European Commission, Joint Research Centre, Via E. Fermi 2749, 21027, Ispra, VA, Italy.
Sci Rep. 2023 Mar 16;13(1):4367. doi: 10.1038/s41598-023-31253-z.
Many geospatial analyses require flexible aggregation of adjacent units to meet a minimum target area or attribute value. This is usually accomplished using several non-automated and complex GIS tasks. We developed an integrated user-friendly approach and algorithm implemented in the 'GHS-SmartDissolve' tool, which addresses minimum mapping unit or attribute value requirements, layers resolution mismatch, spatial uncertainty or modifiable areal unit problem in GIScience. This method automatically dissolves adjacent features updating fields' values to reach a minimum target area or attribute value, using a flexible settings framework to meet user requirements. Also provided as a toolbox for ArcGIS (Esri), the approach is demonstrated by (i) estimating the mean particulate matter concentrations for all municipalities in Italy in 2011 by combining a coarse grid of global PM2.5 concentrations with fine administrative units; (ii) estimating boundaries of Metropolitan areas in Portugal as aggregation of municipalities, by matching their total population.
许多地理空间分析需要灵活地聚合相邻单元，以达到最小目标区域或属性值。这通常需要使用多个非自动化和复杂的 GIS 任务来完成。我们开发了一种集成的、用户友好的方法和算法，并将其实现到 'GHS-SmartDissolve' 工具中，该工具解决了最小制图单元或属性值要求、图层分辨率不匹配、空间不确定性或 GIS 中的可修改区域单位问题。该方法使用灵活的设置框架自动溶解相邻特征，更新字段的值以达到最小目标区域或属性值，以满足用户的要求。该方法还作为一个工具箱提供给 ArcGIS（Esri），通过以下两种方式进行演示：（i）通过将全球 PM2.5 浓度的粗网格与精细的行政单元相结合，估算 2011 年意大利所有城市的平均颗粒物浓度；（ii）通过匹配其总人口，将葡萄牙的大都市区边界作为城市的聚合进行估算。
