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RSS FeedsRemote Sensing, Vol. 13, Pages 3704: GIS-Based Forest Fire Risk Model: A Case Study in Laoshan National Forest Park, Nanjing (Remote Sensing)

 
 

16 september 2021 13:58:31

 
Remote Sensing, Vol. 13, Pages 3704: GIS-Based Forest Fire Risk Model: A Case Study in Laoshan National Forest Park, Nanjing (Remote Sensing)
 


Fire risk prediction is significant for fire prevention and fire resource allocation. Fire risk maps are effective methods for quantifying regional fire risk. Laoshan National Forest Park has many precious natural resources and tourist attractions, but there is no fire risk assessment model. This paper aims to construct the forest fire risk map for Nanjing Laoshan National Forest Park. The forest fire risk model is constructed by factors (altitude, aspect, topographic wetness index, slope, distance to roads and populated areas, normalized difference vegetation index, and temperature) which have a great influence on the probability of inducing fire in Laoshan. Since the importance of factors in different study areas is inconsistent, it is necessary to calculate the significance of each factor of Laoshan. After the significance calculation is completed, the fire risk model of Laoshan can be obtained. Then, the fire risk map can be plotted based on the model. This fire risk map can clarify the fire risk level of each part of the study area, with 16.97% extremely low risk, 48.32% low risk, 17.35% moderate risk, 12.74% high risk and 4.62% extremely high risk, and it is compared with the data of MODIS fire anomaly point. The result shows that the accuracy of the risk map is 76.65%.


 
58 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 13, Pages 3702: Reduced-Dynamic Precise Orbit Determination of Haiyang-2B Altimetry Satellite Using a Refined Empirical Acceleration Model (Remote Sensing)
Remote Sensing, Vol. 13, Pages 3703: ERTFM: An Effective Model to Fuse Chinese GF-1 and MODIS Reflectance Data for Terrestrial Latent Heat Flux Estimation (Remote Sensing)
 
 
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