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激光雷达(Lidar)与光学遥感的有效结合对中国南方区域森林冠顶高度反演意义重大,而国产卫星将为中国森林生态研究提供新的数据源。本文联合利用大脚印激光雷达GLA和国产MERSI数据,在实现GLAS波形数据处理和不同地形条件下森林冠顶高度反演算法基础上,建立了区域尺度不同森林类型林分冠顶高度GLAS+MERSI联合反演关系模型,进行了江西地区森林冠顶高度反演。总体上,GLAS激光雷达森林冠顶高度估算精度较高;且在与MERSI250m数据的联合反演模型中,针叶林模型精度较好(R2=0.7325);阔叶林次之(R2=0.6095);混交林较差(R2=0.4068)。分析发现,考虑了光学遥感生物物理参数的GLAS+MERSI联合关系模型在区域森林冠顶高度估算中有较高精度,且在空间分布上与土地覆盖数据分布特征非常一致。
The effective combination of Lidar and optical remote sensing is of great significance for the inversion of the forest crown height in the southern China. Domestic satellites will provide a new data source for forest ecology research in China. Based on GLAS and domestically produced MERSI data, GLAS + MERSI combined with GLAS waveform data processing and forest crown height inversion algorithm under different topography conditions are established in this paper. Inverse regression model of forest crown in Jiangxi Province was carried out. In general, the accuracy of the GLAS lidar height estimation is high. In the joint inversion model with the MERSI250m, the coniferous forest model has better accuracy (R2 = 0.7325), followed by the broad-leaved forest (R2 = 0.6095) ; Mixed forest is poor (R2 = 0.4068). The analysis shows that the GLAS + MERSI joint relationship model considering the optical remote sensing biophysical parameters has high precision in estimating the crown height of the regional forest, and the spatial distribution is in good agreement with the distribution characteristics of land cover data.