Department of Computing Sciences, Conrad Blucher Institute for Surveying and Science, Texas A&M University-Corpus Christi, Corpus Christi, Texas, United States of America.
PLoS One. 2021 Apr 15;16(4):e0250106. doi: 10.1371/journal.pone.0250106. eCollection 2021.
Spatial analysis extracts meaning and insights from spatially referenced data, where the results are highly dependent on the quality of the data used and the manipulations on the data when preparing it for analysis. Users should understand the impacts that data representations may have on their results in order to prevent distortions in their outcomes. We study the consequences of two common data preparations when locating a linear feature performing shortest path analysis on raster terrain data: 1) the connectivity of the network generated by connecting raster cells to their neighbors, and 2) the range of the attribute scale for assigning costs. Such analysis is commonly used to locate transmission lines, where the results could have major implications on project cost and its environmental impact. Experiments in solving biobjective shortest paths show that results are highly dependent on the parameters of the data representations, with exceedingly variable results based on the choices made in reclassifying attributes and generating networks from the raster. Based on these outcomes, we outline recommendations for ensuring geographic information system (GIS) data representations maintain analysis results that are accurate and unbiased.
空间分析从具有空间参照的数据中提取意义和见解，其结果高度依赖于所使用数据的质量以及在准备进行分析时对数据的操作。用户应该了解数据表示形式可能对其结果产生的影响，以防止结果出现扭曲。当在栅格地形数据上执行最短路径分析时，我们研究了定位线性特征的两种常见数据准备的后果：1）连接栅格单元与其邻居生成的网络的连通性，以及 2）分配成本的属性比例范围。此类分析通常用于定位输电线路，其结果可能对项目成本及其环境影响产生重大影响。解决双目标最短路径的实验表明，结果高度依赖于数据表示形式的参数，根据对属性重新分类和从栅格生成网络的选择，结果变化极大。基于这些结果，我们概述了确保地理信息系统 (GIS) 数据表示形式保持准确且无偏的分析结果的建议。
