An improved change detection method for high-resolution soil moisture mapping in permafrost regions

Soil moisture plays a crucial role in understanding the hydrological cycle and the ecological environment. This research presents an improved change detection method that leverages time series data from Sentinel-1 radar and Sentinel-2 optical sensors (2019–2021) to estimate surface soil moisture. Th...

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Detalhes bibliográficos
Autores: Du, SJ, Duan, P, Zhao, TJ, Wang, Z, Niu, SD, Ma, CF, Zou, DF, Yao, PP, Guo, P, Fan, D, Gao, Q, Zheng, JY, Peng, ZQ, Lü, HS, Shi, JC
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Recursos:Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
Repositorio:r-CTTC. Repositorio Institucional Producción Científica del Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
OAI Identifier:oai:cttc.fundanetsuite.com:p8343
Acesso em linha:https://cttc.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=8343
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184155100&doi=10.1080%2f15481603.2024.2310898&partnerID=40&md5=b9b7a54e9a038e94c13601d90cc6feba
Access Level:acceso abierto
Palavra-chave:China
Qinghai-Xizang Plateau
detection method
hydrological cycle
mapping
NDVI
permafrost
Sentinel
soil moisture
Descrição
Resumo:Soil moisture plays a crucial role in understanding the hydrological cycle and the ecological environment. This research presents an improved change detection method that leverages time series data from Sentinel-1 radar and Sentinel-2 optical sensors (2019–2021) to estimate surface soil moisture. The response of backscatter to soil moisture in bare soil was expressed in a logarithmic form, and the influence function of the normalized difference vegetation index (NDVI) on the backscatter difference was established for various vegetation-covered surfaces. Therefore, the impact of vegetation on backscatter is effectively mitigated, and the resulting change in backscatter relative to bare soil conditions can be obtained. An empirical function is subsequently formulated to ascertain the reference values of soil moisture in each pixel. The retrieval of soil moisture is demonstrated in the Wudaoliang permafrost region of the Qinghai-Tibet Plateau and validated against ground measurements. The retrieval results of the improved change detection method exhibit correlation coefficients ranging from 0.672 to 0.941, with root mean squared errors (RMSE) ranging from 0.031 (Formula presented.) to 0.073 (Formula presented.). Compared to the Soil Moisture Active Passive (SMAP) 9-km product, our new method demonstrates higher correlation (0.898 vs. 0.867) and lower RMSE (0.037 (Formula presented.) vs. 0.044 (Formula presented.)). The soil moisture retrieved from Sentinel shows a strong correlation with the SMAP 9-km soil moisture in the time series, thereby providing a better representation of the region’s soil moisture heterogeneity. Our method demonstrates the feasibility of combining Sentinel-1 and 2 for high-resolution (100 m) soil moisture mapping in permafrost regions. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.