Carbon use efficiency variability from MODIS data

[EN] Carbon use efficiency (CUE) describes how efficiently plants incorporate the carbon fixed during photosynthesis into biomass gain and can be calculated as the ratio between net primary production (NPP) and gross primary production (GPP). In this work, annual CUE has been obtained from annual GPP and NPP MODIS products for the peninsular Spain study area throughout eight years. CUE is spatially and temporally analyzed in terms of the vegetation type and annual precipitation and annual average air temperature. Results show that dense vegetation areas with moderate to high levels of precipitation present lower CUE values, whereas more arid areas present the highest CUE values. However, th…

Assessment of MODIS imagery to track light-use efficiency in a water-limited Mediterranean pine forest

Abstract Daily values of gross primary production ( GPP ) derived from an eddy-covariance flux tower have been used to analyze the information content of the MODIS Photochemical Reflectance Index ( PRI ) on the light-use efficiency ( e ). The study has been conducted in a Mediterranean Pinus pinaster forest showing summer water stress. Advanced processing techniques have been used to analyze the effect of various external factors on e and PRI temporal variations. The intra-annual correlation between these two variables has been found to be mostly attributable to concurrent variations in sun and view zenith angles. The PRI has been normalized from these angular effects ( NPRI ), and its abil…

Vegetation dynamics from NDVI time series analysis using the wavelet transform

A multi-resolution analysis (MRA) based on the wavelet transform (WT) has been implemented to study NDVI time series. These series, which are non-stationary and present short-term, seasonal and long-term variations, can be decomposed using this MRA as a sum of series associated with different temporal scales. The main focus of the paper is to check the potential of this MRA to capture and describe both intra- and inter-annual changes in the data, i.e., to discuss the ability of the proposed procedure to monitor vegetation dynamics at regional scale. Our approach concentrates on what wavelet analysis can tell us about a NDVI time series. On the one hand, the intra-annual series, linked to th…

Use of NOAA-AVHRR NDVI data for environmental monitoring and crop forecasting in the Sahel. Preliminary results

Abstract Several studies have shown that the NDVI calculated from NOAA-AVHRR data is related to annual rainfall and primary productivity in Sahelian areas. Such correlations, however, are affected by several environmental factors and have been tested only with data accumulated during rainy seasons, which is not ideal for the prediction of crop yield. In the present study a methodology of NOAA AVHRR data processing is presented which utilizes NDVI computed only in the first part of some rainy seasons and statistically takes into account the geographical variability in land resources and atmospheric conditions. From the first results of the application of the methodology in Niger, its potenti…

Intercomparison of instruments for measuring leaf area index over rice

Leaf area index (LAI) is a key biophysical parameter used to determine foliage cover and crop growth in environmental studies in order to assess crop yield. LAI estimates can be classified as direct or indirect methods. Direct methods are destructive, time consuming, and difficult to apply over large fields. Indirect methods are non-destructive and cost-effective due to its portability, accuracy and repeatability. In this study, we compare indirect LAI estimates acquired from two classical instruments such as LAI-2000 and digital cameras for hemispherical photography, with LAI estimates acquired with a smart app (PocketLAI) installed on a mobile smartphone. In this work it is shown that LAI…

Capability assessment of the SEVIRI/MSG GPP product for the detection of areas affected by water stress

[ES] Se presenta el nuevo producto de producción primaria bruta (GPP) de EUMETSAT derivado a partir de datos del satélite geoestacionario SEVIRI/MSG (MGPP LSA-411) y se evalúa su potencial para detectar zonas afectadas por estrés hídrico (hot spots). El producto GPP se basa en la aproximación de Monteith, que modela la GPP de la vegetación como el producto de la radiación fotosintéticamente activa (PAR) incidente, la fracción de PAR absorbida (fAPAR) y un factor de eficiencia de uso de la radiación (ε). El potencial del producto MGPP para detectar hot spots se evalúa, utilizando un periodo corto de tres años, a escala local y regional, comparando con datos in situ derivados de medidas en to…

Relation between reflectance of rice crop and indices of pollution by heavy metals in soils of albufera natural park (Valencia, Spain)

13 páginas, 3 figuras, 4 tablas, 1 foto.

