Search results for "fAPAR"
showing 8 items of 8 documents
GEOV1: LAI, FAPAR essential climate variables and FCOVER global time series capitalizing over existing products. Part 2: Validation and intercomparis…
2013
International audience; This paper describes the scientific validation of the first version of global biophysical products (i.e., leaf area index, fraction of absorbed photosynthetically active radiation and fraction of vegetation cover), namely GEOV1, developed in the framework of the geoland-2/BioPar core mapping service at 1 km spatial resolution and 10-days temporal frequency. The strategy follows the recommendations of the CEOS/WGCV Land Product Validation for LAI global products validation. Several criteria of performance were evaluated, including continuity, spatial and temporal consistency, dynamic range of retrievals, statistical analysis per biome type, precision and accuracy. The…
Global Estimation of Biophysical Variables from Google Earth Engine Platform
2018
This paper proposes a processing chain for the derivation of global Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fraction Vegetation Cover (FVC), and Canopy water content (CWC) maps from 15-years of MODIS data exploiting the capabilities of the Google Earth Engine (GEE) cloud platform. The retrieval chain is based on a hybrid method inverting the PROSAIL radiative transfer model (RTM) with Random forests (RF) regression. A major feature of this work is the implementation of a retrieval chain exploiting the GEE capabilities using global and climate data records (CDR) of both MODIS surface reflectance and LAI/FAPAR datasets allowing the global estim…
Combining hectometric and decametric satellite observations to provide near real time decametric FAPAR product
2017
Abstract A wide range of ecological, agricultural, hydrological and meteorological applications at local to regional scales requires decametric biophysical data. However, before the launch of SENTINEL-2A, only few decametric products are produced and most of them remain limited by the small number of available observations, mostly due to a moderate revisit frequency combined with cloud occurrence. Conversely, kilometric and hectometric biophysical products are now widely available with almost complete and continuous coverage, but the associated spatial resolution limits the application over heterogeneous landscapes. The objective of this study is to combine unfrequent decametric spatial res…
On Line Validation Exercise (OLIVE): A Web Based Service for the Validation of Medium Resolution Land Products. Application to FAPAR Products
2014
International audience; The OLIVE (On Line Interactive Validation Exercise) platform is dedicated to the validation of global biophysical products such as LAI (Leaf Area Index) and FAPAR (Fraction of Absorbed Photosynthetically Active Radiation). It was developed under the framework of the CEOS (Committee on Earth Observation Satellites) Land Product Validation (LPV) sub-group. OLIVE has three main objectives: (i) to provide a consistent and centralized information on the definition of the biophysical variables, as well as a description of the main available products and their performances (ii) to provide transparency and traceability by an online validation procedure compliant with the CEO…
Integrating Domain Knowledge in Data-Driven Earth Observation With Process Convolutions
2022
The modelling of Earth observation data is a challenging problem, typically approached by either purely mechanistic or purely data-driven methods. Mechanistic models encode the domain knowledge and physical rules governing the system. Such models, however, need the correct specification of all interactions between variables in the problem and the appropriate parameterization is a challenge in itself. On the other hand, machine learning approaches are flexible data-driven tools, able to approximate arbitrarily complex functions, but lack interpretability and struggle when data is scarce or in extrapolation regimes. In this paper, we argue that hybrid learning schemes that combine both approa…
Noise Reduction and Gap Filling of fAPAR Time Series Using an Adapted Local Regression Filter
2014
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…
Climate Data Records of Vegetation Variables from Geostationary SEVIRI/MSG Data: Products, Algorithms and Applications
2019
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
2014
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…