Search results for "EVAL"
showing 10 items of 7417 documents
The global forest above-ground biomass pool for 2010 estimated from high-resolution satellite observations
2021
Funding Information: We are thankful to the GlobBiomass project team and Frank Martin Seifert (ESA) for valuable suggestions and stimulating scientific discussions. We are thankful to Takeo Tadono (JAXA EORC), Masato Hayashi, (JAXA EORC), Kazufumi Kobayashi (RESTEC), Åke Rosenqvist (soloEO), and Josef Kellndorfer (EBD) for support with the use and interpretation of the ALOS PALSAR mosaics. Support by the CCI Land Cover project team, in particular Sophie Bontemps (UCL), is greatly acknowledged. The help from Martin Jung (MPI-BGC) in feature selection and Ulrich Weber (MPI-BGC) for data processing for the GSV-to-AGB conversions is greatly acknowledged. Forest inventory data for the validation…
Statistical retrieval of atmospheric profiles with deep convolutional neural networks
2019
Abstract Infrared atmospheric sounders, such as IASI, provide an unprecedented source of information for atmosphere monitoring and weather forecasting. Sensors provide rich spectral information that allows retrieval of temperature and moisture profiles. From a statistical point of view, the challenge is immense: on the one hand, “underdetermination” is common place as regression needs to work on high dimensional input and output spaces; on the other hand, redundancy is present in all dimensions (spatial, spectral and temporal). On top of this, several noise sources are encountered in the data. In this paper, we present for the first time the use of convolutional neural networks for the retr…
Sun-induced chlorophyll fluorescence III: benchmarking retrieval methods and sensor characteristics for proximal sensing
2019
[EN] The interest of the scientific community on the remote observation of sun-induced chlorophyll fluorescence (SIF) has increased in the recent years. In this context, hyperspectral ground measurements play a crucial role in the calibration and validation of future satellite missions. For this reason, the European cooperation in science and technology (COST) Action ES1309 OPTIMISE has compiled three papers on instrument characterization, measurement setups and protocols, and retrieval methods (current paper). This study is divided in two sections; first, we evaluated the uncertainties in SIF retrieval methods (e.g., Fraunhofer line depth (FLD) approaches and spectral fitting method (SFM))…
Understanding deep learning in land use classification based on Sentinel-2 time series
2020
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 …
Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress
2019
Remote sensing of solar-induced chlorophyll fluorescence (SIF) is a rapidly advancing front in terrestrial vegetation science, with emerging capability in space-based methodologies and diverse application prospects. Although remote sensing of SIF – especially from space – is seen as a contemporary new specialty for terrestrial plants, it is founded upon a multi-decadal history of research, applications, and sensor developments in active and passive sensing of chlorophyll fluorescence. Current technical capabilities allow SIF to be measured across a range of biological, spatial, and temporal scales. As an optical signal, SIF may be assessed remotely using high-resolution spectral sensors in …
Comparison of SMOS and SMAP soil moisture retrieval approaches using tower-based radiometer data over a vineyard field
2014
International audience; The objective of this study was to compare several approaches to soil moisture (SM) retrieval using l-band microwave radiometry. The comparison was based on a brightness temperature (TB) data set acquired since 2010 by the L-band radiometer ELBARA-II over a vineyard field at the Valencia Anchor Station (VAS) site. ELBARA-II, provided by the European Space Agency (ESA) within the scientific program of the SMOS (Soil Moisture and Ocean Salinity) mission, measures multiangular TB data at horizontal and vertical polarization for a range of incidence angles (30°–60°). Based on a three year data set (2010–2012), several SM retrieval approaches developed for spaceborne miss…
PHYSICS-based retrieval of scattering albedo and vegetation optical depth using multi-sensor data integration
2017
Vegetation optical depth and scattering albedo are crucial parameters within the widely used τ-ω model for passive microwave remote sensing of vegetation and soil. A multi-sensor data integration approach using ICESat lidar vegetation heights and SMAP radar as well as radiometer data enables a direct retrieval of the two parameters on a physics-derived basis. The crucial step within the retrieval methodology is the calculus of the vegetation scattering coefficient KS, where one exact and three approximated solutions are provided. It is shown that, when using the assumption of a randomly oriented volume, the backscatter measurements of the radar provide a sufficient first order estimate and …
Occurrence of fossil organic matter in modern environments: optical, geochemical and isotopic evidence
2011
International audience; This study relates to the input and fate of fossil organic matter (FOM) in the modern environment, and focuses on two experimental watersheds overlying Jurassic marls: Le Laval and Le Brusquet (1 km(2) in area), located near Digne, Alpes-de-Haute-Provence, France. Considering that FOM delivery is mainly a result of different processes affecting sedimentary rocks [(bio)chemical and mechanical weathering], samples from different pools were collected: bedrocks, weathering profiles, soils and riverine particles. The samples were examined using complementary techniques: optical (palynofacies methods), geochemical (Rock-Eval 6 pyrolysis, C/N ratio), molecular (gas chromato…
Soil moisture modelling of a SMOS pixel: interest of using the PERSIANN database over the Valencia Anchor Station
2010
In the framework of Soil Moisture and Ocean Salinity (SMOS) Calibration/Validation (Cal/Val) activities, this study addresses the use of the PERSIANN-CCS<sup>1</sup>database in hydrological applications to accurately simulate a whole SMOS pixel by representing the spatial and temporal heterogeneity of the soil moisture fields over a wide area (50×50 km<sup>2</sup>). The study focuses on the Valencia Anchor Station (VAS) experimental site, in Spain, which is one of the main SMOS Cal/Val sites in Europe. <br><br> A faithful representation of the soil moisture distribution at SMOS pixel scale (50×50 km<sup>2</sup>) requires an accurate estimation…
Global Sensitivity Analysis of Leaf-Canopy-Atmosphere RTMs: Implications for Biophysical Variables Retrieval from Top-of-Atmosphere Radiance Data.
2019
Knowledge of key variables driving the top of the atmosphere (TOA) radiance over a vegetated surface is an important step to derive biophysical variables from TOA radiance data, e.g., as observed by an optical satellite. Coupled leaf-canopy-atmosphere Radiative Transfer Models (RTMs) allow linking vegetation variables directly to the at-sensor TOA radiance measured. Global Sensitivity Analysis (GSA) of RTMs enables the computation of the total contribution of each input variable to the output variance. We determined the impacts of the leaf-canopy-atmosphere variables into TOA radiance using the GSA to gain insights into retrievable variables. The leaf and canopy RTM PROSAIL was coupled with…