The Retrieval Of Moisture Content Of Forest Fuels In Daxing’ Anling Of Heilongjiang Province

The forest fuels moisture plays a crucial role in forest fire and the appearance of thriving remote technology has provided a fast, convenient, reliable way in predicting it. The MODIS data has been applied to natural resources exploration, disaster prediction, and land survey, environment protection, with its advantages of short period, high macroscopically, and stability, economic. In this paper, using MODIS BRDF and LAI data combined estimating model of typical forest litter moisture content in based on the field spectrum to reverse whole forest fuels moisture content in in Daxing’anling of China. The main study contents and conclusions were as follows:(1) Forest fuels content was measured and its spectrum information was collected by drying method, full-ranged band spectrometer SVCHR-10241, respectively. Three transformations of spectrum, namely, the original, the first-order derivate, the continuum-removal,and forest fuels were put in to established the regression model by statistical methods, R2,MRE, RMSE were:0.422、0.17、0.54;0.489、0.33、1.15;0.566、0.306、0.45 respectively,the moisture sensitive band were:468nm～868nm、998nm～1028nm、 1158～1218nm、1318～2248nm、2378～2488nm(extremely significant)and 418nm-468nm、 418nm～468nm、878～988nm、1018nm～1068nm、1228nm～1248nm、 2258nm～2308nm(significant), and has two poles 0.69,-0.69 positive, negative, in 1498nm 1508nm respectively.(2) With the help of professor Chen Jingming 4 - scale model, combined with the BRDF and LAI data products for Daxing’anling region forest litter inversion, it indicated:Forest fuels moisture content was reversed by MODIS BRDF and LAI data products, the solutions to M(multiple scattering factors) and four different components (KT,KZT,KG,KZG) is established LUTS(look-up tables) by 5-Sclaes models introduced by Prof.Chen jingmin.in calculating M, the model based on four given VZAS in two bands (5,6)were analyzed and selected, finally,the two given VZAS (45°、60°) were applied to,the models’ R2were:0.577,0.583; 0.95, 0.947,resplectively.also,the models’R of four different components ((KT,KZT,KG,KZG) were:0.769、0.867、0.937、0.879;0.822、0.83、0.917、0.82.The models’ MRE and RMSE in reversed graph were:61.4%; 696.6%, respectively. It indicated:by using MODIS data inversion of forest litter moisture content can provide accurate and better continuity litter moisture content data, it has certain significance for forest fire forecast.