TY - JOUR
T1 - An advanced change detection method for time-series soil moisture retrieval from Sentinel-1
AU - Zhu, Liujun
AU - Si, Rui
AU - Shen, Xiaoji
AU - Walker, Jeffrey P.
N1 - Funding Information:
Liujun Zhu reports financial support was provided by Hohai Unversity.
Funding Information:
This work was supported by the National Natural Science Foundation of China ( 42101374 and 52121006 ), the Fundamental Research Funds for the Central Universities ( B220201009 ) and the Basic Research Project of Jiangsu Province ( BK20210377 ). The SMAPEx-5 field campaign was supported by an Australian Research Council Discovery Project ( DP140100572 ). The authors express sincere thanks to the data providers and the International Soil Moisture Network for the network data listed in Table 1 . Finally, the authors are grateful to the Reviewers for their valuable comments which helped to improve the quality of this paper.
Publisher Copyright:
© 2022 Elsevier Inc.
PY - 2022/9/15
Y1 - 2022/9/15
N2 - The feasibility of soil moisture retrieval from C-band Sentinel-1 data has been widely acknowledged, with pre-operational 1-km products currently available at regional and/or continental scale using the long-term (LTCD) or short-term change detection (STCD) methods. Both algorithms share the same assumptions of time-invariant roughness and vegetation, which can be questionable even for a short period of 4 Sentinel-1 acquisitions (18–36 days). An advanced change detection (ACD) method is proposed in this study for an improved soil moisture retrieval from Sentinel-1 data, including two main modifications with respect to the existing STCD methods: i) approximating the effect of temporal varying vegetation on the Sentinel-1 backscatter as a variation in the two-way attenuation, and ii) a temporal soil moisture constraint based on the coarse Soil Moisture Active Passive (SMAP) soil moisture product to partly remove the uncertainty caused by vegetation and/or roughness changes. The evaluation, based on time-series observations from 34 OzNet stations and ground samples collected during the Fifth Soil Moisture Active and Passive Experiment (SMAPEx-5) showed that the ACD improved the correlation coefficient (R), root mean square error (RMSE) and un biased RMSE (ubRMSE), achieving 0.66, 0.071 m3/m3 and 0.071 m3/m3 at the point scale, 0.77, 0.063 m3/m3 and 0.051 m3/m3 at 1-km scale, 0.80, 0.055 m3/m3 and 0.050 m3/m3 at 3-km scale. The contribution of the two modifications was further investigated using 559 stations from 22 networks across the world, showing that: i) the two modifications can increase R by 0.08–0.13 and reduce the retrieval RMSE by 0.009–0.013 m3/m3 (10% - 15% relative), and ii) the retrieval over densely vegetated areas or areas with large temporal vegetation variation can benefit more from the proposed modifications. The ACD achieved stable performance for various Sentinel-1 orbits/passes and maintained a stable performance for retrieval windows up to 30 Sentinel-1 acquisitions, providing a promising alternative for achieving consistent soil moisture retrievals from Sentinel-1.
AB - The feasibility of soil moisture retrieval from C-band Sentinel-1 data has been widely acknowledged, with pre-operational 1-km products currently available at regional and/or continental scale using the long-term (LTCD) or short-term change detection (STCD) methods. Both algorithms share the same assumptions of time-invariant roughness and vegetation, which can be questionable even for a short period of 4 Sentinel-1 acquisitions (18–36 days). An advanced change detection (ACD) method is proposed in this study for an improved soil moisture retrieval from Sentinel-1 data, including two main modifications with respect to the existing STCD methods: i) approximating the effect of temporal varying vegetation on the Sentinel-1 backscatter as a variation in the two-way attenuation, and ii) a temporal soil moisture constraint based on the coarse Soil Moisture Active Passive (SMAP) soil moisture product to partly remove the uncertainty caused by vegetation and/or roughness changes. The evaluation, based on time-series observations from 34 OzNet stations and ground samples collected during the Fifth Soil Moisture Active and Passive Experiment (SMAPEx-5) showed that the ACD improved the correlation coefficient (R), root mean square error (RMSE) and un biased RMSE (ubRMSE), achieving 0.66, 0.071 m3/m3 and 0.071 m3/m3 at the point scale, 0.77, 0.063 m3/m3 and 0.051 m3/m3 at 1-km scale, 0.80, 0.055 m3/m3 and 0.050 m3/m3 at 3-km scale. The contribution of the two modifications was further investigated using 559 stations from 22 networks across the world, showing that: i) the two modifications can increase R by 0.08–0.13 and reduce the retrieval RMSE by 0.009–0.013 m3/m3 (10% - 15% relative), and ii) the retrieval over densely vegetated areas or areas with large temporal vegetation variation can benefit more from the proposed modifications. The ACD achieved stable performance for various Sentinel-1 orbits/passes and maintained a stable performance for retrieval windows up to 30 Sentinel-1 acquisitions, providing a promising alternative for achieving consistent soil moisture retrievals from Sentinel-1.
KW - Change detection
KW - High resolution
KW - Sentinel-1
KW - Soil moisture
KW - Synthetic aperture radar (SAR)
UR - http://www.scopus.com/inward/record.url?scp=85133726388&partnerID=8YFLogxK
U2 - 10.1016/j.rse.2022.113137
DO - 10.1016/j.rse.2022.113137
M3 - Article
AN - SCOPUS:85133726388
SN - 0034-4257
VL - 279
JO - Remote Sensing of Environment
JF - Remote Sensing of Environment
M1 - 113137
ER -