Spatial co-location patterns on weather and forest fire data
Автор: Imas S. Sitanggang, Sergi Roseli, Lailan Syaufina
Журнал: International Journal of Information Technology and Computer Science @ijitcs
Статья в выпуске: 9 Vol. 10, 2018 года.
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One of problems that can increase the risk of forest fire occurrences in Indonesia is drought which is affected by weather conditions. Therefore, weather conditions and forest fire are strongly related. Spatial co-location pattern can be applied to identify the weather conditions that are vulnerable to fires based on the distance between weather observation points and hotspot occurrences. The purpose of this study is to apply the co-location miner algorithm on the weather and hotspot data in Rokan Hilir Riau Indonesia and to analyze the generated co-location patterns. Experimental results show that precipitation which co-located with hotspot occurrences are 0.08–6.69 mm/day. In addition, the temperature which co-located with hotspot occurrences are 22°C–29.17°C. Inside the intervals, hotspots will occur in the radius of 9.724 km from the precipitation and temperature observation points. In 2008, many hotspots were found on the three areas in the study area with the average of precipitation around 3.65–3.71 mm/day and temperature around 24.44°C–25.23°C.
Co-location pattern, forest and land fire, hotspot, Rokan Hilir, spatial data mining
Короткий адрес: https://sciup.org/15016293
IDR: 15016293 | DOI: 10.5815/ijitcs.2018.09.02
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