Generation of global vegetation products from EUMETSAT AVHRR/METOP satellites

We describe the methodology applied for the retrieval of global LAI, FAPAR and FVC from Advanced Very High Resolution Radiometer (AVHRR) onboard the Meteorological-Operational (MetOp) polar orbiting satellites also known as EUMETSAT Polar System (EPS). A novel approach has been developed for the joint retrieval of three parameters (LAI, FVC, and FAPAR) instead of training one model per parameter. The method relies on multi-output Gaussian Processes Regression (GPR) trained over PROSAIL EPS simulations. A sensitivity analysis is performed to assess several sources of uncertainties in retrievals and maximize the positive impact of modeling the noise in training simulations. We describe the ma…

Tracking seasonal drought effects on ecosystem light use efficiency in a mediterranean forest using climatic and remote sensing data

Daily values of light use efficiency (LUE) of a Mediterranean forest throughout five years have been analyzed in terms of different spectral indices obtained from MODIS products and which are informative on the water stress conditions. Although correlations between LUE and the different indices are rather high, the inter-annual variation of LUE due to the summer water stress is not well identified in most of them. In particular, the PRI (photochemical reflectance index) inter-annual variation has been found to be mostly attributable to concurrent variations in sun and view zenith angles. For the study area and at MODIS spatial resolution, the different indices are informative on changes in …

A Critical Comparison of Remote Sensing Leaf Area Index Estimates over Rice-Cultivated Areas: From Sentinel-2 and Landsat-7/8 to MODIS, GEOV1 and EUMETSAT Polar System

Leaf area index (LAI) is a key biophysical variable fundamental in natural vegetation and agricultural land monitoring and modelling studies. This paper is aimed at comparing, validating and discussing different LAI satellite products from operational services and customized solution based on innovative Earth Observation (EO) data such as Landsat-7/8 and Sentinel-2A. The comparison was performed to assess overall quality of LAI estimates for rice, as a fundamental input of different scale (regional to local) operational crop monitoring systems such as the ones developed during the "An Earth obseRvation Model based RicE information Service" (ERMES) project. We adopted a multiscale approach f…

Solar angle and sky light effects on ground reflectance measurements in a citrus canopy

Abstract Ground radiometry was used to gather spectral data from different targets of a citrus canopy, in order to analyze the effect of solar zenith angle and proportion of diffuse radiation on spectral reflectance. Results have shown that the variation in solar angle causes significant changes in nadirsensed reflectance from vegetation, which exhibits a marked diurnal pattern with a minimum slightly shifted from the solar noon. This fact is more noticeable in the near-infrared and middle-infrared regions of the spectrum. Furthermore, the visible part of the spectrum has resulted in being highly influenced by the diffuse radiation incident on the canopy, which has been quantified by two di…

Simulation of citrus orchard reflectance by means of a geometrical canopy model

Computer simulation of the reflectance for citrus crops, by using a geometrical canopy model, has been carried out to analyse and interpret the reflectance values from Landsat-5 Thematic Mapper (TM...

