Search results for "Vegetation"
showing 10 items of 1069 documents
Quantifying vegetation biophysical variables from the Sentinel-3/FLEX tandem mission: Evaluation of the synergy of OLCI and FLORIS data sources
2020
The ESA’s forthcoming FLuorescence EXplorer (FLEX) mission is dedicated to the global monitoring of the vegetation’s chlorophyll fluorescence by means of an imaging spectrometer, FLORIS. In order to properly interpret the fluorescence signal in relation to photosynthetic activity, essential vegetation variables need to be retrieved concomitantly. FLEX will fly in tandem with Sentinel-3 (S3), which conveys the Ocean and Land Colour Instrument (OLCI) that is designed to characterize the atmosphere and the terrestrial vegetation at a spatial resolution of 300 m. In this work we present the retrieval models of four essential biophysical variables: (1) Leaf Area Index (LAI), (2) leaf chlorophyll…
Hybrid inversion of radiative transfer models based on high spatial resolution satellite reflectance data improves fractional vegetation cover retrie…
2021
In forest landscapes affected by fire, the estimation of fractional vegetation cover (FVC) from remote sensing data using radiative transfer models (RTMs) enables to evaluate the ecological impact of such disturbance across plant communities at different spatio-temporal scales. Even though, when landscapes are highly heterogeneous, the fine-scale ground spatial variation might not be properly captured if FVC products are provided at moderate or coarse spatial scales, as typical of most of operational Earth observing satellite missions. The objective of this study was to evaluate the potential of a RTM inversion approach for estimating FVC from satellite reflectance data at high spatial reso…
Multi-Crop Green LAI Estimation with a New Simple Sentinel-2 LAI Index (SeLI)
2019
The spatial quantification of green leaf area index (LAIgreen), the total green photosynthetically active leaf area per ground area, is a crucial biophysical variable for agroecosystem monitoring. The Sentinel-2 mission is with (1) a temporal resolution lower than a week, (2) a spatial resolution of up to 10 m, and (3) narrow bands in the red and red-edge region, a highly promising mission for agricultural monitoring. The aim of this work is to define an easy implementable LAIgreen index for the Sentinel-2 mission. Two large and independent multi-crop datasets of in situ collected LAIgreen measurements were used. Commonly used LAIgreen indices applied on the Sentinel-2 10 m ×
Crop specific algorithms trained over ground measurements provide the best performance for GAI and fAPAR estimates from Landsat-8 observations
2021
Abstract Estimation of Green Area Index (GAI) and fraction of Absorbed Photosynthetically Active Radiation (fAPAR) from decametric satellites was investigated in this study using a large database of ground measurements over croplands. It covers six main crop types including rice, corn, wheat and barley, sunflower, soybean and other types of crops. Ground measurements were completed using either digital hemispherical cameras, LAI-2000 or AccuPAR devices over sites representative of a decametric pixel. Sites were spread over the globe and the data collected at several growth stages concurrently to the acquisition of Landsat-8 images. Several machine learning techniques were investigated to re…
Potential of Automated Digital Hemispherical Photography and Wireless Quantum Sensors for Routine Canopy Monitoring and Satellite Product Validation
2021
To better characterize the temporal dynamics of vegetation biophysical variables, a variety of automated in situ measurement techniques have been developed in recent years. In this study, we investigated automated digital hemispherical photography (DHP) and wireless quantum sensors, which were installed at two sites under the Copernicus Ground Based Observations for Validation (GBOV) project. Daily estimates of plant area index (PAI) and the fraction of absorbed photosynthetically active radiation (FAPAR) were obtained, which realistically described expected vegetation dynamics. Good correspondence with manual DHP and LAI-2000 data (RMSE = 0.39 to 0.90 for PAI, RMSE = 0.07 for FAPAR) provid…
Top-of-Atmosphere Retrieval of Multiple Crop Traits Using Variational Heteroscedastic Gaussian Processes within a Hybrid Workflow.
2021
In support of cropland monitoring, operational Copernicus Sentinel-2 (S2) data became available globally and can be explored for the retrieval of important crop traits. Based on a hybrid workflow, retrieval models for six essential biochemical and biophysical crop traits were developed for both S2 bottom-of-atmosphere (BOA) L2A and S2 top-of-atmosphere (TOA) L1C data. A variational heteroscedastic Gaussian process regression (VHGPR) algorithm was trained with simulations generated by the combined leaf-canopy reflectance model PROSAILat the BOA scale and further combined with the Second Simulation of a Satellite Signal in the Solar Spectrum (6SV) atmosphere model at the TOA scale. Establishe…
Towards a long-term dataset of ELBARA-II measurements assisting SMOS level-3 land product and algorithm validation at the Valencia Anchor Station
2015
[EN] The Soil Moisture and Ocean Salinity (SMOS) mission was launched on 2nd November 2009 with the objective of providing global estimations of soil moisture and sea salinity. The main activity of the Valencia Anchor Station (VAS) is currently to assist in a long-term validation of SMOS land products. This study focus on a level 3 SMOS data validation with in situ measurements carried out in the period 2010-2012 over the VAS. ELBARA-II radiometer is placed in the VAS area, observing a vineyard field considered as representative of a major proportion of an area of 50×50 km, enough to cover a SMOS footprint. Brightness temperatures (TB) acquired by ELBARA-II have been compared to those obser…
NPP VIIRS land surface temperature product validation using worldwide observation networks.
2013
International audience; Thermal infrared satellite observations of the Earth's surface are key components in estimating the surface skin temperature over global land areas. This work presents validation methodologies to estimate the quantitative uncertainty in Land Surface Temperature (LST) product derived from the Visible Infrared Imager Radiometer Suite (VIIRS) onboard Suomi National Polar-orbiting Partnership (NPP) using ground-based measurements currently made operationally at many field and weather stations around the world. Over heterogeneous surfaces in terms of surface types or biophysical properties (e.g., vegetation density, emissivity), the validation protocol accounts for land s…
Retrieval of daily gross primary production over Europe and Africa from an ensemble of SEVIRI/MSG products
2018
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 multisensor fusion approach to improve LAI time series
2011
International audience; High-quality and gap-free satellite time series are required for reliable terrestrial monitoring. Moderate resolution sensors provide continuous observations at global scale for monitoring spatial and temporal variations of land surface characteristics. However, the full potential of remote sensing systems is often hampered by poor quality or missing data caused by clouds, aerosols, snow cover, algorithms and instrumentation problems. A multisensor fusion approach is here proposed to improve the spatio-temporal continuity, consistency and accuracy of current satellite products. It is based on the use of neural networks, gap filling and temporal smoothing techniques. …