Firdaus, Septriani, Alsella Meiriza, R. F. Malik, S. Nurmaini
{"title":"Spatio-temporal analysis of South Sumatera hotspot distribution","authors":"Firdaus, Septriani, Alsella Meiriza, R. F. Malik, S. Nurmaini","doi":"10.1109/ICECOS.2017.8167133","DOIUrl":null,"url":null,"abstract":"This paper presents the analysis of South Sumatera hotspots distribution pattern from 2005–2015 based on spatial and temporal aspects. The hotspot distribution data used is FIRMS MODIS Fires data. The spatial aspect is represented by the attribute of latitude and longitude as the location of the occurrence of hotspots and the temporal is represented by the date attribute. DBSCAN clustering is used to analyze spatial aspect. The results show that Tulung Selapan subdistrict is on high fire-prone region. Air Sugihan, Cengal, Bayung Lencir is on medium and the others is low. For temporal aspect, the result shows most hotspots occurred on August, September and October.","PeriodicalId":6528,"journal":{"name":"2017 International Conference on Electrical Engineering and Computer Science (ICECOS)","volume":"17 1","pages":"198-201"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Electrical Engineering and Computer Science (ICECOS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECOS.2017.8167133","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
This paper presents the analysis of South Sumatera hotspots distribution pattern from 2005–2015 based on spatial and temporal aspects. The hotspot distribution data used is FIRMS MODIS Fires data. The spatial aspect is represented by the attribute of latitude and longitude as the location of the occurrence of hotspots and the temporal is represented by the date attribute. DBSCAN clustering is used to analyze spatial aspect. The results show that Tulung Selapan subdistrict is on high fire-prone region. Air Sugihan, Cengal, Bayung Lencir is on medium and the others is low. For temporal aspect, the result shows most hotspots occurred on August, September and October.
本文从时空角度分析了2005-2015年南苏门答腊热点地区的分布格局。使用的热点分布数据是FIRMS MODIS Fires数据。空间方面用纬度和经度属性表示为热点发生的位置,时间方面用日期属性表示。使用DBSCAN聚类分析空间方面。结果表明,土隆西拉潘街道属于火灾高发区。苏吉汉航空公司、甘格尔航空公司、巴扬伦西尔航空公司处于中等水平,其他航空公司处于低水平。从时间上看,8月、9月和10月是热点地区。