TY - JOUR
T1 - Soil moisture retrieval from time series multi-angular radar data using a dry down constraint
AU - Zhu, Liujun
AU - Walker, Jeffrey P.
AU - Tsang, Leung
AU - Huang, Huanting
AU - Ye, Nan
AU - Rüdiger, Christoph
PY - 2019/9/15
Y1 - 2019/9/15
N2 - Multi-angular and multi-temporal methods have been developed and accepted as two promising strategies for reliable soil moisture retrieval from radar data. However, the way to combine time series multi-angular data acquired from both descending and ascending orbits with different imaging modes (e.g., ScanSAR and Stripmap) remains unresolved. Consequently, a multi-temporal algorithm is proposed for soil moisture retrieval at the pixel – paddock scale (25–500 m) using time series multi-angular L-band (1.26 GHz) radar data. The method assumes time-invariant roughness and vegetation for the retrieval period together with a soil moisture dry-down constraint for noise reduction, while utilizing multi-angular data without incidence angle normalization. The Numerical Maxwell Model of Three-Dimensional simulations and distorted Born approximation (NMM3D-DBA) were used to build a set of landcover specific multi-angular look up tables (LUTs). Effective isotropic roughness values were assumed suitably able to account for the periodic features in cultivated surfaces, with values determined as part of the soil moisture retrieval. A genetic algorithm was used to minimize the difference between LUTs and time series multi-angular radar observations with the dry-down constraint. Evaluation based on the Fifth Soil Moisture Active Passive Experiment dataset (SMAPEx-5) has shown an acceptable overall root mean square error (RMSE) of 0.070 m3/m3 at the 25-m pixel scale and 0.056 m3/m3 at the paddock (field) scale (~0.1–0.5 km). Further investigations on the effect of polarization combination and time interval of radar data have confirmed the effectiveness of the proposed method for irregularly collected data with different imaging modes.
AB - Multi-angular and multi-temporal methods have been developed and accepted as two promising strategies for reliable soil moisture retrieval from radar data. However, the way to combine time series multi-angular data acquired from both descending and ascending orbits with different imaging modes (e.g., ScanSAR and Stripmap) remains unresolved. Consequently, a multi-temporal algorithm is proposed for soil moisture retrieval at the pixel – paddock scale (25–500 m) using time series multi-angular L-band (1.26 GHz) radar data. The method assumes time-invariant roughness and vegetation for the retrieval period together with a soil moisture dry-down constraint for noise reduction, while utilizing multi-angular data without incidence angle normalization. The Numerical Maxwell Model of Three-Dimensional simulations and distorted Born approximation (NMM3D-DBA) were used to build a set of landcover specific multi-angular look up tables (LUTs). Effective isotropic roughness values were assumed suitably able to account for the periodic features in cultivated surfaces, with values determined as part of the soil moisture retrieval. A genetic algorithm was used to minimize the difference between LUTs and time series multi-angular radar observations with the dry-down constraint. Evaluation based on the Fifth Soil Moisture Active Passive Experiment dataset (SMAPEx-5) has shown an acceptable overall root mean square error (RMSE) of 0.070 m3/m3 at the 25-m pixel scale and 0.056 m3/m3 at the paddock (field) scale (~0.1–0.5 km). Further investigations on the effect of polarization combination and time interval of radar data have confirmed the effectiveness of the proposed method for irregularly collected data with different imaging modes.
KW - Multi-angular
KW - Multi-temporal
KW - Soil moisture
KW - Synthetic aperture radar
UR - http://www.scopus.com/inward/record.url?scp=85066958023&partnerID=8YFLogxK
U2 - 10.1016/j.rse.2019.111237
DO - 10.1016/j.rse.2019.111237
M3 - Article
AN - SCOPUS:85066958023
VL - 231
JO - Remote Sensing of Environment
JF - Remote Sensing of Environment
SN - 0034-4257
M1 - 111237
ER -