0000000000863109
AUTHOR
Zanping Xing
showing 3 related works from this author
Global Long-Term Brightness Temperature Record from L-Band SMOS and Smap Observations
2021
Passive microwave remote sensing observations at L-band provide key and global information on surface soil moisture (SM) and vegetation optical depth (VOD), which are related to the Earth water and carbon cycles. Only two spaceborne L-band sensors are currently operating: SMOS, launched end of 2009 and thus providing now a 11-year global dataset and SMAP, launched beginning of 2015. To ensure SM and L-VOD data continuity in the event of failure of one of the space-borne SMOS or SMAP sensors, we developed a consistent brightness temperature (TB) record by first producing consistent 40° SMOS and SMAP TB estimates based on SMOS-IC and SMAP enhanced data resp., and then fusing them via linear f…
Alternate Inrae-Bordeaux VOD Indices from SMOS, AMSR2 and ASCAT: Overview of Recent Developments
2021
International audience; Vegetation optical depth (VOD) is used to parameterize microwave extinction effects within the vegetation layer. Many studies have showed VOD presents interesting features for applications in ecology, water and carbon cycles, and VOD is only marginally impacted by signal disturbances and artefacts from atmospheric, cloud and sun illumination effects. As soil moisture (and not VOD) has generally been the main factor of interest in retrieval studies from microwave observations, there is room for improvement in the retrieved VOD products. In this context, INRAE Bordeaux recently developed alternate VOD products from the SMOS, AMSR2 and ASCAT sensors, by addressing speci…
Interannual Variability of Biomass (SMOS Vegetation Optical Depth) Over the Contiguous United States
2021
Interannual variability in biomass represented by SMOS vegetation optical depth (VOD) and precipitation was assessed over the Contiguous United States. The greatest interannual variability in both VOD and precipitation occurred in shrubs and herbaceous (grasslands), with forests the least variable. At a continental scale, VOD was strongly correlated with annual precipitation. Results showed a significant correlation coefficient (∼ 0.93) between interannual variability of precipitation and biomass, indicating that the interannual variability of precipitation could be a good predictor of the interannual variability of biomass.