Contribution assessment and prediction of impact of human activity on Hulunbeier grassland fire risk based on weights of evidence

摘要

In this paper, Weights of Evidence is used to explore the effect of human activity on the grassland fire risk. Combined with the collected information of Hulunbeier grassland fires, select 5 factors which is related to human activities, with the support of ARCGIS and ARCVIEW software, analyze quantitatively the relationship between each factor and the spatial distribution of grassland fire points. Thus, a thematic prediction map can be generated by the WofE extension in ARCVIEW, and divided into high, middle and low risk areas, and then a fire point prediction model is established. The result of model testing shows to be effective. Thus, it proves that weights of evidence can indicate the relationship between grassland fires and human activity objectively and quantitatively, so it can provide decision support for grassland fire risk management and avoiding.