Search results for "11"

Derivation of global vegetation biophysical parameters from EUMETSAT Polar System

2020

Abstract This paper presents the algorithm developed in LSA-SAF (Satellite Application Facility for Land Surface Analysis) for the derivation of global vegetation parameters from the AVHRR (Advanced Very High Resolution Radiometer) sensor on board MetOp (Meteorological–Operational) satellites forming the EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Polar System (EPS). The suite of LSA-SAF EPS vegetation products includes the leaf area index (LAI), the fractional vegetation cover (FVC), and the fraction of absorbed photosynthetically active radiation (FAPAR). LAI, FAPAR, and FVC characterize the structure and the functioning of vegetation and are key par…

Validation of the Sentinel-3 Ocean and Land Colour Instrument (OLCI) Terrestrial Chlorophyll Index (OTCI): Synergetic Exploitation of the Sentinel-2 …

2018

Continuity to the Medium Resolution Imaging Spectrometer (MERIS) Terrestrial Chlorophyll Index (MTCI) will be provided by the Sentinel-3 Ocean and Land Colour Instrument (OLCI), and to ensure its utility in a wide range of operational applications, validation efforts are required. In the past, these activities have been constrained by the need for costly airborne hyperspectral data acquisition, but the Sentinel-2 Multispectral Instrument (MSI) now offers a promising alternative. In this paper, we explore the synergetic use of Sentinel-2 MSI data for validation of the Sentinel-3 OLCI Terrestrial Chlorophyll Index (OTCI) over the Valencia Anchor Station, a large agricultural site in the Valen…

Fractals and geography

2007

Machine learning regression algorithms for biophysical parameter retrieval: Opportunities for Sentinel-2 and -3

2012

Abstract ESA's upcoming satellites Sentinel-2 (S2) and Sentinel-3 (S3) aim to ensure continuity for Landsat 5/7, SPOT-5, SPOT-Vegetation and Envisat MERIS observations by providing superspectral images of high spatial and temporal resolution. S2 and S3 will deliver near real-time operational products with a high accuracy for land monitoring. This unprecedented data availability leads to an urgent need for developing robust and accurate retrieval methods. Machine learning regression algorithms may be powerful candidates for the estimation of biophysical parameters from satellite reflectance measurements because of their ability to perform adaptive, nonlinear data fitting. By using data from …

Optimized Class-Separability in Hyperspectral Images

2016

International audience; Image visualization techniques are mostly based on three bands as RGB color composite channels for human eye to characterize the scene. This, however, is not effective in case of hyper-spectral images (HSI) because they contain dozens of informative spectral bands. To eliminate redundancy of spectral information among these bands, dimensionality reduction (DR) is applied while at the same trying to retain maximum information. In this paper, we propose a new method of information-preserved hyper-spectral satellite image visualization that is based on fusion of unsupervised band selection techniques and color matching function (CMF) stretching. The results show consist…

Environmental and biological factors are joint drivers of mercury biomagnification in subarctic lake food webs along a climate and productivity gradi…

2021

Subarctic lakes are getting warmer and more productive due to the joint effects of climate change and intensive land-use practices (e.g. forest clear-cutting and peatland ditching), processes that potentially increase leaching of peat- and soil-stored mercury into lake ecosystems. We sampled biotic communities from primary producers (algae) to top consumers (piscivorous fish), in 19 subarctic lakes situated on a latitudinal (69.0-66.5 degrees N), climatic (+3.2 degrees C temperature and +30% precipitation from north to south) and catchment land-use (pristine to intensive forestry areas) gradient. We first tested how the joint effects of climate and productivity influence mercury biomagnific…

Smap-based retrieval of vegetation opacity and albedo

2020

Over land the vegetation canopy affects the microwave brightness temperature by emission, scattering and attenuation of surface soil emission. The questions addressed in this study are: 1) what is the transparency of the vegetation canopy for different biomes around the Globe at the low-frequency L-band?, 2) what is the seasonal amplitude of vegetation microwave optical depth for different biomes?, 3) what is the effective scattering at this frequency for different vegetation types?, 4) what is the impact of imprecise characterization of vegetation microwave properties on retrieval of soil surface conditions? These questions are addressed based on the recently completed one full annual cycl…

Evaluating roughness effects on C-band AMSR-E observations

2014

International audience; The usefulness of microwave remote sensing to retrieve near-surface soil moisture has already been demonstrated in many studies. However, obtaining high quality estimates of soil moisture is influenced by many effects from soil, vegetation and atmosphere; one of the key parameters is surface roughness. This research focusses on a semi-empirical method to evaluate the roughness effects from space borne observations. Global maps of roughness effects are evaluated at C-band from AMSR-E measurements.

LAI, FAPAR and FCOVER ground-truth map creation from FASat-C satellite imagery and in-situ measurements in Chimbarongo, Chile, for satellite products…

2016

[EN] In remote sensing, validation exercises are essential to ensure the quality of the products originated from satellite Earth observations. To assess the measurement uncertainty derived from satellite products, several ground field data from different ecosystems must be available for use. In the same order of importance, it is necessary to define data sampling and up-scaling methodologies to allow a suitable comparison between the ground data and the pixel size of the product. This paper shows the applied methodology used in the FP7 ImagineS project (Implementing Multi-scale Agricultural Indicators Exploiting Sentinels) to validate 10-days global LAI, FAPAR and vegetation cover products …

Vegetation vulnerability to drought in Spain

2014

[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…