{"title":"Hubungan Dual Polametric SAR Band – C dan Landsat 8 untuk Identifikasi Potensi Kekeringan","authors":"Hikmah Fajar Assidiq, Catur Aries Rokhmana","doi":"10.12962/J24423998.V16I2.8581","DOIUrl":null,"url":null,"abstract":"Drought is a disastrous and complex disaster that can cause material and immaterial losses. The drought in Indonesia is categorized by several types including Agricultural Drought, Meteorological Drought, and Hydrological Drought. Agricultural drought is a condition where there is a decrease in water content in the soil. These conditions will have an impact on vegetation and / or land cover so preventive action is needed. Preventive action is carried out quickly, effectively and efficiently so that an approach with a dynamic pattern is needed. The dynamic pattern approach is done by a method that can be done any time. The use of Active Sensor remote sensing can perform monitoring at any time and dynamically. One of the satellites with radar sensors is Sentinel 1A. Sentinel 1A has a C band wave. Polarization in the Sentinel-1 image has a dual-pol form consisting of VV and VH or HH and HV. The Polarization combination has the potential to measure drought. The method that can be used is the Vegetation Radar Index. The radar vegetation index is developed from the NDVI algorithm. The RVI Drought Classification is made by maintaining the relationship between the NDVI Landsat 8 results and the RVI results. This study aims to examine the use of SAR data for drought identification with the relationship between Dual Polametric SAR Band C and Landsat 8. The results explain that NDVI has a coefficient of determination with an RVI of 0.2981 Kata kunci: kekeringan; RVI; Sentinel 1A Cara untuk sitasi: Assidiq, H.F., & Rokhmana, C.A. (2021). Hubungan Dual Polametric SAR Band – C dan Landsat 8 untuk Identifikasi Potensi Kekeringan. Geoid, 16(2), 248 258.","PeriodicalId":30776,"journal":{"name":"Geoid","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geoid","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12962/J24423998.V16I2.8581","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Drought is a disastrous and complex disaster that can cause material and immaterial losses. The drought in Indonesia is categorized by several types including Agricultural Drought, Meteorological Drought, and Hydrological Drought. Agricultural drought is a condition where there is a decrease in water content in the soil. These conditions will have an impact on vegetation and / or land cover so preventive action is needed. Preventive action is carried out quickly, effectively and efficiently so that an approach with a dynamic pattern is needed. The dynamic pattern approach is done by a method that can be done any time. The use of Active Sensor remote sensing can perform monitoring at any time and dynamically. One of the satellites with radar sensors is Sentinel 1A. Sentinel 1A has a C band wave. Polarization in the Sentinel-1 image has a dual-pol form consisting of VV and VH or HH and HV. The Polarization combination has the potential to measure drought. The method that can be used is the Vegetation Radar Index. The radar vegetation index is developed from the NDVI algorithm. The RVI Drought Classification is made by maintaining the relationship between the NDVI Landsat 8 results and the RVI results. This study aims to examine the use of SAR data for drought identification with the relationship between Dual Polametric SAR Band C and Landsat 8. The results explain that NDVI has a coefficient of determination with an RVI of 0.2981 Kata kunci: kekeringan; RVI; Sentinel 1A Cara untuk sitasi: Assidiq, H.F., & Rokhmana, C.A. (2021). Hubungan Dual Polametric SAR Band – C dan Landsat 8 untuk Identifikasi Potensi Kekeringan. Geoid, 16(2), 248 258.