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恐龙谷南缘微地貌地形特征要素提取及分析
引用本文:罗为东,甘淑,袁希平,高莎.恐龙谷南缘微地貌地形特征要素提取及分析[J].测绘通报,2021,0(8):48-54.
作者姓名:罗为东  甘淑  袁希平  高莎
作者单位:昆明理工大学国土资源工程学院,云南 昆明650093;云南省高校高原山地空间信息测绘技术应用工程研究中心,云南 昆明650093;云南省高校高原山地空间信息测绘技术应用工程研究中心,云南 昆明650093;滇西应用技术大学地球科学与工程技术学院,云南 大理671006
基金项目:国家自然科学基金(41861054;41561083)
摘    要:地形特征信息是地学研究中的重要依据,用于描述地形变化的总体样貌,决定了基础地形地貌形态特征。本文对禄丰恐龙谷南缘环状微地貌的地形特征进行提取及分析。首先,采用无人机测量技术获取测区影像数据,通过影像数据处理构建测区0.5 m分辨率的DOM数据与点云数据,并基于TerraSolid软件平台搭建滤波规则对点云数据进行分类、抽稀压缩处理,提取测区地面点,以地面点数据为基础数据构建测区2 m分辨率的DEM;然后,通过叠加ArcGIS空间分析中最大值提取与正负地形提取,完成地形特征点的提取分析;并结合ArcGIS中水文分析、平面曲率与坡型组合的方法,完成地形特征线提取分析;最后,在eCognition 9.0中通过面向对象的方法,实现地形面状特征提取。试验结果表明:①提取鞍部点的最佳分析窗口为11×11。②通过鞍部点位及两种方法提取脊—谷线,其中水文分析提取脊线更为细致,整体连贯性更为突出且从山体两侧脊线分布密集,试验区山体崎岖处提取鞍部点,即说明恐龙谷南缘整体受亚热带低纬度高原季风气候影响,山体受一定程度风化侵蚀。③恐龙谷南缘地形面状特征中裸岩、裸地两者面积占比较大,两者相加后占测区总面积64.2%,结合实地干湿分明的气候特点和实际勘察植被相对低矮的特征,在一定程度上说明该区域表层土壤疏松,需注意水土流失引起的生态问题。

关 键 词:地形特征  点云  实景构建DEM  DOM  特征分析
收稿时间:2021-01-25

Extraction and analysis of feature elements of micro-topography in southern margin of Dinosaur Valley
LUO Weidong,GAN Shu,YUAN Xiping,GAO Sha.Extraction and analysis of feature elements of micro-topography in southern margin of Dinosaur Valley[J].Bulletin of Surveying and Mapping,2021,0(8):48-54.
Authors:LUO Weidong  GAN Shu  YUAN Xiping  GAO Sha
Institution:1. School of Land and Resources Engineering, Kunming University of Science and Technology, Kunming 650093, China;2. Application Engineering Research Center of Spatial Information Surveying and Mapping Technology in Plateau and Mountainous Areas Set by Universities in Yunnan Province, Kunming 650093, China;3. School of Earth Sciences and Engineering, West Yunnan University of Applied Sciences, Dali 671006, China
Abstract:Topographic feature information is an important basis in geoscience research. It is used to describe the overall appearance of topographic transformation and determines the basic landform and topographic features. This paper qims at the research on the extraction and analysis of topographic features of the annular micro-topography on the southern edge of Lufeng Dinosaur Valley. Firstly, the drone survey technology is used to obtain the image data of the survey area, and the 0.5 m resolution DOM data and point cloud data of the survey area are constructed through image data processing. Based on the Terra solid software platform, the filter rules are built to classify the point cloud data, dilute and compress, extract the ground points in the survey area, and use the ground point data as the basic data to construct DEM data with a resolution of 2 m in the survey area. Then, by superimposing the maximum value extraction and positive and negative terrain extraction in ArcGIS spatial analysis, the extraction and analysis of terrain feature points are completed; combined with the hydrological analysis in ArcGIS and the combination of plane curvature and slope type, the extraction and analysis of terrain feature lines are completed. Finally, an object-oriented method is used by eCognition9.0 to realize the extraction of terrain features. The test results show that: ① The best analysis window for extracting saddle points is 11×11; ② The ridge-valley line is extracted by saddle point positions and two methods. Among them, the hydrological analysis extracts the ridge line that is more detailed and the overall coherence. It is prominent and the saddle points that are extracted from the densely distributed ridges on both sides of the mountain and the rugged mountain in the experimental area. It shows that the southern edge of Dinosaur Valley is affected by the subtropical low-latitude plateau monsoon climate as a whole, and the mountain is weathered and eroded to a certain extent; ③ The topography of the southern edge of Dinosaur Valley among the characteristics, bare rock and bare land account for a relatively large area. Combining the dry and wet climate characteristics of the field and the relatively low vegetation actually is surveyed, which shows to a certain extent that the surface soil in this area is loose, and the attention should be paid to ecological problems caused by soil erosion.
Keywords:topographic features  point cloud  real scene construction DEM  DOM  feature analysis  
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