Estimation of soil moisture using remote sensing and its evaluation with field data (Case study of Hormoz Abad Plain)

and water management in the field. Therefore, its measurement has special importance. The surface soil has a great diversity in soil moisture and different methods were used to measure this property. Due to the problems of contact methods of soil moisture measurement, remote sensing has gained attention because of the possibility of analyzing and monitoring soil moisture on a large and global scale. In this research, satellite data and moisture measured in selected fields located in Hormoaz Abad Plain have been analyzed and compared. Sentinel-2 satellite data have been analyzed using the Google Earth Engine system. The results of this research showed that the use of triple indices in the OPTRAM model to estimate moisture is not very accurate, but the use of the EVI plant index has provided better results than the other two indices.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-10-01
Primary Topic
Soil Moisture and Remote Sensing
Type
article
Field-Weighted Citation Impact
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article

Estimation of soil moisture using remote sensing and its evaluation with field data (Case study of Hormoz Abad Plain)

SHILAP Revista de lepidopterología
Soil Moisture and Remote Sensing
article

Estimation of soil moisture using remote sensing and its evaluation with field data (Case study of Hormoz Abad Plain)

article en

Abstract

and water management in the field. Therefore, its measurement has special importance. The surface soil has a great diversity in soil moisture and different methods were used to measure this property. Due to the problems of contact methods of soil moisture measurement, remote sensing has gained attention because of the possibility of analyzing and monitoring soil moisture on a large and global scale. In this research, satellite data and moisture measured in selected fields located in Hormoaz Abad Plain have been analyzed and compared. Sentinel-2 satellite data have been analyzed using the Google Earth Engine system. The results of this research showed that the use of triple indices in the OPTRAM model to estimate moisture is not very accurate, but the use of the EVI plant index has provided better results than the other two indices.

SHILAP Revista de lepidopterología
Isfahan University of Technology (IR)
Clean water and sanitation
Openalex Percentile: Top 62%
Soil Moisture and Remote Sensing
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