基于回溯地形图的自然管理制图重建

Q4 Earth and Planetary Sciences Geodeziya i Kartografiya Pub Date : 2023-04-20 DOI:10.22389/0016-7126-2023-993-3-25-34
A. Beshentsev, A. A. Lubsanov
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引用次数: 0

摘要

以贝加尔湖流域最发达的地区为例,编制了二十世纪初区域自然管理的数字地图重建;它能够确立过去领土经济使用的物理和地理特征。作为自然管理对象回溯层矢量化和随后将其shp文件转换为ArcGIS环境空间对象类的结果,形成了两个此类类的制图集。它们具有两种类型的区域自然利用,传统的田园和入侵农业。通过在现代地形基础上对地图集进行逐层地理信息建模和数字地形模型,建立了领土的主要定居区和经济利用区,并对不同类型的自然管理的空间和时间生命支持结构进行了各种测绘。针对可操作的数字可视化,提出了一种通过布置ArcGIS信息环境中基于文件的地理数据来存储和映射空间对象类别集的技术解决方案。介绍了二十世纪初田园和农业自然管理的地图重建,以及基于景观的一般地图重建。
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Cartographic reconstruction of nature management based on retrospective topographic maps
Taking the most developed part of the Baikal basin as example a digital cartographic reconstruction of the regional nature management of the early XX century is compiled; it enables establishing the physical and geographical characteristics of the territory economic use in the past. As a result of nature management objects retrospective layers vectorization and subsequent transformation of their shp files into the ArcGIS environment spatial object classes, two cartographic sets of such classes were formed. They characterize two types of regional nature use, traditional pastoral and invasive agricultural. As a result of layer-by-layer geoinformation modeling of cartographic sets on a modern topographic basis and a digital relief model, primary areas of settlement and economic use of the territory were established, and various mapping of spatial and temporal life support structures of nature management different types was performed. For operational digital visualization, a technological solution is proposed for storing and mapping sets of classes of spatial objects through arrangement of a file-based geodata of the ArcGIS information environment. Cartographic reconstructions of pastoral and agricultural nature management at the beginning of the XX century are presented, as well as its general cartographic reconstruction on landscape basis.
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来源期刊
Geodeziya i Kartografiya
Geodeziya i Kartografiya Earth and Planetary Sciences-Earth-Surface Processes
CiteScore
0.60
自引率
0.00%
发文量
73
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