DEM数据中路径搜索与地貌自动划分方法研究

发布时间：2018-04-05 10:44

本文选题：路径搜索　切入点：骨架线　出处：《西安建筑科技大学》2017年硕士论文

【摘要】：在数字高程模型(Digital Elevation Model,简称DEM)数据上进行路径搜索和地貌类型的划分是数字地形分析在地理学、地貌学以及地理信息科学中研究的热点问题,在人类生产、生活实践中具有良好的应用价值。在复杂的自然地形中,人或者车辆朝一定方向行进时,往往需要考虑地形对通行性的影响来选取适宜的路径。以此实际需要为导向,设计了一种沿搜索方向寻找较易通行路径的解决方法。此外,由于地貌影响着资源的配置,需要深入研究基本地貌类型的自动划分方法,科学地认知地貌特征,合理地利用自然资源。论文的主要工作分为以下两个方面:(1)考虑地形平坦度、地势等因素对通行性的影响,以坡度、地势起伏度、地表粗糙度为通行性评价指标对区域的通行程度进行评估与分级,在通行性分级数据的基础上,提取了可通行性区域的骨架线,并将其转化为有向图,进而运用Dijkstra算法找出与搜索方向吻合的路径。(2)目前,公认的地貌划分体系是地貌形态与成因综合对地貌进行划分。遵循这一划分原则,从地形因子的数学含义和地学意义出发,对进行了定性分析,筛选了适合地貌划分的地形因子组合,用以训练卷积神经网络实现了平原和山地特征信息的自动挖掘,再结合决策表对中国青藏高原、两广丘陵等部分地区进行地貌自动划分。
[Abstract]:Path search and geomorphologic classification based on digital elevation model digital Elevation model (demm) are hot issues in digital terrain analysis in geography, geomorphology and geographic information science.It has good application value in life practice.In complex natural terrain, when people or vehicles move in a certain direction, it is often necessary to consider the influence of terrain on the traffic to select the appropriate path.Based on the practical needs, a new method is designed to find a more accessible path along the search direction.In addition, due to the influence of geomorphology on the allocation of resources, it is necessary to study the automatic division method of basic geomorphological types, to scientifically recognize the geomorphological characteristics and to make rational use of natural resources.The main work of the paper is divided into the following two aspects: 1) considering the influence of terrain flatness, topography and other factors on the transportability, using slope, terrain fluctuation and surface roughness as the indicators of the evaluation of the accessibility of the area to evaluate and classify the traffic degree.Based on the traffic classification data, the skeleton line of the traversability region is extracted and transformed into a directed graph, and then the path matching with the search direction is found by using the Dijkstra algorithm.The recognized system of geomorphological classification is the combination of geomorphology and its origin.In accordance with this principle, from the mathematical meaning and geoscientific significance of topographic factors, the qualitative analysis is carried out, and the combination of topographic factors suitable for geomorphologic classification is selected.In order to train convolutional neural network, the feature information of plain and mountain can be excavated automatically, and the geomorphology of some areas such as Qinghai-Tibet Plateau, Liangguanghilly area and so on in China are divided automatically with decision table.
【学位授予单位】：西安建筑科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：P208

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