Global surface effects estimated by the L-band SMOS satellite
Language
en
Autre communication scientifique (congrès sans actes - poster - séminaire...)
This item was published in
MicroRad 2016 - 14. Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment, 2016-04-11, Espoo. 2016, vol. 4, p. communication orale
Aalto University
English Abstract
The Soil Moisture and Ocean Salinity (SMOS) mission is the first satellite dedicated to providing global surface soil moisture (SM). SMOS operates at L-band (1.4 GHz) and at this frequency, the signal depends on soil ...Read more >
The Soil Moisture and Ocean Salinity (SMOS) mission is the first satellite dedicated to providing global surface soil moisture (SM). SMOS operates at L-band (1.4 GHz) and at this frequency, the signal depends on soil moisture and vegetation optical depth but it is also significantly affected by surface effects and in particular by the soil roughness. However, when dense vegetation is present, the L-band signal is poorly sensitive to the soil effects. First, by using multiple regressions between soil moisture (SM) and brightness temperature (TB) at different incidence angles and polarizations, SMOS sensitivity to the soil effects are evaluated. A global-scale map of SMOS sensitivity to the soil effects is computed and shows that for 87\% of the land surfaces, the SMOS observations are sensitive to the soil effects, while a very low sensitivity to the soil effects was estimated over ~ 13% of the land surfaces. For instance, over broadleaf evergreen forest (essentially the Amazon and Congo forest), SMOS is sensitive to the soil effects for only half of the pixels considered. In a second step, in L-MEB (L-band Microwave Emission of the Biosphere), the forward emission model of the SMOS algorithm , the vegetation and roughness effects were combined in only one parameter referred to as TR in this study. By inverting L-MEB, SM and TR were retrieved at global scale from the SMOS Level 3 (L3) TB observations during 2011. Assuming a linear relationship between TR and LAI obtained by the MODIS data, the effects of roughness and vegetation were decoupled and a global map of soil roughness effects (Hr) was estimated. It was found that the spatial pattern of the Hr values can be associated to the main vegetation types. Higher values of roughness (Hr=0.37-0.41) were obtained for forests (broadleaf evergreen, deciduous and mixed coniferous) while the lower values (Hr=0.15-0.17) were obtained for deserts, shrubs and bare soil. Intermediate values (Hr=0.15-0.20) were obtained over grasslands, tundra and cultivations Over vegetation biomes composed by forests and wooded grasslands, Hr values are mainly correlated to the vegetation density (R ~ 0.55). For deserts, shrubs and bare soil, the Hr values were mainly correlated to the topography slopes (R ~ 0.53). The global maps presented in this study, could lead to improved retrievals of soil moisture and vegetation optical depth for present, such as SMOS and the Soil Moisture Active Passive (SMAP), and future microwave remote sensing missions .Read less <
Keywords
capteur smos
télédétection
donnée satellite
analyse de données
rugosité du sol
English Keywords
soil moisture and ocean salinity
remote sensing
data analysis
Origin
Hal imported