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Publications (122)
Canopy nitrogen content (CNC) is a crucial variable for plant health, influencing photosynthesis and growth. An optimized, scalable approach for spatially explicit CNC quantification using Sentinel-2 (S2) data is presented, integrating PROSAIL-PRO simulations with Gaussian Process Regression (GPR) and an Active Learning technique, specifically the...
Introduction
Detecting and monitoring crop stress is crucial for ensuring sufficient and sustainable crop production. Recent advancements in unoccupied aerial vehicle (UAV) technology provide a promising approach to map key crop traits indicative of stress. While using single optical sensors mounted on UAVs could be sufficient to monitor crop statu...
Vegetation productivity is a critical indicator of global ecosystem health and is impacted by human activities and climate change. A wide range of optical sensing platforms, from ground-based to airborne and satellite, provide spatially continuous information on terrestrial vegetation status and functioning. As optical Earth observation (EO) data a...
Agriculture is the largest consumer of water worldwide, accounting for about 70% of the global freshwater withdrawals. Thus, crop water use efficiency and impacts of water stress on crop water consumption are the key concerns for agricultural water management. Present study investigates the variability of evapotranspiration (ET) and crop water use...
High spatial resolution land surface temperature (LST, <100 m) is crucial for agricultural water management, crop water stress monitoring, fire mapping, urban heat island study and volcano eruption detection. LST retrievals from the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) launched in June 2018, together with...
Quantum yield of fluorescence (φF) is key to interpret remote measurements of sun-induced fluorescence (SIF), and whether the SIF signal is governed by photochemical quenching (PQ) or non-photochemical quenching (NPQ). Disentangling PQ from NPQ allows using SIF estimates in various applications in aquatic optics. However, obtaining φF is challengin...
Different types of the Crop Water Stress Index (CWSI) have been useful for water stress monitoring and irrigation management in semi-arid regions, however little research exists on its effective application in humid regions. This study aims to assess the effectiveness of three CWSI models (CWSIe - empirical, CWSIt - theoretical, CWSIh - hybrid) for...
Canopy nitrogen content (CNC, kg/ha) provides crucial information for site-specific crop fertilization and the usability of Sentinel-2 (S2) satellite data for CNC monitoring at high fertilization levels in managed agricultural fields is still underexplored. Winter wheat samples were collected in France and Belgium in 2017 (n = 126) and 2018 (n = 18...
Tree restoration is an effective way to store atmospheric carbon and mitigate climate change. However, large-scale tree-cover expansion has long been known to increase evaporation, leading to reduced local water availability and streamflow. More recent studies suggest that increased precipitation, through enhanced atmospheric moisture recycling, ca...
Vegetation plays a vital role in the ecological functioning of terrestrial and coastal ecosystems. Remote sensing generally provides timely and accurate information to manage ecosystems sustainably and effectively. In this respect, thermal infrared (TIR, 3-14 µm) remote sensing data form a valuable data source for vegetation studies. The TIR data p...
Hyperspectral cameras onboard unmanned aerial vehicles (UAVs) have recently emerged for monitoring crop traits at the sub-field scale. Different physical, statistical, and hybrid methods for crop trait retrieval have been developed. However, spectra collected from UAVs can be confounded by various issues, including illumination variation throughout...
Hyperspectral cameras onboard unmanned aerial vehicles (UAVs) have recently emerged for monitoring crop traits at the sub-field scale. Different physical, statistical, and hybrid methods for crop trait retrieval have been developed. However, spectra collected from UAVs can be confounded by various issues, including illumination variation throughout...
Vegetation regulates the exchange of water, energy, and carbon fluxes between the land and the atmosphere. This regulation of surface fluxes differs with vegetation type and climate, but the effect of vegetation on surface fluxes is not well understood. A better knowledge of how and when vegetation influences surface fluxes could improve climate mo...
Abstract. Vegetation regulates the exchange of water, energy, and carbon fluxes between the land and the atmosphere. This regulation of surface fluxes differs with vegetation type and climate, but the effect of vegetation on surface fluxes is not well understood. A better knowledge of how and when vegetation influences surface fluxes could improve...
Look-up table (LUT)-based canopy reflectance models are considered robust methods to estimate vegetation attributes from remotely sensed data. However, the LUT inversion approach is sensitive to measurements and model uncertainties, which raise the ill-posed inverse problem. Therefore, regularization options are needed to mitigate this problem and...