A simple geometrical model for analysing the spectral response of a citrus canopy using satellite images

Abstract 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 b…

A comparison of direct and indirect methods for measuring leaf and surface areas of individual bushes

Indirect estimates of leaf area from measurements with three commercially available instruments (DEMON, LAI-2000 and Sunfleck Ceptometer) were compared with directly measured areas of individual Retama sphaerocarpa bushes. The three indirect methods gave good estimates of the total surface area of individual bushes. For the DEMON, the method of log-linear averaging of transmitted radiation gave estimates closer to directly measured surface area than the method of averaging transmission linearly. For the LAI-2000, estimated surface area index multiplied by canopy projected area gave the best agreement with directly measured values. For measurements with the Sunfleck Ceptometer, values of sur…

Development of an earth observation processing chain for crop bio-physical parameters at local scale

This paper proposes a full Earth observation processing chaing for biophysical parameter estimation at local scales. In particular, we focus on the Leaf Area Index (LAI) as an essential climate variable required for the monitoring and modeling of land surfaces at local scale. The main goal of this study is tied to the use of optical satellite images to retrieve Earth Observation (EO) biophysical parameters able to describe the spatio-temporal changes in agro-ecosystems at local scale. The objective of this work is two-fold: (i) to set up and update the EO products processing chain at high resolution (local) scale; and (ii) derive multitemporal LAI maps at 30 m resolution to be fed into a cr…

A global Canopy Water Content product from AVHRR/Metop

Abstract Spatially and temporally explicit canopy water content (CWC) data are important for monitoring vegetation status, and constitute essential information for studying ecosystem-climate interactions. Despite many efforts there is currently no operational CWC product available to users. In the context of the Satellite Application Facility for Land Surface Analysis (LSA-SAF), we have developed an algorithm to produce a global dataset of CWC based on data from the Advanced Very High Resolution Radiometer (AVHRR) sensor on board Meteorological–Operational (MetOp) satellites forming the EUMETSAT Polar System (EPS). CWC reflects the water conditions at the leaf level and information related …

Multitemporal Monitoring of Plant Area Index in the Valencia Rice District with PocketLAI

Leaf area index (LAI) is a key biophysical parameter used to determine foliage cover and crop growth in environmental studies in order to assess crop yield. Frequently, plant canopy analyzers (LAI-2000) and digital cameras for hemispherical photography (DHP) are used for indirect effective plant area index (PAI(eff)) estimates. Nevertheless, these instruments are expensive and have the disadvantages of low portability and maintenance. Recently, a smartphone app called PocketLAI was presented and tested for acquiring PAI(eff) measurements. It was used during an entire rice season for indirect PAI(eff) estimations and for deriving reference high-resolution PAI(eff) maps. Ground PAI(eff) value…

Monitoring fire-affected areas using Thematic Mapper data

In this paper three methods for updating inventories of burned areas have been presented and examined. They include Multitemporal Principal Component Analysis (MPCA), Change Vector Analysis (CVA) a...

Understanding deep learning in land use classification based on Sentinel-2 time series

AbstractThe use of deep learning (DL) approaches for the analysis of remote sensing (RS) data is rapidly increasing. DL techniques have provided excellent results in applications ranging from parameter estimation to image classification and anomaly detection. Although the vast majority of studies report precision indicators, there is a lack of studies dealing with the interpretability of the predictions. This shortcoming hampers a wider adoption of DL approaches by a wider users community, as model’s decisions are not accountable. In applications that involve the management of public budgets or policy compliance, a better interpretability of predictions is strictly required. This work aims …

Extraction of Endmembers from Spectral Mixtures

Abstract Linear spectral mixture modeling (LSMM) divides each ground resolution element into its constituent materials using endmembers which represent the spectral characteristics of the cover types. However, it is difficult to identify and estimate the spectral signature of pure components or endmembers which form the scene, since they vary with the scale and purpose of the study. We propose three different methods to estimate the spectra of pure components from a set of unknown mixture spectra. Two of the methods consist in different optimization procedures based on objective functions defined from the coordinate axes of the dominant factors. The third one consists in the design of a neu…

Vegetation vulnerability to drought in Spain

[EN] Frequency of climatic extremes like long duration droughts has increased in Spain over the last century.The use of remote sensing observations for monitoring and detecting drought is justified on the basis that vegetation vigor is closely related to moisture condition. We derive satellite estimates of bio-physical variables such as fractional vegetation cover (FVC) from MODIS/EOS and SEVIRI/MSG time series. The study evaluates the strength of temporal relationships between precipitation and vegetation condition at time-lag and cumulative rainfall intervals. From this analysis, it was observed that the climatic disturbances affected both the growing season and the total amount of vegeta…

