Uhl Johannes H, Zoraghein Hamidreza, Leyk Stefan, Balk Deborah, Corbane Christina, Syrris Vasileios, Florczyk Aneta J
Department of Geography, University of Colorado Boulder, Boulder, Colorado, USA.
National Center for Atmospheric Research (NCAR), Boulder, Colorado, USA.
Int J Digit Earth. 2020;13(1):22-44. doi: 10.1080/17538947.2018.1550120. Epub 2018 Nov 26.
There is an increasing availability of geospatial data describing patterns of human settlement and population such as various global remote-sensing based built-up land layers, fine-grained census-based population estimates, and publicly available cadastral and building footprint data. This development constitutes new integrative modelling opportunities to characterize the continuum of urban, peri-urban, and rural settlements and populations. However, little research has been done regarding the agreement between such data products in measuring human presence which is measured by different proxy variables (i.e., presence of built-up structures derived from different remote sensors, census-derived population counts, or cadastral land parcels). In this work, we quantitatively evaluate and cross-compare the ability of such data to model the urban continuum, using a unique, integrated validation database of cadastral and building footprint data, U.S. census data, and three different versions of the Global Human Settlement Layer (GHSL) derived from remotely sensed data. We identify advantages and shortcomings of these data types across different geographic settings in the U.S., which will inform future data users on implications of data accuracy and suitability for a given application, even in data-poor regions of the world.
描述人类居住和人口模式的地理空间数据越来越多,例如各种基于全球遥感的建成区土地图层、基于精细人口普查的人口估计数据,以及公开可用的地籍和建筑物占地面积数据。这一发展为表征城市、城郊和农村住区及人口的连续性提供了新的综合建模机会。然而,对于这些数据产品在通过不同代理变量(即来自不同遥感传感器的建成结构、人口普查得出的人口计数或地籍地块)测量人类存在方面的一致性,相关研究甚少。在这项工作中,我们使用一个独特的、集成的验证数据库,该数据库包含地籍和建筑物占地面积数据、美国人口普查数据以及从遥感数据得出的三个不同版本的全球人类住区层(GHSL),对这些数据建模城市连续性的能力进行了定量评估和交叉比较。我们确定了这些数据类型在美国不同地理环境中的优势和不足,这将为未来的数据用户提供信息,使其了解数据准确性和适用性对特定应用的影响,即使在世界上数据匮乏的地区也是如此。