Thermal infrared (TIR) multi-/hyperspectral and sun-induced fluorescence (SIF) approaches together with classic solar-reflective (visible, near-, and shortwave infrared reflectance (VNIR)/SWIR) hyperspectral remote sensing form the latest state-of-the-art techniques for the detection of crop water stress. Each of these three domains requires dedica...
Understanding the link between vegetation characteristics and tree transpiration is a critical need to facilitate satellite-based transpiration estimation. Many studies use the Normalized Difference Vegetation Index (NDVI), a proxy for tree biophysical characteristics, to estimate evapotranspiration. In this study, we investigated the link between...
There is a need for a better understanding of the link between vegetation characteristics and tree transpiration to facilitate satellite derived transpiration estimation. Many studies use the normalized difference vegetation index (NDVI), a proxy for tree biophysical characteristics, to estimate evapotranspiration. In this study we investigated the...
High-resolution airborne thermal infrared (TIR) together with sun-induced fluorescence (SIF) and hyperspectral optical images (visible, near- and shortwave infrared; VNIR/SWIR) were jointly acquired over an experimental site. The objective of this study was to evaluate the potential of these state-of-the-art remote sensing techniques for detecting...
Definition of a mandatory metadata set, aligned with current international efforts in the spectroscopy community.
The required and optional metadata of a spectral data set was investigated in depth in an OPTIMISE workshop titled “Ecosystem specific metadata definition” in 2017, hosted by the LIST institute in Luxembourg.
This paper describes the concept of the hyperspectral Earth-observing thermal infrared (TIR) satellite mission HiTeSEM (High-resolution Temperature and Spectral Emissivity Mapping). The scientific goal is to measure specific key variables from the biosphere, hydrosphere, pedosphere, and geosphere related to two global problems of significant societ...
Development of a Time Series Analysis Toolbox for ESA Earth Observation Products and integrate with ESA’s Mission exploitation platform to provide a selection of univariate and multivariate time-series analysis methods for Proba-V and Copernicus imagery.
Water stress is one of the most critical abiotic stressors limiting crop development. The main imaging and non-imaging remote sensing based techniques for the detection of plant stress (water stress and other types of stress) are thermography, visible (VIS), near-and shortwave infrared (NIR/SWIR) reflectance, and fluorescence. Just very recently, i...
Canopy chlorophyll content (CCC) is an essential ecophysiological variable for photosynthetic functioning. Remote sensing of CCC is vital for a wide range of ecological and agricultural applications. The objectives of this study were to explore simple and robust algorithms for spectral assessment of CCC. Hyperspectral datasets for six vegetation ty...
Canopy and aerodynamic conductances (gC and gA) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their representation is crucial for predicting transpiration
(λET) and evaporation
(λEE) flux components of the terrestrial latent heat
flux (λE), which has important...
In 2015, two major conferences focused on hyperspectral remote sensing and imaging spectroscopy were held in Luxembourg and Tokyo, respectively. They are namely the 9th EARSeL SIG Imaging Spectroscopy workshop and the 7th Workshop on Hyperspectral Image and Signal Processing. As a follow up to these conferences, the current special issue of JSTARS...
The “High resolution temperature and spectral emissivity mapping” (HiTeSEM) initiative aims at developing a conceptual instrument design for a hyperspectral thermal satellite to find answers for the most pressing research and data requirements within the scope of Food Security and Human Health. The satellite is proposed to consist of two long-wave...
Canopy and aerodynamic conductances (gC and gA) are some of the key land surface variables determining the land surface response of climate models. Their representation is crucial for predicting transpiration (λET) and evaporation (λEE), which has important implications for global climate change and water resource management. Here, we present a nov...
The RAdiative transfer Model Intercomparison (RAMI) activity focuses on the benchmarking of canopy radiative transfer (RT) models. For the current fourth phase of RAMI, six highly realistic virtual plant environments were constructed on the basis of intensive field data collected from (both deciduous and coniferous) forest stands as well as test si...
The RAdiative transfer Model Intercomparison (RAMI) activity focuses on the benchmarking of canopy radiative transfer (RT) models. For the current fourth phase of RAMI, six highly realistic virtual plant environments were constructed on the basis of intensive field data collected from (both deciduous and coniferous) forest stands as well as test si...
HiTeSEM (High-resolution Temperature and Spectral Emissivity Mapping) is a preparatory study, funded by the German Aerospace Center (DLR) that aims preparing the floor for a future spaceborn hyperspectral thermal mission. Thermal remote sensing is poised to become a major source of information on land surface processes. HiTeSEM aims at closing the...
