Multi-scenario Satellite Drought Assessment using Moisture Stress Index (MSI) in Mae Suk Watershed, Mae Chai District, Phayao Province
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Creator Siriwan Ruenrom
Title Multi-scenario Satellite Drought Assessment using Moisture Stress Index (MSI) in Mae Suk Watershed, Mae Chai District, Phayao Province
Contributor Rangsan Ket-ord, Niti Iamchuen
Publisher School of Information and Communication Technology, University of Phayao
Publication Year 2567
Journal Title The Journal of Spatial Innovation Development
Journal Vol. 5
Journal No. 3
Page no. 93-105
Keyword Remote sensing, Land use, Moisture Stress Index, Phayao, Upper Ing watershed
URL Website https://ph01.tci-thaijo.org/index.php/jsid/index
Website title The Journal of Spatial Innovation Development
ISSN 2730-1494
Abstract Drought is a natural disaster that has persisted from the past to the present. It can occur in any area and is usually caused by changes in rainfallThe amount of rainfall decreases more than usual for an extended period, affecting agricultural production. Current drought conditions can be assessed using indices calculated through remote sensing techniques. The Moisture Stress Index (MSI) is used to analyze drought-prone areas and their impact on land use. In this research study, the aims are (1) to analyze areas at risk of drought under varying rainfall amounts and (2) to examine the relationship between drought risk areas and land use status. The research results indicate that drought areas (ranging from moderate to extreme drought) appear in all three landscapes, with 10,193 rai in low rainfall areas, 13,654 rai in normal rainfall areas, and 5,736 rai in high rainfall areas. When analyzing the MSI index values in conjunction with land use, it was found that various activities have different drought indices: agricultural areas (0.6 – 1.9), forest areas (0.4 – 1.4), miscellaneous areas (0.6 – 1.9), urban and built-up areas (0.6 – 1.4), and water resource areas (0.4 – 1.6). Studying the MSI index can indicate the drought level for each type of land use, which can be utilized in planning to support decision-making in agriculture based on the varying amounts of rainfall during different periods.
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