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Sensitivity of TDS-1 GNSS-R Reflectivity to Soil Moisture: Global and Regional Differences and Impact of Different Spatial Scales

CommSensLab, Unidad de Excelencia María de Maeztu, Department of Signal Theory and Communications, Universitat Politècnica de Catalunya, E-08034 Barcelona, Spain
Institut d’Estudis Espacial de Catalunya/Centre de Tecnologies Espacials-Universitat Politècnica de Catalunya, UPC Campus Nord, E-08034 Barcelona, Spain
Castelldefels School of Telecommunications and Aerospace Engineering, UPC-BarcelonaTech, UPC Campus Baix Llobregat, E-08860 Castelldefels, Spain
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(11), 1856;
Received: 1 October 2018 / Revised: 11 November 2018 / Accepted: 15 November 2018 / Published: 21 November 2018
(This article belongs to the Special Issue Soil Moisture Retrieval using Radar Remote Sensing Sensors)
The potential of Global Navigation Satellite Systems-Reflectometry (GNSS-R) techniques to estimate land surface parameters such as soil moisture (SM) is experimentally studied using 2014–2017 global data from the UK TechDemoSat-1 (TDS-1) mission. The approach is based on the analysis of the sensitivity to SM of different observables extracted from the Delay Doppler Maps (DDM) computed by the Space GNSS Receiver–Remote Sensing Instrument (SGR-ReSI) instrument using the L1 (1575.42 MHz) left-hand circularly-polarized (LHCP) reflected signals emitted by the Global Positioning System (GPS) navigation satellites. The sensitivity of different GNSS-R observables to SM and its dependence on the incidence angle is analyzed. It is found that the sensitivity of the calibrated GNSS-R reflectivity to surface soil moisture is ~0.09 dB/% up to 30° incidence angle, and it decreases with increasing incidence angles, although differences are found depending on the spatial scale used for the ground-truth, and the region. The sensitivity to subsurface soil moisture has been also analyzed using a network of subsurface probes and hydrological models, apparently showing some dependence, but so far results are not conclusive. View Full-Text
Keywords: soil moisture; GNSS-R; satellite; hydrology; model; probe; sensitivity soil moisture; GNSS-R; satellite; hydrology; model; probe; sensitivity
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MDPI and ACS Style

Camps, A.; Vall·llossera, M.; Park, H.; Portal, G.; Rossato, L. Sensitivity of TDS-1 GNSS-R Reflectivity to Soil Moisture: Global and Regional Differences and Impact of Different Spatial Scales. Remote Sens. 2018, 10, 1856.

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