A. Rifa’i, Ragil Andika Yuniawan, F. Faris, Andy Subiyantoro, Vilman Sidik, Hadi Prayoga
{"title":"降雨卫星阈值在吉陵驿地区滑坡事件预测中的应用","authors":"A. Rifa’i, Ragil Andika Yuniawan, F. Faris, Andy Subiyantoro, Vilman Sidik, Hadi Prayoga","doi":"10.1109/ICARES56907.2022.9993592","DOIUrl":null,"url":null,"abstract":"Landslides often occur in Indonesia, especially in the mountainous areas where there are many steep slopes. Conversely, disaster mitigation in mountainous areas also receives less priority than in urban areas. To overcome this problem, an effective and efficient disaster mitigation effort requires in mountainous areas without spending much money. This study aims to calculate the threshold value of rainfall that triggers landslides using satellite data in the mountainous area. This information is expected to be a mitigation effort against landslides in mountainous locations. This study took the place of the administrative boundary of the Girimulyo district. Rainfall data using GPM satellite compared with the local ground station. A total of 50 landslide events that occurred in the Girimulyo district from 2017–2021 were used as inventory for analysis in this study. Information on landslide events was obtained from the local government and validated through field investigation. The result shows that rainfall data from satellite and local ground station show a good correlation with the landslide events, proved by AUC values 0.893 and 0.761, respectively. However, in further statistical analysis, the rainfall threshold derived from satellite data outperformed the rainfall threshold derived from the local ground station.","PeriodicalId":252801,"journal":{"name":"2022 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology (ICARES)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Performance of rainfall satellite threshold to predict landslide events in Girimulyo District\",\"authors\":\"A. Rifa’i, Ragil Andika Yuniawan, F. Faris, Andy Subiyantoro, Vilman Sidik, Hadi Prayoga\",\"doi\":\"10.1109/ICARES56907.2022.9993592\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Landslides often occur in Indonesia, especially in the mountainous areas where there are many steep slopes. Conversely, disaster mitigation in mountainous areas also receives less priority than in urban areas. To overcome this problem, an effective and efficient disaster mitigation effort requires in mountainous areas without spending much money. This study aims to calculate the threshold value of rainfall that triggers landslides using satellite data in the mountainous area. This information is expected to be a mitigation effort against landslides in mountainous locations. This study took the place of the administrative boundary of the Girimulyo district. Rainfall data using GPM satellite compared with the local ground station. A total of 50 landslide events that occurred in the Girimulyo district from 2017–2021 were used as inventory for analysis in this study. Information on landslide events was obtained from the local government and validated through field investigation. The result shows that rainfall data from satellite and local ground station show a good correlation with the landslide events, proved by AUC values 0.893 and 0.761, respectively. However, in further statistical analysis, the rainfall threshold derived from satellite data outperformed the rainfall threshold derived from the local ground station.\",\"PeriodicalId\":252801,\"journal\":{\"name\":\"2022 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology (ICARES)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology (ICARES)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICARES56907.2022.9993592\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology (ICARES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICARES56907.2022.9993592","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Performance of rainfall satellite threshold to predict landslide events in Girimulyo District
Landslides often occur in Indonesia, especially in the mountainous areas where there are many steep slopes. Conversely, disaster mitigation in mountainous areas also receives less priority than in urban areas. To overcome this problem, an effective and efficient disaster mitigation effort requires in mountainous areas without spending much money. This study aims to calculate the threshold value of rainfall that triggers landslides using satellite data in the mountainous area. This information is expected to be a mitigation effort against landslides in mountainous locations. This study took the place of the administrative boundary of the Girimulyo district. Rainfall data using GPM satellite compared with the local ground station. A total of 50 landslide events that occurred in the Girimulyo district from 2017–2021 were used as inventory for analysis in this study. Information on landslide events was obtained from the local government and validated through field investigation. The result shows that rainfall data from satellite and local ground station show a good correlation with the landslide events, proved by AUC values 0.893 and 0.761, respectively. However, in further statistical analysis, the rainfall threshold derived from satellite data outperformed the rainfall threshold derived from the local ground station.