Department of Economic Geography, Faculty of Spatial Sciences, University of Groningen, Groningen, the Netherlands.
Rudolf Agricola School for Sustainable Development, University of Groningen, Groningen, the Netherlands.
PLoS One. 2023 Aug 2;18(8):e0288647. doi: 10.1371/journal.pone.0288647. eCollection 2023.
This paper is uniquely focused on mapping business land in satellite imagery, with the aim to introduce a standardized approach to estimating how much land in an observed area is allocated to business. Business land and control categories of land are defined and operationalized in a straightforward setting of pixel-based classification. The resultant map as well as information from a sample-based quantification of the map's accuracy are used jointly to estimate business land's total area more precisely. In particular, areas where so-called errors of omission are possibly concentrated are accounted for by post-stratifying the map in an extension of recent advances in remote sensing. In specific, a post-stratum is designed to enclose areas where business activity is co-located. This then enhances the area estimation in a spatially explicit way that is informed by urban and regional economic thought and observation. In demonstrating the methodology, a map for the San Francisco Bay Area metropolitan area is obtained at a producer's accuracy of 0.89 (F1-score = 0.84) or 0.82 to 0.94 when sub-selecting reference sample pixels by confidence in class assignment. Overall, the methodological approach is able to infer the allocation of land to business (in km2 ± 95% C.I.) on a timely and accurate basis. This inter-disciplinary study may offer some fundamental ground for a potentially more refined assessment and understanding of the spatial distribution of production factors as well as the related structure and implications of land use.
本文专注于在卫星图像中对商业用地进行测绘，旨在引入一种标准化的方法来估算观测区域内有多少土地用于商业用途。商业用地和控制用地类别在基于像素的分类这一简单设置中进行定义和操作化。生成的地图以及基于样本的地图精度量化信息被联合用于更精确地估算商业用地的总面积。特别是，通过在遥感领域的最新进展的扩展中对地图进行后分层，可以考虑所谓的漏报误差集中的区域。具体来说，设计了一个后分层区域，用于包围商业活动共置的区域。然后，这以一种由城市和区域经济思想和观察所告知的空间明确方式增强了面积估算。在演示方法时，获得了旧金山湾区大都市区的地图，其生产者精度为 0.89（F1 分数= 0.84），或者当通过置信度选择参考样本像素时，精度为 0.82 至 0.94。总体而言，该方法能够及时准确地推断出土地在商业（以平方公里为单位，±95%置信区间）上的分配情况。这项跨学科研究可能为更精细地评估和理解生产要素的空间分布以及相关的土地利用结构和影响提供一些基本依据。
