Herlawati Herlawati, Fata Nidaul Khasanah, Prima Dina Atika, Rafika Sari, Rahmadya Trias Handayanto
{"title":"Prediksi Perubahan Penggunaan Lahan dan Pola Berdasarkan Citra Landsat Multi Waktu dengan Land Change Modeler (LCM)","authors":"Herlawati Herlawati, Fata Nidaul Khasanah, Prima Dina Atika, Rafika Sari, Rahmadya Trias Handayanto","doi":"10.31603/komtika.v5i1.5139","DOIUrl":null,"url":null,"abstract":"Land use/cover greatly affect the quality of an area. Therefore, many regional planners need assistance byother fields, such as geoinformatics, computer science, environment, and others. Although prediction and forecasting have been widely studied, in regardto real conditions (geospatial)itstill needmoredevelopment, especially thoseinvolving a combination of regional types, such as urban and suburban areas. This study uses a remote sensing base and geographic information system in predicting land in the city and district of Bekasi, West Java, Indonesia. With two scenarios compared (business as usual and vegetation conservation), the model that has been created and validated (with an AUC accuracy result of 0.828) is used to predict land use change until 2030. Scenarios with vegetation conservation are able to keep green areas to switch to land types others, such as buildings and industry","PeriodicalId":292404,"journal":{"name":"Jurnal Komtika (Komputasi dan Informatika)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Komtika (Komputasi dan Informatika)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31603/komtika.v5i1.5139","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Land use/cover greatly affect the quality of an area. Therefore, many regional planners need assistance byother fields, such as geoinformatics, computer science, environment, and others. Although prediction and forecasting have been widely studied, in regardto real conditions (geospatial)itstill needmoredevelopment, especially thoseinvolving a combination of regional types, such as urban and suburban areas. This study uses a remote sensing base and geographic information system in predicting land in the city and district of Bekasi, West Java, Indonesia. With two scenarios compared (business as usual and vegetation conservation), the model that has been created and validated (with an AUC accuracy result of 0.828) is used to predict land use change until 2030. Scenarios with vegetation conservation are able to keep green areas to switch to land types others, such as buildings and industry