Spatial temporal clustering for hotspot using kulldorff scan statistic method (KSS): A case in Riau Province

3rd International Symposium on LAPAN-IPB Satellite For Food Security and Environmental Monitoring 2016

地球科学;轻工业;生态环境科学

Hudjimartsu, S.A.^1 ; Djatna, T.^2 ; Ambarwari, A.^1 ; Apriliantono^1

Department of Computer Science, Faculty of Math and Natural Sciences, Kampus IPB, Jl. Meranti Wing 20, Babakan, Dramaga, Jawa Barat, Bogor, Indonesia^1

Department Agroindustrial Technology, Faculty of Agricultural Technology, Kampus IPB, Gedung Fateta lt.2, Bogor, Dramaga, Jawa Barat, Indonesia^2

关键词: Early indicators;    Human activities;    Initial information;    Pollution hazards;    Scan statistics;    Spatial temporals;    Temporal dimensions;    Warning informations;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/54/1/012056/pdf
DOI  :  10.1088/1755-1315/54/1/012056

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

The forest fires in Indonesia occurs frequently in the dry season. Almost all the causes of forest fires are caused by the human activity itself. The impact of forest fires is the loss of biodiversity, pollution hazard and harm the economy of surrounding communities. To prevent fires required the method, one of them with spatial temporal clustering. Spatial temporal clustering formed grouping data so that the results of these groupings can be used as initial information on fire prevention. To analyze the fires, used hotspot data as early indicator of fire spot. Hotspot data consists of spatial and temporal dimensions can be processed using the Spatial Temporal Clustering with Kulldorff Scan Statistic (KSS). The result of this research is to the effectiveness of KSS method to cluster spatial hotspot in a case within Riau Province and produces two types of clusters, most cluster and secondary cluster. This cluster can be used as an early fire warning information.