Qinghai Province Natural Grassland Fire Prone Data Set

It is combined with historical precipitation data with a resolution of 1km in Qinghai Province from 2000 to 2020 NDVI、 By constructing a maximum entropy model, the average wind speed, relative humidity, slope, aspect, vegetation type, and distance from the river data are simulated and predicted to predict the susceptibility of natural grassland fires in Qinghai Province.

To improve the spatial partitioning accuracy, the Kvamme gain statistical model was used to validate the partitioning accuracy simulated by the maximum entropy model. The AUC value of the model accuracy was 0.947, and the G value was close to 1, indicating that the constructed natural grassland fire susceptibility evaluation model can effectively identify high-risk areas where natural grassland fires occur. The dataset has a resolution of 1km and the file format is GeoTIFF.