Drought Monitoring In The Mediterranean Basin Using The Seviri/Msg Gpp Product (Mgpp)

Recently, the Satellite Application Facility for Land Surface Analysis (LSA-SAF) has just released a new product that helps to characterize ecosystem processes, the 10-day LSA SAF GPP product from SEVIRI/MSG data (MGPP LSA-411). The GPP product is based on Monteith's concept, which models GPP as the product of the incoming photosynthetically active radiation (PAR), the fractional absorption of that flux $(\mathrm{f}_{APAR})$ and a light-use efficiency factor $(\varepsilon)$. Preliminary results on the use of the MGPP product in the assessment of ecosystem response to drought events are presented in this work for a short period of three years. A few sites located in the Mediterranean basin a…

Growing stock volume from multi-temporal landsat imagery through google earth engine

Growing stock volume (GSV) is one of the most important variables for.forest management and is traditionally- estimated from ground measurements. These measurements are expensive and therefore sparse and hard to maintain in time on a regular basis. Remote sensing data combined with national forest inventories constitute a helpful tool to estimate and map forest attributes. However, most studies on GSV estimation from remote sensing data focus on small forest areas with a single or only a few species. The current study aims to map GSV in peninsular Spain, a rather large and very heterogeneous area. Around 50 000 wooded land plots from the Third Spanish National Forest Inventory (NFI3) were u…

A Mixture Modeling Approach to Estimate Vegetation Parameters for Heterogeneous Canopies in Remote Sensing

In this article, we describe a reflectance model which parametrizes the reflectance of vegetation canopies from optical properties of leaves and soil, and dominant canopy structural parameters. The model assumes certain principles of geometric models, for example, that sensor integrates the radiance reflected from three components, plant, shaded soil, and illuminated soil. Its inversion provides compositional information of the ground surface that is linked with the interpretation of the linear spectral mixture modeling (LSMM). This model also offers the potential for retrieving other meaningful biophysical properties such as LAI. The model has been tested on simulated spectra of spectral m…

Mapping Leaf Area Index with a Smartphone and Gaussian Processes

Leaf area index (LAI) is a key biophysical parameter used to determine foliage cover and crop growth in environmental studies. Smartphones are nowadays ubiquitous sensor devices with high computational power, moderate cost, and high-quality sensors. A smartphone app, which is called PocketLAI, was recently presented and tested for acquiring ground LAI estimates. In this letter, we explore the use of state-of-the-art nonlinear Gaussian process regression (GPR) to derive spatially explicit LAI estimates over rice using ground data from PocketLAI and Landsat 8 imagery. GPR has gained popularity in recent years because of its solid Bayesian foundations that offer not only high accuracy but also…

Deep learning for agricultural land use classification from Sentinel-2

[ES] En el campo de la teledetección se ha producido recientemente un incremento del uso de técnicas de aprendizaje profundo (deep learning). Estos algoritmos se utilizan con éxito principalmente en la estimación de parámetros y en la clasificación de imágenes. Sin embargo, se han realizado pocos esfuerzos encaminados a su comprensión, lo que lleva a ejecutarlos como si fueran “cajas negras”. Este trabajo pretende evaluar el rendimiento y acercarnos al entendimiento de un algoritmo de aprendizaje profundo, basado en una red recurrente bidireccional de memoria corta a largo plazo (2-BiLSTM), a través de un ejemplo de clasificación de usos de suelo agrícola de la Comunidad Valenciana dentro d…

A SIMPLIFIED ALGORITHM FOR THE EVALUATION OF FROST-AFFECTED CITRUS

Patterns Comparison Between Gome-2 Sun-Induced Fluorescence and Msg Gross Primary Production

