Research Progress in the Evaluation of Fuel Moisture Content in Vegetation Canopy
In recent years,the frequent occurrence of forest fires has caused serious human and material loss,and the research on forest fire forecasting and prevention/control has attracted increasing attention.The moisture content of vegetation canopy is an important parameter of forest fuel and a key factor to forest fire forecasting,which has important significance for the prediction and early-warning of forest fire occurrence and fire behaviors.In view of the fact that there are many methods and diverse data for evaluating vegetation canopy's moisture content at present,this paper classifies the methods at home and abroad,especially the method of remote sensing inversion,summarizes their development state and existing problems,and discusses the prospects in the application of multi-source remote sensing data fusion,artificial intelligence algorithms,GIS analysis methods to the spatiotemporal inversion of fine vegetation canopy moisture content,in order to provide references for enhancing the evaluation efficiency of vegetation canopy moisture content,expanding the application of remote sensing inversion of fuel moisture content,and improving the accuracy of forest fire forecasting.
fuel moisture contentforest fire forecastingvegetation canopyremote sensingassessment method
NETL
NSTL
万方数据
