Evaluation of soil surface moisture in Dak Nong province, Vietnam by Sentinel-1 radar image

  • Affiliations:

    Hanoi University of Mining and Geology, Hanoi, Vietnam

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  • Received: 20th-Jan-2023
  • Revised: 25th-May-2023
  • Accepted: 19th-June-2023
  • Online: 30th-June-2023
Pages: 51 - 58
Views: 1390
Downloads: 19
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Abstract:

This study focuses on monitoring the variation of surface soil moisture (0-1 cm) and ground soil moisture (0÷1 m) in the soil in Dak Nong province using Sentinel-1 radar images received in December 2017. Active radar signals utilized in this method were sent and received using short wave pulses. The intensity of the received signal is compared to determine the scattering coefficient of the surface. The most common imaging constructs of active shortwave are Synthetic Aperture Radar (SAR), which transmits a series of pulses that pass through a radar antenna. Soil moisture is calculated by measuring electromagnetic radiation in the wavelength range from 0,5÷100 cm based on the contrast between the dielectric properties of water (~80) and soil particles (<4). With increasing humidity, the dielectric constant of the water mixture increases, this change can be detected by radar sensors. The results of moisture estimation by satellite images are checked by the results of field sampling and laboratory analysis. Radar remote sensing technique has demonstrated the ability to estimate soil moisture on the principle of correlating with actual measured data. The return scattering value of the soil consists of two components: the former is the feedback scattering value of the raw soil; while the latter is the feedback scattering value of the vegetation cover. It is recommended that this technology should be applied to territories with complex, difficult-to-access terrains and few meteorological monitoring stations.

How to Cite
Vu, T.Phuong Thi, Nguyen, P.Quoc and Do, C.Cao 2023. Evaluation of soil surface moisture in Dak Nong province, Vietnam by Sentinel-1 radar image. Journal of Mining and Earth Sciences. 64, 3 (Jun, 2023), 51-58. DOI:https://doi.org/10.46326/JMES.2023.64(3).06.
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