基于ASTER数据遥感影像的决策树分类

以黑龙江省北安市为研究区域，尝试利用ASTER视反射率值进行便利、准确的土地利用分类研究。对ASTER数据进行波段相关分析，确定最佳组合波段；然后重点分析转换为视反射率值的影像特征和光谱特征，从中提取各种典型地物的光谱曲线； 并依据提取的光谱曲线建立基于地物反射率值大小关系或阈值的决策树模型，对研究区不同地物类型进行分类，并对结果进行精度评价。应用效果表明，该方法简单有效，但对于混合光谱容易错分。

Decision Tree Based on ASTER Image Classification and Its Application

The autuors present a decision tree based method for an easier and more accurate land-use classification using apparent reflectance values derived from ASTER images.The method starts with the correlation analyses among ASTER bands so that the optimal bands composite is found for best visual interpretation.On the derived image,apparent reflectance values represented,emphasis is paid to the analysis of the spatial and spectral characteristics of various land-use types.Spectral profiles of several typical land-use types are extracted.A decision tree model is established based on given thresholds of the apparent reflectance values.With the model the classification is then performed,associated with an accuracy assessment.The procedures are applied to ASTER images from Beian municipal region of Heilongjiang Province,Northeast China.The classified results show that the decision tree method facilitates the classification effectively.One shortcoming of the method is that some wrong classification may occur in areas where mixed spectra of different land-use types exist.