| 多模型协同下的城郊地区DEM构建方法研究 |
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| 引用本文： | 赵明伟,金永林,江岭,王春,杨灿灿,徐燕.多模型协同下的城郊地区DEM构建方法研究[J].地球信息科学,2020,22(3):389-398. |
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| 作者姓名： | 赵明伟 金永林 江岭 王春 杨灿灿 徐燕 |
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| 作者单位： | 1. 滁州学院地理信息与旅游学院,滁州 239000;2. 中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室,北京 100101 |
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| 基金项目： | 国家自然科学基金项目(41701450);国家自然科学基金项目(41571398);安徽省自然科学基金项目(1808085QD103);资源与环境信息系统国家重点实验室2018年度开放基金项目;安徽省大学生创新训练项目(2019CXXL102) |
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| 摘 要： | 人类活动对地表的改造使其呈现形态多样化、不连续等特征,此时传统的DEM构建方法难以满足这些区域DEM精度要求。为此,本文提出了一种多模型协同构建DEM的思路,首先按照形态特征和语义信息对地形进行分类,然后对不同类型的地形区域,选择、设计适宜的方法分别进行DEM构建,最后将不同区域构建DEM结果融合拼接形成区域完整的DEM结果。本文选择江苏省南京市城市郊区某区域为实验区,以1:500比例尺地形图为基本数据源进行DEM构建实验。实验结果表明,与传统经典DEM构建方法相比,本文提出的多模型协同的DEM构建方法能够有效表达实验区域不同的地形特征,特别是对于人工改造的地形(如道路、边坡等区域),本文方法构建的DEM其形态精度优势显著;同时,基于验证点法的高程精度分析结果表明,本文方法构建DEM的高程精度亦优于传统DEM构建方法,特别是对于一些形态规则而高程信息相对稀少的区域,以边坡区域为例,经典DEM构建法平均误差均超过5 m,而本文构建结果平均误差为0.26 m,精度优势非常明显。研究表明本文提出的多模型协同的DEM构建方法适用于人类活动改造或显著影响的区域的DEM构建。
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| 关 键 词： | DEM 地形图 人工地形 形态特征 多模型协同 语义信息 形态精度 高程精度 |
| 收稿时间： | 2019-09-30 |
Research on DEM Construction in Suburban Areas based on Multi-model Cooperation |
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| ZHAO Mingwei,JIN Yonglin,JIANG Ling,WANG Chun,YANG Cancan,XU Yan.Research on DEM Construction in Suburban Areas based on Multi-model Cooperation[J].Geo-information Science,2020,22(3):389-398. |
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| Authors: | ZHAO Mingwei JIN Yonglin JIANG Ling WANG Chun YANG Cancan XU Yan |
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| Institution: | 1. College of Geographic Information and Tourism, Chuzhou University, Chuzhou 239000, China;2. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China |
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| Abstract: | Digital Elevation Model(DEM) is the digital expression of terrain surface morphology. As an important basic geographic information data, DEM has an important application in the field of natural and human sciences. Therefore, the construction of DEM data with high form accuracy and elevation accuracy has become a hot issue in related research fields. With the development of human society, the transformation and influence of human activities on the topography are becoming more and more significant, the surface modification taken by human activities makes it diversified and discontinuous. At this time, traditional DEM construction methods cannot meet the accuracy requirements of DEM in these areas. To solve this problem, this paper proposes a multi-model collaborative approach to construct DEM. Firstly, the features of the earth’s surface are classified according to their morphological features and semantic information. Then, this research construct DEM according to the design of different features of the earth's surface and the selection of appropriate methods. Finally, the research fuse and stitch the results of DEM to form a regional and complete DEM result. This paper chooses a suburban area of Nanjing as the experimental area and takes a large-scale topographic map as the basic data source to carry out DEM construction experiment. The results show that compared with the traditional DEM construction method, the multi-model collaborative DEM construction method proposed in this paper can effectively guarantee the expression of various types of terrain elements in the experimental area. Especially for the terrain transformed by human activities, such as roads, slopes and other areas, the DEM constructed by this method has a significant advantage in morphological accuracy.At the same time, the height accuracy analysis results based on the verification point method show thatthe elevation accuracy of DEM constructed by this method is also better than that of traditional DEM constructed method. Especially for some areas with regular shape and relatively scarce elevation information, the accuracy advantage of this method is particularly remarkable. This research results prove that the proposed multi-model collaborative DEM construction method is suitable for DEM construction in areas where human activities are transformed or significantly affected.The research of this paper has certain theoretical significance and application value for enriching the method system of DEM construction and analysis, as well as the production of high-precision DEM data in urban areas. |
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| Keywords: | DEM topographic map artificial topography morphological character multi-model collaboration semantic information morphological accuracy elevation accuracy |
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