The results were evaluated against the mineral maps produced using the original HyMAP data using the (1) mis-classification, (2) RMS value of the CCSM and (3) the optimal sampling size derived from local variance estimates. (1) and (2) show that accuracy decreases rapidly with larger FOV, possibly due to increased spectral mixing. The optimal sampling sizes calculated for hematite and goethite reflect this. Values were to be 20–30 m for goethite and <10 m for hematite.RésuméDans le cadre du Programme d'Observation de la Terre (ESA), le Spectromètre Imageur de Résolution Moyenne (MERIS) est développé comme l'un des composants de la charge utile de ENVISAT-1. Bien que MERIS soit un spectromètre imageur entièrement programmable, une série standard de 15 bandes de canaux sera transmise pour chaque pixel de 300m (au sol) couvrant l'étendue du spectre visible et du proche infra rouge. Du fait que MERIS est un capteur multidisciplinaire qui fournit des données pouvant être entrées dans des modèles d'écosystème à différentes échelles, nous avons étudié les performances de MERIS pour la cartographie minérale relative à l'échelle d'observation utilisant des séries de données de simulation dégradées à différentes résolutions dans une fourchette de 10m à 300m. Des algorithmes pour simuler les données MERIS utilisant des séries de données de spectromètre imageur aéroporté sont présentés à l'aide de données de HyMAP acquises le 2 Juin 1999 au dessus de la zone de Tabernas dans le Sud de l'Espagne (Province d'Almeria). Une librairie spectrale de spectres minéraux a été examinée pour identifier le potentiel des sites de minéraux pouvant être cartographiés à la résolution spectrale et dans les bandes de MERIS. Un total de 74 (sur 160) minéraux a des caractéristiques d'absorption dans les bandes de MERIS ; la plupart représentent des métaux (ou des minéraux s'en rapprochant), qui normalement ne sont pas “visibles” par le capteur étant donné son champ de vision (FOV). L'étude s'est concentrée sur la cartographie de goéthite et hématite. Les données HyMAP ont été utilisées pour simuler les données MERIS à différents résolutions. Des cartes de minéraux ont été produites en utilisant l'approche cartographique de corrélogramme spectral croisé (CCSM). Les résultats ont été évalués par comparaison avec les cartes de minéraux produites à partirdes données originales HyMAP en utilisant (1) l'erreur de classification, (2) la valeur moyenne quadratique du CCSM et (3) la dimension optimale de l'échantillon dérivée de variances locales. (1) et (2) montrent que la précision décroît rapidement avec un plus grand champ de vision (FOV), probablement dû à un accroissement du mixage spectral. Les dimensions optimales des échantillons calculées pour l'hématite et la goéthite traduisent ceci ; les valeurs devraient être de 20 – 30 m pour la goéthite et < 10m pour l'hématite.ResumenDentro del marco del Programa de observación terrestre (Earth Observation Program) de la ESA (agencia espacial europea), se está desarrollando el espectrómetro de imagen de resolución media (Medium Resolution Imaging Spectrometer) (MERIS) como uno de los componentes de carga útil del ENVISAT-1. Aunque MERIS es un espectrómetro para obtención de imágenes totalmente programable, se transmitirá una franja estándar fija de 15 canales por cada cuadricula (pixel) de 300 m (sobre la tierra) abarcando la gama de longitudes de onda del visible y el infrarrojo próximo. Dado que MERIS es un sensor multidisciplinar que proporciona datos que se pueden introducir en modelos de ecosistemas a varias escalas, hemos estudiado la capacidad de MERIS para el mapeo de minerales con respecto a la escala de observación, empleando para ello grupos de datos simulados degradados a varias resoluciones en el intervalo de 10 a 300 m. Se presentan algoritmos para simular los datos de MERIS empleando series de datos del espectrómetro de obtención de imágenes aerotransportadas empleando datos del HyMAP obtenidos el 2 de junio de 1999 en la zona de Taberna, en la provincia de Almería. Se examinó una biblioteca de espectros de minerales para identificar las posibles series de minerales representables sobre un mapa con la resolución de espectros y el ajuste de banda de MERIS. Un total de 74 (de 160) minerales tienen características de absorción en las longitudes de onda de MERIS; la mayor parte de ellos representan minerales de mena (o afines) que no es probable que sean “vistos” por el sensor dada su FOV. El estudio pues, se centró en el mapeo de goetita y hematites. Los datos de HyMAP se utilizaron para simular los datos de MERIS a distintas resoluciones. Los mapas de minerales se obtuvieron mediante el método de mapeo espectral de correlación cruzada (CCSM). Los resultados fueron evaluados frente a los mapas de minerales producidos mediante los datos originales de HyMAP empleando la (1) clasificación errónea, (2) el valor de RMS del CCSM y (3) el tamaño de muestreo óptimo obtenido por cálculos de la varianza local. (1) y (2) demuestran que la exactitud disminuye rápidamente a medida que aumenta el FOV, posiblemente debido a que aumenta la mezcla de espectros. Los tamaños de muestreo óptimos calculados para hematites y goetita son un reflejo de esto. Los valores encontrados fueron de 20–30 m para goetita y <10 m para hematites.
International Journal of Applied Earth Observation and Geoinformation.
