6533b85ffe1ef96bd12c1c99
RESEARCH PRODUCT
Global-Scale Evaluation of Roughness Effects on C-Band AMSR-E Observations
Jean-pierre WigneronRobert Fernandez-moranAmen Al-yaariXiaoyong YuMarie ParrensYann KerrQin-yu YeLingmei JiangShu WangWei Jisubject
010504 meteorology & atmospheric sciencestélédétectionScience0211 other engineering and technologiesWeather forecasting[SDU.STU]Sciences of the Universe [physics]/Earth SciencesElectromagnétismesoil surface roughness02 engineering and technologySurface finishcomputer.software_genredonnée satellite01 natural sciencesSciences de la TerreNormalized Difference Vegetation Indexsoil moisture;soil surface roughness;AMSR-EElectromagnetismEmissivitySurface roughnessTraitement du signal et de l'image14. Life underwaterWater content021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRadiometercapteur smosQSignal and Image processingradiométrie microondesVegetationAMSR-E15. Life on land[SPI.ELEC]Engineering Sciences [physics]/ElectromagnetismEarth SciencesGeneral Earth and Planetary SciencesEnvironmental sciencesoil moisturecomputer[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingdescription
Quantifying roughness effects on ground surface emissivity is an important step in obtaining high-quality soil moisture products from large-scale passive microwave sensors. In this study, we used a semi-empirical method to evaluate roughness effects (parameterized here by the parameter) on a global scale from AMSR-E (Advanced Microwave Scanning Radiometer for EOS) observations. AMSR-E brightness temperatures at 6.9 GHz obtained from January 2009 to September 2011, together with estimations of soil moisture from the SMOS (Soil Moisture and Ocean Salinity) L3 products and of soil temperature from ECMWF’s (European Centre for Medium-range Weather Forecasting) were used as inputs in a retrieval process. In the first step, we retrieved a parameter (referred to as the parameter) accounting for the combined effects of roughness and vegetation. Then, global MODIS NDVI data were used to decouple the effects of vegetation from those of surface roughness. Finally, global maps of the Hr parameters were produced and discussed. Initial results showed that some spatial patterns in the values could be associated with the main vegetation types (higher values of were retrieved generally in forested regions, intermediate values were obtained over crops and grasslands, and lower values were obtained over shrubs and desert) and topography. For instance, over the USA, lower values of were retrieved in relatively flat regions while relatively higher values were retrieved in hilly regions.
year | journal | country | edition | language |
---|---|---|---|---|
2015-05-05 | Remote Sensing |