A Study On The Inversion And Validation Of Larix Gmelinii Leaf Area Index Based On Remotely-sensed Data

Vegetation leaf area index is one of the most important vegetation parameters, It take a important role in meteorology, agriculture and ecological environment research. Vegetation leaf area index inversion and verification is the hot topic of research.In this paper, we do a preliminary study of leaf area index inversion and validation in some forest areas in the Daxinganling Larch forest .Revealed and compared the methods of inversion of the local leaf area index and validation. Provide the basic data to further study on local leaf area index inversion and validation.Research shows that:Plants in less time, with the increase in the density of leaf area index will likely increase. After the increase in the number of plants because of the canopy shielded the situation between the leaf area index increased in complexity, resulting in the highest density of the sample leaf area index is not the biggest phenomenon. With the density of leaf area index did not significantly change the law.Leaf area index in a single peak growing season curve, the largest numerical July. By comparing relationship between the different vegetation index and the leaf area index ,we found that the effect of NDVI than other vegetation index (the ratio of vegetation index, soil rest vegetation index, improved soil vegetation index) should be good. The best model is the Third curve regression model: y = 44.327x~3 - 73.933x~2 + 43.306x - 6.5692 R~2 = 0.7264By studying on TM image inversion leaf area index scale conversion process, it proved a point of the method is not feasible, scaling work in multi-scale and the application of remote sensing image is essential.Determine the best sequence for the inversion of a leaf area index we should do inversion first and then change it scale.There is a big gap between MODIS LAI and TM LAI, some MODIS serious data are not in line with local conditions. MODIS need to improve its accuracy in further...