Search results for "SATELLITE"
showing 10 items of 1031 documents
Mapping land surface emissivity from NDVI: Application to European, African, and South American areas
1996
Thermal infrared emissivity is an important parameter both for surface characterization and for atmospheric correction methods. Mapping the emissivity from satellite data is therefore a very important question to solve. The main problem is the coupling of the temperature and emissivity effects in the thermal radiances. Several methods have been developed to obtain surface emissivity from satellite data. In this way we propose a theoretical model that relates the emissivity to the NDVI (normalized difference vegetation index) of a given surface and explains the experimental behavior observed by van de Griend and Owe. We can use it to obtain the emissivity in any thermal channel, but in this …
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…
Validation of SMAP surface soil moisture products with core validation sites
2017
Abstract The NASA Soil Moisture Active Passive (SMAP) mission has utilized a set of core validation sites as the primary methodology in assessing the soil moisture retrieval algorithm performance. Those sites provide well-calibrated in situ soil moisture measurements within SMAP product grid pixels for diverse conditions and locations. The estimation of the average soil moisture within the SMAP product grid pixels based on in situ measurements is more reliable when location specific calibration of the sensors has been performed and there is adequate replication over the spatial domain, with an up-scaling function based on analysis using independent estimates of the soil moisture distributio…
Gaussian Processes Retrieval of LAI from Sentinel-2 Top-of-Atmosphere Radiance Data
2020
Abstract Retrieval of vegetation properties from satellite and airborne optical data usually takes place after atmospheric correction, yet it is also possible to develop retrieval algorithms directly from top-of-atmosphere (TOA) radiance data. One of the key vegetation variables that can be retrieved from at-sensor TOA radiance data is leaf area index (LAI) if algorithms account for variability in atmosphere. We demonstrate the feasibility of LAI retrieval from Sentinel-2 (S2) TOA radiance data (L1C product) in a hybrid machine learning framework. To achieve this, the coupled leaf-canopy-atmosphere radiative transfer models PROSAIL-6SV were used to simulate a look-up table (LUT) of TOA radi…
Optimizing Gaussian Process Regression for Image Time Series Gap-Filling and Crop Monitoring
2020
Image processing entered the era of artificial intelligence, and machine learning algorithms emerged as attractive alternatives for time series data processing. Satellite image time series processing enables crop phenology monitoring, such as the calculation of start and end of season. Among the promising algorithms, Gaussian process regression (GPR) proved to be a competitive time series gap-filling algorithm with the advantage of, as developed within a Bayesian framework, providing associated uncertainty estimates. Nevertheless, the processing of time series images becomes computationally inefficient in its standard per-pixel usage, mainly for GPR training rather than the fitting step. To…
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…
Vicarious Calibration of the Landsat 7 Thermal Infrared Band and LST Algorithm Validation of the ETM+ Instrument Using Three Global Atmospheric Profi…
2017
Due to problems in the thermal infrared sensor on-board the Landsat-8 satellite, Landsat-7 (L7) can be an interesting alternative source of thermal data because it is the only source of well-calibrated, free, high-resolution data. To contribute to the quality of thermal data, a vicarious calibration (VC) of the enhanced thematic mapper instrument and a validation of the single-channel general equation and the water vapor approach algorithm in conjunction with an inversion of the radiative transfer equation (RTE) have been performed during 2013–2015 over two Spanish test sites. For this purpose, three global atmospheric profile data sets were used to better characterize the error due to atmo…
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…
Evaluation of the MODIS Albedo product over a heterogeneous agricultural area
2013
In this article, the Moderate Resolution Imaging Spectroradiometer MODIS Bidirectional Reflectance Distribution Function BRDF/Albedo product MCD43 is evaluated over a heterogeneous agricultural area in the framework of the Earth Observation: Optical Data Calibration and Information Extraction EODIX project campaign, which was developed in Barrax Spain in June 2011. In this method, two models, the RossThick-LiSparse-Reciprocal RTLSR which corresponds to the MODIS BRDF algorithm and the RossThick-Maignan-LiSparse-Reciprocal RTLSR-HS, were tested over airborne data by processing high-resolution images acquired with the Airborne Hyperspectral Scanner AHS sensor. During the campaign, airborne im…
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…