Thanh Binh Nguyen; Minh Hai Pham; Van Tuan Nguyen

doi:10.54491/jgac.2018.36.272

Original research | No. 36 (2018)

Mapping soil moisture using multi-temporal remote sensing data MODIS by NDVI/LST triangle method, pilot study for the Ca river basin

DOI: 10.54491/jgac.2018.36.272

10.54491/jgac.2018.36.272

Published 2018-06-01

Thanh Binh Nguyen⁺⁻
Minh Hai Pham⁺⁻
Van Tuan Nguyen⁺⁻

Thanh Binh Nguyen

Institute of Geography, Vietnam Academy of Science of Technology

Minh Hai Pham

Vietnam Institute of Geodesy and Cartography, Ministry of Natural Resources and Environment

Van Tuan Nguyen

Institute of Water Resources Planning, Ministry of Agriculture and Rural Development

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How to Cite

Nguyen, T. B., Pham, M. H., & Nguyen, V. T. (2018). Mapping soil moisture using multi-temporal remote sensing data MODIS by NDVI/LST triangle method, pilot study for the Ca river basin. Journal of Geodesy and Cartography, (36), 24–31. https://doi.org/10.54491/jgac.2018.36.272

Abstract

Surface parameters such as roughness or vegetation density are factors that prevent the widespread adoption of radar data in mapping soil moisture. Therefore, a suitable technique for estimating soil moisture without requiring information about the roughness of the soil surface and not limited to pixels with NDVI> 0.4 is necessary. This paper uses the relationship between surface temperature LST and NDVI calculated from MODIS data combined with field soil moisture data to estimate soil moisture for the Ca river basin. Initial results show that the soil moisture is estimated with correlation coefficient R2 > 70 and the root mean squared error RMSE is 0.045. This study shows that the estimation of soil moisture by combining field and parameters (LST, NDVI) extracted from MODIS data is accurate and effective can be used as an input for many hydrological models.

https://doi.org/10.54491/jgac.2018.36.272

PDF (Tiếng Việt) | Download: 135

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