15 October 2009 Integrating models to predict the reason of unknown-caused grassland fire based on GIS
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Proceedings Volume 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining; 749242 (2009) https://doi.org/10.1117/12.838567
Event: International Symposium on Spatial Analysis, Spatial-temporal Data Modeling, and Data Mining, 2009, Wuhan, China
Abstract
This study predicts the reason of unknown-caused fires that occurred in grassland in the east of Inner Mongolia, China. GIS and logistic regression are used to build the predicting models. The causes of grassland fires were classified as vehicle, production, living and lighting. The areas were divided into fired and unfired grid cells (500m*500m) with spatial analysis, in order to determine the spatial factors and weather factors, such as the nearest distance to villages, roads, fields etc. Logistic regression was used to build predictive models of the probability for each reason of grassland fires. Four probabilities of each unknown-caused grassland fire were calculated and the maximum value expresses the fire reason. The results show that natural fires are less than human-caused grassland fires and they can be used in fire risk models and to support fire management decision-making. These methods would take advantage to the other grassland fire studies, such as fire ecology, fire weather, fire cycle, etc.
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Zhengxiang Zhang, Zhengxiang Zhang, Guanglei Hou, Guanglei Hou, Hongyan Zhang, Hongyan Zhang, Daowei Zhou, Daowei Zhou, } "Integrating models to predict the reason of unknown-caused grassland fire based on GIS", Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 749242 (15 October 2009); doi: 10.1117/12.838567; https://doi.org/10.1117/12.838567
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