A comparison between maximum monthly MSG gross primary production (GPP) estimates with the sun-induced chlorophyll fluorescence (SIF) product from the Global Ozone Monitoring Experiment-2 (GOME-2) over Europe and Africa is presented as an indirect validation of MSG GPP estimates. The maximum daily GPP value for each month is derived from daily MSG GPP, which takes full advantage of the SEVIRI/MSG products from the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) delivered by the Satellite Application Facility for Land Surface Analysis (LSA SAF). A linear relationship found between both products over savanna, grasslands and forests at high latitudes evidence…

Optimized Application of Biome-BGC for Modeling the Daily GPP of Natural Vegetation Over Peninsular Spain

A methodology for improving the application of Biome-BGC in peninsular Spain was developed focusing on the optimization of the rooting depth (zroot), which is not available for the study area on a spatially distributed basis. The optimal zroot was identified by comparing daily gross primary production (GPP) simulations with varying zroot to GPP estimations from a production efficiency model previously optimized for and validated in the study area. The methodology was first tested in four eddy covariance (EC) sites representative of Mediterranean ecosystems and next applied at a regional scale to the whole study area. As a result, daily GPP simulated maps for the 2005-2012 period and an opti…

Characterizing land condition variability in Ferlo, Senegal (2001–2009) using multi-temporal 1-km Apparent Green Cover (AGC) SPOT Vegetation data

Abstract The ecosystem state or ‘land condition’ can be characterized by a set of attributes, which show variations at different temporal scales. A multi-resolution analysis (MRA) based on the wavelet transform (WT) has been implemented to examine the land condition of a dryland region in Ferlo (Senegal) over the period 2001–2009. This methodology has proven to be useful for smoothing time series while considering those temporal resolutions that incorporate information about the vegetation dynamics. For this purpose, time series of the 1-km Apparent Green Cover (AGC) from the 10-day composites SPOT Vegetation (VGT) data are analyzed. Two relevant outputs from the MRA, A 1 (de-noised) and th…

Intercomparison and quality assessment of MERIS, MODIS and SEVIRI FAPAR products over the Iberian Peninsula

Abstract The fraction of absorbed photosynthetically active radiation (FAPAR) is a key variable in productivity and carbon cycle models. The variety of available FAPAR satellite products from different space agencies leads to the necessity of assessing the existing differences between them before using into models. Discrepancies of four FAPAR products derived from MODIS, SEVIRI and MERIS (TOAVEG and MGVI algorithms), covering the Iberian Peninsula from July 2006 to June 2007 are here analyzed. The assessment is based on an intercomparison involving the spatial and temporal consistency between products and a statistical analysis across land cover types. In general, significant differences ar…

Mapping daily global solar irradiation over Spain: A comparative study of selected approaches

Abstract Three methods to estimate the daily global solar irradiation are compared: the Bristow–Campbell (BC), Artificial Neural Network (ANN) and Kernel Ridge Regression (KRR). BC is an empirical approach based on air maximum and minimum temperature. ANN and KRR are non-linear approaches that use temperature and precipitation data (which have been selected as the best combination of input data from a gamma test). The experimental dataset includes 4 years (2005–2008) of daily irradiation collected at 40 stations and temperature and precipitation data collected at 400 stations over Spain. Results show that the ANN method produces the best global solar irradiation estimates, with a mean absol…

Vegetation cover seasonal changes assessment from TM imagery in a semi-arid landscape

This work evaluates the suitability of spectral mixture analysis (SMA) methods to assess vegetation cover seasonal changes in a desertification context. Our main interest is to produce remotely sensed derived maps, sensitive to vegetation activity and quite independent of the soil background. A further aim is to analyse the inter-annual variations of this magnitude for different natural vegetation species, in response to seasonal and climatic changes. Fractional vegetation cover (FVC) was obtained using a Variable Endmember Spectral Mixture Analysis (VESMA) technique. The aim is to identify the main vegetation cover and lithological units and decompose them in separate stages. The use of sp…

