面向地理国情监测的房屋建筑区树冠覆盖多特征协同提取

针对全国地理国情监测工作新增树冠覆盖提取这一全新的工作任务，本文通过深入分析房屋建筑区主要地物光谱特征和纹理特征，确定以光谱特征归一化植被指数（NDVI），以及对比度（contrast）信息熵（entropy）两个纹理特征作为判断规则，按照面向对象的思路，设计了一种综合应用高分辨率遥感影像光谱特征和纹理特征的房屋建筑区树冠覆盖范围提取方法。试验结果表明，该方法能够自动提取房屋建筑区树冠覆盖范围，大幅降低了当前常用的目视解译方法的工作量，与采用单一影像特征的提取方法相比，本文方法能够有效地区分房屋建筑区内与树冠覆盖光谱特征相近的地物要素。

Multi-feature collaborative extraction of canopy coverage in building area for geographical condition monitoring

In view of the new task of extracting canopy cover in national geographic condition monitoring work, through in-depth study and analysis of spectral and texture characteristics of main ground features in housing construction area, the normalized vegetation index (NDVI), contrast and entropy are used as judgment rules. According to the idea of object-oriented, an extraction method of canopy coverage in building area based on high-resolution remote sensing image is designed. The experimental results show that the method can automatically extract the canopy coverage of the building area, greatly reduce the workload of the current common visual interpretation methods, and can effectively distinguish other ground features in the building area with similar spectral characteristics of canopy coverage compared with using a single image feature.