| 基于三方向搜索的DEM中洼地处理方法 |
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| 引用本文： | 李辉,陈晓玲,张利华,李长安.基于三方向搜索的DEM中洼地处理方法[J].水科学进展,2009,20(4):473-479. |
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| 作者姓名： | 李辉 陈晓玲 张利华 李长安 |
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| 作者单位： | 1.中国地质大学地球科学学院地理系, 湖北, 武汉, 430074; |
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| 基金项目： | 国家科技支撑计划，鄱阳湖湿地与流域研究教育部重点实验室开放基金，中国地质大学(武汉)优秀青年教师基金 |
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| 摘 要： | 数字高程模型(DEM)是流域参数提取的基础,然而DEM中普遍存在的洼地和平地影响了流域水系的自动提取,因此洼地去除方法成为研究的热点。针对现有洼地去处方法存在的问题,提出了一种基于"三方向搜索"的洼地处理方法。该方法通过对洼地及其周围网格高程值增减来达到去除洼地的目的,避免了传统填洼方法大规模的对DEM进行增高处理。实验结果表明,该算法简单易行,能有效的去除洼地,消除DEM提取的河网中的伪河道及"平行线"现象;且对DEM中高程值的改动较小,从而较大限度的保留了原始地形信息。
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| 关 键 词： | 数字高程模型 流域 洼地 三方向搜索 河网 |
| 收稿时间： | 2008-07-23 |
Depression removal method for grid DEM based on threE-direction search |
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| LI Hui,CHEN Xiao-ling,ZHANG Li-hua,LI Chang-an.Depression removal method for grid DEM based on threE-direction search[J].Advances in Water Science,2009,20(4):473-479. |
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| Authors: | LI Hui CHEN Xiao-ling ZHANG Li-hua LI Chang-an |
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| Institution: | 1.Geography department, China University of Geoscience, Wuhan 430074, China;2.Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330027, China;3.State Key Lab of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China |
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| Abstract: | The Digital Elevation Model (DEM) is the fundamental data source to extract the watershed parameters. However, the depressions and flat areas commonly exist due to the errors in the production of DEM. Various methods are thus proposed to remove the depressions and flat area in DEM. Most of the methods assume that the depressions are caused mainly by the underestimation of DEM values. In fact, the overestimation can also cause the depressions in the nearby grid cells. In this paper, a new method based on threE-direction search is presented to handle the problems by both raising and reducing the DEM values. The result suggests that the proposed method is easy to implement and can eliminate the "parallel river" in the result, and makes less modification of the original DEM values only to keep the original information to the largest extent. |
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| Keywords: | Digital Elevation Model(DEM) watershed depression threedirection search river network |
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