HiTeSEM (High-resolution Temperature and Spectral Emissivity Mapping) is a preparatory study, funded by the German Aerospace Center (DLR) that aims preparing the floor for a future spaceborn hyperspectral thermal mission. Thermal remote sensing is poised to become a major source of information on land surface processes. HiTeSEM aims at closing the...
HiTeSEM (High-resolution Temperature and Spectral Emissivity Mapping) is a preparatory study, funded by the German Aerospace Center (DLR) that aims at preparing the floor for a future spaceborne hyperspectral thermal mission. Up to now this spectral region in Earth observation is mainly used to measure surface temperature. Nevertheless, the spectra...
Although shrublands, savannas and grasslands account for 37% of the world's terrestrial area, not many studies have analysed the role of these ecosystems in the global carbon cycle at a regional scale. The MODIS Gross Primary Production (GPP) product is used here to help bridge this gap. In this study, the agreement between the MODIS GPP product (G...
Fine scale maps of vegetation biophysical variables are useful status indicators for monitoring and managing national parks and endangered habitats. Here, we assess in a comparative way four different retrieval methods for estimating leaf area index (LAI) in grassland: two radiative transfer model (RTM) inversion methods (one based on look-up-table...
Complex crop growth models (CGM) require a large number of input parameters, which can cause large errors if they are uncertain. Furthermore, they often lack spatial information. The coupling of a CGM with a radiative transfer model offers the possibility to assimilate remote sensing data while taking into account uncertainties in input parameters....
There is growing concern that increasing eutrophication causes degradation of coastal ecosystems. Studies in terrestrial ecosystems have shown that increasing the concentration of nitrogen in soils contributes to the acidification process, which leads to leaching of base cations. To test the effects of eutrophication on the availability of base cat...
Spectral reflectance can be used to assess large-scale performances of plants in the field based on plant nutrient balance as well as composition of defence compounds. However, plant chemical composition is known to vary with season - due to its phenology - and it may even depend on the succession stage of its habitat. Here we investigate (i) how s...
Quantification of chlorophyll content provides useful insight into the physiological performance of plants. Several leaf chlorophyll estimation techniques, using hyperspectral instruments, are available. However, to our knowledge, a non-destructive bark chlorophyll estimation technique is not available. We set out to assess Boswellia papyrifera tre...
Determining the foliar N:P ratio provides a tool for understanding nutrient limitation on plant production and consequently for the feeding patterns of herbivores. In order to understand the nutrient limitation at landscape scale, remote sensing techniques offer that opportunity. The objective of this study is to investigate the utility of field sp...
Grass nitrogen (N) and phosphorus (P) concentrations are direct indicators of rangeland quality and provide imperative information for sound management of wildlife and livestock. It is challenging to estimate grass N and P concentrations using remote sensing in the savanna ecosystems. These areas are diverse and heterogeneous in soil and plant mois...
The radiation transfer model intercomparison (RAMI) activity aims at
assessing the reliability of physics-based radiative transfer (RT)
models under controlled experimental conditions. RAMI focuses on
computer simulation models that mimic the interactions of radiation with
plant canopies. These models are increasingly used in the development of
sat...
Plant toxic biochemicals play an important role in defense against natural enemies and often are toxic to humans and livestock. Hyperspectral reflectance is an established method for primary chemical detection and could be further used to determine plant toxicity in the field. In order to make a first step for pyrrolizidine alkaloids detection (tox...
Some biochemical compounds are closely related with the quality of tea (Camellia sinensis (L.)). In this study, the concentration of these compounds including total tea polyphenols, free amino acids and soluble sugars were estimated using reflectance spectroscopy at three different levels: powder, leaf and canopy, with partial least squares regress...
Hyperspectral remote sensing enables the large-scale mapping of canopy biochemical properties. This study explored the possibility of retrieving the concentration of nitrogen, phosphorus, potassium, calcium, magnesium, and sodium from mangroves in the Berau Delta, Indonesia. The objectives of the study were to (1) assess the accuracy of foliar chem...
Biogas production from energy crops by anaerobic digestion is becoming increasingly important. The amount of biogas that can be produced per unit of biomass is referred to as the biomethane potential (BMP). For energy crops, the BMP varies among varieties and with crop state during the vegetation period. Traditional ways of analytical BMP determina...