Start of the dry season as a main determinant of inter-annual Mediterranean forest production variations

Abstract Recent investigations have highlighted the dependence of Mediterranean forest production on spring rainfall. The current work introduces the concept of the start of the dry season (SDS) and performs a three-step analysis to determine the effect of SDS on Mediterranean forest production. Seven forest zones of Tuscany (Central Italy), which present differently pronounced Mediterranean features, are considered. First, a statistical analysis investigates the influence of spring water budget on forest Normalized Difference Vegetation Index (NDVI) inter-annual variations during July–August. The analysis is then extended to assess the impact of inter-annual SDS variability on forest gross…

Noise Reduction and Gap Filling of fAPAR Time Series Using an Adapted Local Regression Filter

Time series of remotely sensed data are an important source of information for understanding land cover dynamics. In particular, the fraction of absorbed photosynthetic active radiation (fAPAR) is a key variable in the assessment of vegetation primary production over time. However, the fAPAR series derived from polar orbit satellites are not continuous and consistent in space and time. Filtering methods are thus required to fill in gaps and produce high-quality time series. This study proposes an adapted (iteratively reweighted) local regression filter (LOESS) and performs a benchmarking intercomparison with four popular and generally applicable smoothing methods: Double Logistic (DLOG), sm…

Validation of daily global solar irradiation images from MSG over Spain

Abstract Daily irradiation images over Spain – area that embraces a highly heterogeneous landscape, climatic conditions and relief – are calculated from the down-welling surface short-wave radiation flux (DSSF) product derived from the MSG SEVIRI images. Their analysis and validation is carried out using two different station networks along the year 2008. The first network covers the peninsular Spain and Balearic islands. A denser one, covering the Catalonian territory and including many stations located in rugged terrain, is found useful to assess the elevation correction to be applied to the images. The statistics from the validation using the first network shows a relative mean bias of a…

Quantifying water stress effect on daily light use efficiency in Mediterranean ecosystems using satellite data

16 pages, 2 figures, 6 tables, supplemental material https://dx.doi.org/10.1080/17538947.2016.1247301

Daily GPP estimates in Mediterranean ecosystems by combining remote sensing and meteorological data

The accurate representation of terrestrial CO2 uptake (GPP) using Monteith's approach requires a frequent and site-specific parameterization of the model inputs. In this work, an optimization of this approach has been carried out by adjusting the inputs (f(APAR), PAR and epsilon) for the study area, peninsular Spain, a typical Mediterranean region. The daily GPP images have been calculated for 2008 and 2011 with a 1-km spatial resolution and validated by comparison with in situ GPP estimates from the eddy covariance data (direct validation) and by inter-comparison with the MODIS GPP product. The direct validation has evidenced an excellent agreement with correlations up to 0.98 in 2008 and …

Monitoring water stress in Mediterranean semi-natural vegetation with satellite and meteorological data

In arid and semi-arid environments, the characterization of the inter-annual variations of the light use efficiency ε due to water stress still relies mostly on meteorological data. Thus the GPP estimation based on procedures exclusively driven by remote sensing data has not found yet a widespread use. In this work, the potential to characterize the water stress in semi-natural vegetation of three spectral indices (NDWI, SIWSI and NDI7) – from MODIS broad spectral bands – has been analyzed in comparison to a meteorological factor (Cws). The study comprises 70 sites (belonging to 7 different ecosystems) uniformly distributed over Tuscany, and three eddy covariance tower sites. An operational…

Retrieval of daily gross primary production over Europe and Africa from an ensemble of SEVIRI/MSG products

