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http://dx.doi.org/10.11108/kagis.2022.25.4.001

Comparison and Analysis of Drought Index based on MODIS Satellite Images and ASOS Data for Gyeonggi-Do  

Yu-Jin, KANG (Department of Civil Engineering, Inha University)
Hung-Soo, KIM (Department of Civil Engineering, Inha University)
Dong-Hyun, KIM (Department of Civil Engineering, Inha University)
Won-Joon, WANG (Department of Civil Engineering, Inha University)
Han-Eul, LEE (Department of Civil Engineering, Inha University)
Min-Ho, SEO (Geospatial Research Center, GEO C&I., Co., Ltd.)
Yun-Jae, CHOUNG (Geospatial Research Center, GEO C&I., Co., Ltd.)
Publication Information
Journal of the Korean Association of Geographic Information Studies / v.25, no.4, 2022 , pp. 1-18 More about this Journal
Abstract
Currently, the Korea Meteorological Administration evaluates the meteorological drought by region using SPI6(standardized precipitation index 6), which is a 6-month cumulative precipitation standard. However, SPI is an index calculated only in consideration of precipitation at 69 weather stations, and the drought phenomenon that appears for complex reasons cannot be accurately determined. Therefore, the purpose of this study is to calculate and compare SPI considering only precipitation and SDCI (Scaled Drought Condition Index) considering precipitation, vegetation index, and temperature in Gyeonggi. In addition, the advantages and disadvantages of the station data-based drought index and the satellite image-based drought index were identified by using results calculated through the comparison of SPI and SDCI. MODIS(MODerate resolution Imaging Spectroradiometer) satellite image data, ASOS(Automated Synoptic Observing System) data, and kriging were used to calculate SDCI. For the duration of precipitation, SDCI1, SDCI3, and SDCI6 were calculated by applying 1-month, 3-month, and 6-month respectively to the 8 points in 2014. As a result of calculating the SDCI, unlike the SPI, drought patterns began to appear about 2-month ago, and drought by city and county in Gyeonggi was well revealed. Through this, it was found that the combination of satellite image data and station data increased efficiency in the pattern of drought index change, and increased the possibility of drought prediction in wet areas along with existing dry areas.
Keywords
Meteorological Drought; Standardized Precipitation Index; Scaled Drought Condition Index; MODIS Satellite Images; ASOS Data;
Citations & Related Records
Times Cited By KSCI : 12  (Citation Analysis)
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