Methods are presented testing the suitability of PROSAIL radiative transfer model for analysing HyMap imaging spectroscopy data over grassland. The presented methods include forward modelling and cross-checks of 2D correlation plots. In the forward modelling, it is taken into account that the in situ data are not error free. To increase the predict...
A new instrument has been setup at the Centre de Recherche Public-Gabriel Lippmann to measure spectral emissivity values of typical earth surface samples in the 8 to 12 mu m range at a spectral resolution of up to 0.25 cm(-1). The instrument is based on a Hyper-Cam-LW built by Telops with a modified fore-optic for vertical measurements at ground le...
Genetic variation between various plant species determines differences in their physio-chemical makeup and ultimately in their hyperspectral emissivity signatures. The hyperspectral emissivity signatures, on the one hand, account for the subtle physio-chemical changes in the vegetation, but on the other hand, highlight the problem of high dimension...
Recent studies revealed that plant–soil biotic interactions may cause changes in above‐ground plant chemistry. It would be a new step in below‐ground–above‐ground interaction research if such above‐ground chemistry changes could be efficiently detected. Here we test how hyperspectral reflectance may be used to study such plant–soil biotic interacti...
Abstract: This study aimed to investigate the potential of MERIS in estimating the quantity and quality of a grassland using various vegetation indices (NDVI, SAVI, TSAVI, REIP, MTCI and band depth analysis parameters) at a regional scale. Green biomass was best predicted by NBDI (normalised band depth index) and yielded a calibration R 2 of 0.73 a...
The regional mapping of grass nutrients is of interest in the sustainable planning and management of livestock and wildlife grazing. The objective of this study was to estimate and map foliar and canopy nitrogen (N) at a regional scale using a recent high resolution spaceborne multispectral sensor (i.e. RapidEye) in the Kruger National Park (KNP) a...
Leaf water content determines plant health, vitality, photosynthetic efficiency and is an important indicator of drought assessment. The retrieval of leaf water content from the visible to shortwave infrared spectra is well known. Here for the first time, we estimated leaf water content from the mid to thermal infrared (2.5-14.0μm) spectra, based o...
Tea (Camellia Sinensis (L.)) is an important economic crop and the market price of tea depends largely on its quality. This research
aims to explore the potential of hyperspectral remote sensing on predicting the concentration of biochemical components, namely
total tea polyphenols, as indicators of tea quality at canopy scale. Experiments were car...
The objective of this study was to estimate leaf water content based on continuous wavelet analysis from the far infrared (2.5 - 14.0 mu m) spectra. The entire dataset comprised of 394 far infrared spectra which were divided into calibration (262 spectra) and validation (132 spectra) subsets. The far infrared (2.5 - 14.0 mu m) spectra were first tr...
Tittle: Identifying plant species using MIR and TIR (2 - 14 µm)
emissivity spectra Identification plant species using remote sensing is
generally limited by the similarity of their reflectance spectra in the
visible, NIR and SWIR domains. Laboratory measured emissivity spectra in
the mid to thermal infrared (MIR-TIR; 2 µm - 14 µm) shows
significant...
Plant species discrimination using remote sensing is generally limited by the similarity of their reflectance spectra in the visible, NIR and SWIR domains. Laboratory measured emissivity spectra in the mid infrared (MIR; 2.5 mu m-6 mu m) and the thermal infrared (TIR; 8 mu m-14 mu m) domain of different plant species, however, reveal significant di...
The structure of vegetation canopies largely controls the functioning of ecosystems. There is a substantial demand for spatial information on canopy structure. This paper examines the retrieval of an important forest structure property, leaf area index (LAI) from spectro-directional satellite observations (PROBA/CHRIS) using a forest reflectance mo...
Coastal ecosystems, such as mangroves, pose a challenge for chlorophyll
(CHL) and nitrogen (N) estimation using Hyperspectral. Mangroves have
unique characteristics such as high humidity, wet soils (mud), water
logged, and roots on the mangrove floors that provide strong influence
to mangrove canopy spectra. This study aims to find optimum
Hyperspe...
Statistical and physical models have seldom been compared in studying grasslands. In this paper, both modeling approaches are investigated for mapping leaf area index (LAI) in a Mediterranean grassland (Majella National Park, Italy) using HyMap airborne hyperspectral images. We compared inversion of the PROSAIL radiative transfer model with narrow...
We used GPS satellite tracking data and field measurements of vegetation to investigate the effect of food resources, distance to roosts, and the location of refuges on the distribution of Barnacle Geese Branta leucopsis in the northern part of The Netherlands. To deal with spatial dependence among the data, a spatial lag model was used. A signific...
