"Expansion-Fusion" Extraction of Surface Gully Area Based on DEM and High-Resolution Remote Sensing Images
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摘要: 地表沟壑的精细化提取是地形地貌特征的重要内容.针对现有沟壑提取结果中存在断裂区域和伪沟壑区域的情况，提出一种基于DEM和高分辨率遥感影像的地表沟壑“膨胀-融合”式提取方法.该方法综合了D8算法、坡向变率算法和面向对象分类方法的提取结果，首先引入距离制图算法对初始沟壑进行方向性膨胀，然后通过栅格重分类和代数运算进行沟壑融合，剔除伪沟壑区域，最终实现研究区域内沟壑的精细化提取.以GDEM v2数据和高分二号影像数据为数据源，精细化提取了湖北省神农架林区举黑沟至麻湾村一带的地表沟壑.采用随机点验证法对实验区域内的沟壑提取结果进行了精度评价，结果表明该方法的总体精度为92%，能有效弥合数据中的断裂区域，同时剔除伪沟壑区域，达到提高沟壑提取精度的目的.Abstract: Refined extraction of surface gullies is an important part of topography research. Aiming at the existence of fracture zones and a pseudo-gully zones in the existing gully extraction results,in this paper,it proposes an "expansion-fusion" extraction method based on DEM and high-resolution remote sensing image. The method combines the D8 algorithm,the SOA (slope of aspect) algorithm and the object-oriented classification method to extract the results. Firstly,the distance mapping algorithm is introduced to directional expansion of the initial gully,and then the raster re-classification and algebraic operation are used to merge the gully and eliminate the pseudo-gully. In this study,this method is adopted to extract gully area with GDEM v2 data and GF-2 data covering the area of Juheigou to Mawancun in Shennongjia Forest of Hubei Province. The random point verification method is used to evaluate the accuracy of the gully extraction in the experimental area. The results show that the overall accuracy of the method is 92%,which can effectively bridge the fracture area in the combined data,and eliminate the pseudo-gully area to improve the extraction accuracy of the gully.
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图 1 基于DEM和高分辨率遥感影像的“膨胀-融合”地表沟壑提取方法总体流程
Fig. 1. The flow chart of surface gully "expansion-fusion" extraction method based on DEM and high-resolution remote sensing image
图 2 多源沟壑数据的膨胀与融合方法流程图
Fig. 2. The flow chart of expansion and fusion method of multi-source gully data
表 1 分类规则
Table 1. The rules of classification
目标特征 长/宽 主方向纹理特征 坡度 归一化植被指数 灰度共生矩阵 Forest < 30° > 0.2 124~129 Road > 2 70°~110° 114~123 Gully 80°~130° > 20° 122~128 Farm < 30° 0.21~0.30 90~110 
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表 2 精度评价矩阵
Table 2. The accuracy evaluation matrix
指标 沟壑提取精度 非沟壑提取精度 总体精度 水文分析法 61.1% 89.6% 84.5% 坡向变率法 55.6% 81.1% 76.5% 面向对象的分类法 75% 91.5% 88.5% 融合提取方法 83.3% 93.9% 92%
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