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【目的】利用遥感和地形信息分析其与地面样地蓄积量的相关关系,探讨基于遥感和地学信息的森林蓄积量遥感估测方法。【方法】以样地蓄积量作为因变量,以SPOT5图像各波段、海拔、坡度及郁闭度为自变量,建立主成分回归、偏最小二乘回归、逐步回归模型。并从模型拟合效果、样本配对系数、模型适用性进行了比较分析。【结果】在同一自变量标准与估测精度保证的情况下,综合考虑拟合效果、估测值与实测值样本配对相关系数及模型适用性,以逐步回归模型最优。【结论】将逐步回归模型反演整个研究区得到估测蓄积量为33197465.0m3,野外实测值为31813463.0m3。
【Objective】 The objective of this study is to analyze the relationship between the accumulation of ground-based samples and remote sensing and topographic information, and to explore remote sensing estimation of forest volume based on remote sensing and geoscience information. 【Method】 The principal component regression, partial least-squares regression and stepwise regression model were established with plot accumulation as the dependent variable and the bands, altitudes, slopes and canopy degrees of SPOT5 images as independent variables. The comparative analysis of model fitting effect, sample matching coefficient and model applicability was carried out. 【Result】 The results show that under the condition of the same independent variable standard and the accuracy of the estimation, the fitting coefficient and the applicability of the model are considered synthetically, and the model is optimized step by step. 【Conclusion】 The results of stepwise regression model inversion of the entire study area showed that the estimated accumulation was 33197465.0 m3 and the field observation was 31813463.0 m3.