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摘要： 地震经常诱发数量众多，覆盖范围广的滑坡并造成极大危害，因此，需要对大范围的滑坡灾害进行快速评估。随着遥感影像分辨率的提高，面向对象分类方法在这方面的应用比传统的目视解译和基于像素的方法更具优势。但是，目前基于面向对象方法的滑坡识别研究还相对较少，而且通常针对小范围的研究区。基于SPOT5 2.5 m多光谱影像，提出一种综合光谱、空间、地形和形态特征的面向对象滑坡自动识别方法，并应用于较大范围研究区。结果表明:面向对象滑坡自动识别方法能将研究区内95%的滑坡识别出来，综合考虑滑坡的过度提取与遗漏提取情况，滑坡提取质量为74.04%，效果较好，能够快速、有效地识别大范围的滑坡。该方法可以应用于对地震或强降雨引起的大范围滑坡灾害进行快速评估，为灾后应急救援和恢复重建工作提供参考。 关键词： 面向对象;  遥感影像;  滑坡;  识别;  规则集     Abstract: Earthquakes in mountain area often induce hundreds of thousands of landslides resulting in destructive casualties and economic damage.It is urgent needed to rapidly detect the extent areas of the landslides.With the advent of very high resolution satellite remote sensing，the application of the object\|oriented classification method in this area have significant advantage comparing to those of visual interpretation and pixel\|based methods.However，the study of object\|oriented landslide detection is relatively few，and the study usually has a small study area.The method of object\|oriented rapid identification of landslides based on the spectral，spatial and morphometric properties of landslides and a 2.5m SPOT5 multi\|spectral image is proposed in this paper and is applied in a relatively large study area.The normalized difference vegetation index (NDVI) threshold was set to remove vegetation objects and obtain landslide candidates.Then，the spectral characteristics，texture，terrain features and context of the image were used to build indicators to gradually separate the landslide from false positives.The small scale chessboard segmentation was conducted to further eliminate vegetation objects and get the landslide objects.The object\|oriented detection results show that the adopted method can recognize about 95% of the landslides in the study area.When considering the landslide excessive detection and omissions，the landslide detection quality percentage of the proposed method is 74.04%.Hence，the method proposed in the article can help to rapid assess landslide disasters caused by earthquakes or heavy rainfalls，providing a reference for post\|disaster emergency relief and reconstruction work.

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