基于香格里拉地区Landsat 8影像、外业调查和森林资源二类调查数据,采用坡度匹配法对遥感数据进行了地形校正,使用线性波谱分离(LSU)、匹配滤波(MF)、最小能量约束(CEM)、像元均方差抛物线(PMVP)等4种方法,提取了高山松丰度图。分析丰度结果,4个典型样区平均均方根误差值排序为LSU<PMVP<CEM<MF,PMVP能较好地分出高山松边界信息,丰度提取效果较好。使用上述4种不同方法将4个不同的地物混合类型提取的高山松丰度与真实丰度(0.557 7)进行对比,接近程度依次为PMVP,LSU,CEM,MF。利用像元均方差抛物线方法提取高山松丰度精度较高,后期还可以探索更合适的拟合曲线方法,使其能应用到森林树种的丰度提取和林地覆盖分类中。
Four typical research sample areas which are boundary mixed were selected based on Landsat8 images.The method of slope matching was used to do topographic corrections.The abundance of the Pinus densat was extracted using the method of linear spectral separation(LSU),matched filtering(MF),the minimum energy constraint(CEM),the pixel mean variance parabola(PMVP).The results of the abundance show that the order of the average root mean square error values of the four typical sample areas is:LSU <PMVP<CEM <MF.The PMVP could better separate Pinus densat boundary with a good result.Using PMVP to extract abundance has achieved higher accuracy.It could also explore more suitable curve fitting methods applied to the extraction of forest tree species abundance and land cover classification in the future.
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