The main goal of this paper is to derive a method for a daily gross primary production (GPP) product over Europe and Africa taking the full advantage of the SEVIRI/MSG satellite products from the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) sensors delivered from the Satellite Application Facility for Land Surface Analysis (LSA SAF) system. Special attention is paid to model the daily GPP response from an optimized Montheith's light use efficiency model under dry conditions by controlling water shortage limitations from the actual evapotranspiration and the potential evapotranspiration (PET). The PET was parameterized using the mean daily air temperatur…

A generalized soil-adjusted vegetation index

Operational monitoring of vegetative cover by remote sensing currently involves the utilisation of vegetation indices (VIs), most of them being functions of the reflectance in red (R) and near-infrared (NIR) spectral bands. A generalized soil-adjusted vegetation index (GESAVI), theoretically based on a simple vegetation canopy model, is introduced. It is defined in terms of the soil line parameters (A and B) as: GESAVI=(NIRBRA)/(R+Z), where Z is related to the red reflectance at the cross point between the soil line and vegetation isolines. As Z is a soil adjustment coefficient, this new index can be considered as belonging to the SAVI family. In order to analyze the GESAVI sensitivity to s…

Evaluation of the LSA-SAF gross primary production product derived from SEVIRI/MSG data (MGPP)

The objective of this study is to describe a completely new 10-day gross primary production (GPP) product (MGPP LSA-411) based on data from the geostationary SEVIRI/MSG satellite within the LSA SAF (Land Surface Analysis SAF) as part of the SAF (Satellite Application Facility) network of EUMETSAT. The methodology relies on the Monteith approach. It considers that GPP is proportional to the absorbed photosynthetically active radiation APAR and the proportionality factor is known as the light use efficiency ε. A parameterization of this factor is proposed as the product of a εmax, corresponding to the canopy functioning under optimal conditions, and a coefficient quantifying the reduction of …

Climate Data Records of Vegetation Variables from Geostationary SEVIRI/MSG Data: Products, Algorithms and Applications

The scientific community requires long-term data records with well-characterized uncertainty and suitable for modeling terrestrial ecosystems and energy cycles at regional and global scales. This paper presents the methodology currently developed in EUMETSAT within its Satellite Application Facility for Land Surface Analysis (LSA SAF) to generate biophysical variables from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on board MSG 1-4 (Meteosat 8-11) geostationary satellites. Using this methodology, the LSA SAF generates and disseminates at a time a suite of vegetation products, such as the leaf area index (LAI), the fraction of the photosynthetically active radiation absorbed …

Estimación de la fAPAR sobre la Península Ibérica a partir de la inversión del modelo de transferencia radiativa 4SAIL2

El objetivo de este trabajo consiste en la estimación de la fAPAR en la Península Ibérica a partir de datos MODIS. En primer lugar, se ha simulado un conjunto de datos de reflectividades y de fAPAR a partir de los modelos de transferencia radiativa de hoja (PROSPECT) y de cubiertas heterogéneas (4SAIL2). En segundo lugar, se ha entrenado un conjunto de redes neuronales artificiales (RNAs) para obtener mediante inversión la relación entre la fAPAR y las reflectividades simuladas y así calcular, por último, la fAPAR de la Península Ibérica a partir de imágenes de reflectividad de MODIS. Además, se ha analizado la influencia de la configuración de observación e iluminación, nadir y oblicua. La…

Linear spectral mixture modelling to estimate vegetation amount from optical spectral data

Abstract Spectral mixture modelling has developed in recent years as a suitable remote sensing tool for analysing the biophysical and compositional character of ground surfaces. In this paper the potentiality of the linear spectral mixture model to extract vegetation related parameters from 0·4-2·5 μm reflectance data has been tested. High spectral resolution reflectance measurements of soil-plant mixtures with different soil colour and plant densities were carried out in a laboratory experiment. The constrained least-squares and the factor analysis unmixing procedures were applied to generate endmember fractions of the components present in the mixtures and to test the validity of the mode…