Vegetation indices (VI) combine mathematically a few selected spectral bands to minimize undesired effects of soil background, illumination conditions and atmospheric perturbations. In this way, the relation to vegetation biophysical variables is enhanced. Albeit numerous experiments found close relationships between vegetation indices and several...
Information about the distribution of grass foliar nitrogen (N) and phosphorus (P) is important for understanding rangeland vitality and for facilitating the effective management of wildlife and livestock. Water absorption effects in the near-infrared (NIR) and shortwave-infrared (SWIR) regions pose a challenge for nutrient estimation using remote...
Information about the distribution of grass nitrogen (N) concentration is crucial in understanding rangeland vitality and facilitates effective management of wildlife and livestock. A challenge in estimating grass N concentration using remote sensing in savannah ecosystems is that these areas are characterised by heterogeneity in edaphic, topograph...
Greenhouse gas inventories and emission reduction program requires scientifically robust methods to quantify forest carbon storage in forest. Remote sensing techniques are accurate and low-cost alternatives to the field based assessment. High spatial resolution remotely sensed imagery provides viable sources and opportunities for forest inventory a...
The potential of reflectance spectroscopy to estimate the concentration of biochemical compounds related to tea (Camellia sinensis (L.)) quality (total tea polyphenols and free amino acids) is demonstrated. Partial least squares regression (PLSR) was performed to establish the relationship
between reflectance and biochemicals for leaf powders as we...
We analysed stability and predictive capabilities of known nitrogen absorption features between plant material prepared for NIRS (dried) and RS (fresh) studies. Grass spectra were taken of the plant canopy, and again after the grass sample was dried and ground. Models were derived using stepwise multiple linear regression (sMLR). Regression values...
The research evaluated the information content of spectral reflectance (laboratory and airborne data) for the estimation of needle chlorophyll (CAB) and nitrogen (CN) concentration in Norway spruce (Picea abies L. Karst.) needles. To identify reliable predictive models different types of spectral transformations were systematically compared regardi...
Saleem Ullah1 , Si Yali1 , Martin Schlerf1 Forage quantity is an important factor influencing feeding pattern and distribution of wildlife. The main objective of this study was to evaluate the predictive performance of vegetation indices and band depth analysis parameters for estimation of green biomass using MERIS data. Green biomass was best pred...
Accurate quantitative estimation of vegetation biochemical characteristics is necessary for a large variety of agricultural and ecological applications. The advent of hyperspectral remote sensing has offered possibilities for measuring specific vegetation variables that were difficult to measure using conventional multi-spectral sensors. In this st...
The canopy chlorophyll content is one of the prime parameters that characterize the grassland status and hence an important information for grassland's management. Hyperspectral remote sensing with narrow and continuous spectral bands is potentially more sensitive to specific vegetation variables such as the amount of greenness (LAI) and canopy chl...
Lizards are an "excellent group of organisms" to examine the habitat and microhabitat use mainly because their ecology and physiology is well studied. Due to their behavioral body temperature regulation, the thermal environment is especially linked with their habitat use. In this study, for mapping and understanding lizard's distribution at microha...
In this study, we monitored the quality of fresh tea leaves as raw materials of tea products by hyperspectral technology, as a way to explore the potential of hyperspectral remote sensing to detect the taste-related chemical components with low concentration in living plants. At leaf scale, empirical models have been established to find the relatio...
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...
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 measureme...
The study shows that leaf area index (LAI) and canopy chlorophyll content 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 chlorophyll content. We teste...
Studies that compare modelled reflectances with satellite-measured reflectances for different wavelengths and view angles are still rare. We compared model outputs from three different canopy reflectance models (SLC, FRT and INFORM) with satellite measured reflectances (Chris/PROBA). Comparison of the simulated directional reflectances reveals gene...
The potential of canopy reflectance modelling to retrieve simultaneously several structural variables in managed Norway spruce stands was investigated using the “Invertible Forest Reflectance Model”, INFORM. INFORM is an innovative extension of the FLIM model, with crown transparency, infinite crown reflectance and understory reflectance simulated...
Classifications of coniferous forest stands regarding tree species and age classes were performed using hyperspectral remote sensing data (HyMap) of a forest in western Germany. Spectral angle mapper (SAM) and maximum likelihood (ML) classifications were used to classify the images. Classification was performed using (i) spectral information alone,...