Evaluation of Fire Ignition Probability Model by Using Spatial Autocorrelation Method: A Case Study in Yunnan Province

Abstract

Abstract:The forests in Yunnan province are dense and precious. Meanwhile, the forests fire happens frequently. There are ten models generated with two modeling methods in the study area, Yunnan province. In this paper, the spatial autocorrelation method was applied to analyze and evaluate the performance of fire ignition probability models. The results show that: 1) the models generated by geography weight logistic regression method are better than the ones created by binary logistic regression method; 2) compared with other models, the Model 7 is optimal in terms of evaluating by the quantitative spatial autocorrelation method. The results are of significance for making decisions of establishing early warning systems.

Spatial Pattern and Hotspots of Urban Rail Public Transport to Public Access Using Geospatial Techniques in Selangor, Malaysia

“…Spatial autocorrelation statistics are used in Clusters, randomness, or spatial pattern dispersal (Brianna et al, 2020). Wubuli et al, mentioned that spatial autocorrelation divided into two conditions, which are local and global spatial autocorrelation (Wubuli et al, 2015;Wang et al, 2017). The global spatial autocorrelation calculates the total degree of spatial autocorrelation for a dataset.…”

“…The global spatial autocorrelation calculates the total degree of spatial autocorrelation for a dataset. The local autocorrelation uses the location and types of clusters (Wang et al, 2017).…”