【摘要】 以长白山汪清林区为例,分析了星载激光雷达(ICESat-GLAS)数据在森林类型识别上的应用效果。采用软件Matlab和IDL对原始二进制数据进行处理,得到GLAS回波波形图;进一步提取与森林类型相关的波形特征参数,作为支持向量分类机(C-SVC)的输入量,进行森林类型识别,并采用K-折交叉验证方法对核函数选择进行评价。结果表明:C-SVC分类方法能够识别阔叶林和针叶林2种森林类型,识别精度达到85.24%。更多还原

【Abstract】 In Wangqing area of Changbai Mountains,the investigation was conducted to analyze the capability of the ICESatGLAS( Ice,Cloud and Land Elevation Satellite-Geoscience Laser Altimeter System) data on the forest type identification.The original binary ICESat-GLAS data was processed to obtain waveforms by MATLAB and IDL. The GLAS waveform metrics were derived as the input dataset of C-Support Vector Classification method( C-SVC) for forest type identification,and the kernel function selection was evaluated using K-fold cross-validation method. The C-SVC method is capable to classify broadleaf and coniferous forests with the accuracy of 85.24%.更多还原