Automated Geospatial Approach for Assessing SDG Indicator 11.3.1: A Multi-Level Evaluation of Urban Land Use Expansion across Africa

IF 2.8 3区 地球科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Orion S. E. Cardenas-Ritzert, Jody C. Vogeler, Shahriar Shah Heydari, Patrick A. Fekety, Melinda Laituri, Melissa McHale
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引用次数: 0

Abstract

Geospatial data has proven useful for monitoring urbanization and guiding sustainable development in rapidly urbanizing regions. The United Nations’ (UN) Sustainable Development Goal (SDG) Indicator 11.3.1 leverages geospatial data to estimate rates of urban land and population change, providing insight on urban land use expansion patterns and thereby informing sustainable urbanization initiatives (i.e., SDG 11). Our work enhances a UN proposed delineation method by integrating various open-source datasets and tools (e.g., OpenStreetMap and openrouteservice) and advanced geospatial analysis techniques to automate the delineation of individual functional urban agglomerations across a country and, subsequently, calculate SDG Indicator 11.3.1 and related metrics for each. We applied our automated geospatial approach to three rapidly urbanizing countries in Africa: Ethiopia, Nigeria, and South Africa, to conduct multi-level examinations of urban land use expansion, including identifying hotspots of SDG Indicator 11.3.1 where the percentage growth of urban land was greater than that of the urban population. The urban agglomerations of Ethiopia, Nigeria, and South Africa displayed a 73%, 14%, and 5% increase in developed land area from 2016 to 2020, respectively, with new urban development being of an outward type in Ethiopia and an infill type in Nigeria and South Africa. On average, Ethiopia’s urban agglomerations displayed the highest SDG Indicator 11.3.1 values across urban agglomerations, followed by those of South Africa and Nigeria, and secondary cities of interest coinciding as SDG Indicator 11.3.1 hotspots included Mekelle, Ethiopia; Benin City, Nigeria; and Polokwane, South Africa. The work presented in this study contributes to knowledge of urban land use expansion patterns in Ethiopia, Nigeria, and South Africa, and our approach demonstrates effectiveness for multi-level evaluations of urban land expansion according to SDG Indicator 11.3.1 across urbanizing countries.
评估可持续发展目标指标 11.3.1 的自动化地理空间方法:对非洲各地城市土地使用扩张的多层次评估
事实证明,地理空间数据有助于监测城市化进程和指导快速城市化地区的可持续发展。联合国(UN)可持续发展目标(SDG)指标 11.3.1 利用地理空间数据估算城市土地和人口的变化率,提供了对城市土地使用扩张模式的深入了解,从而为可持续城市化倡议(即 SDG 11)提供信息。我们的工作通过整合各种开源数据集和工具(如 OpenStreetMap 和 openrouteservice)以及先进的地理空间分析技术,增强了联合国提出的划定方法,从而自动划定一个国家的各个功能城市群,并随后计算出每个功能城市群的可持续发展目标指标 11.3.1 和相关指标。我们将自动化地理空间方法应用于三个快速城市化的非洲国家:埃塞俄比亚、尼日利亚和南非,对城市用地扩张进行了多层次的研究,包括确定可持续发展目标指标 11.3.1 中城市用地增长百分比高于城市人口增长百分比的热点地区。从 2016 年到 2020 年,埃塞俄比亚、尼日利亚和南非的城市群已开发土地面积分别增长了 73%、14% 和 5%,埃塞俄比亚的新城市发展属于外向型,尼日利亚和南非的新城市发展属于填充型。平均而言,埃塞俄比亚的城市群显示出最高的可持续发展目标指标 11.3.1 值,其次是南非和尼日利亚的城市群,作为可持续发展目标指标 11.3.1 热点的二级城市包括埃塞俄比亚的梅凯莱、尼日利亚的贝宁市和南非的波洛克瓦内。本研究中介绍的工作有助于了解埃塞俄比亚、尼日利亚和南非的城市土地使用扩张模式,我们的方法证明了根据可持续发展目标指标 11.3.1 在城市化国家对城市土地扩张进行多层次评估的有效性。
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来源期刊
ISPRS International Journal of Geo-Information
ISPRS International Journal of Geo-Information GEOGRAPHY, PHYSICALREMOTE SENSING&nb-REMOTE SENSING
CiteScore
6.90
自引率
11.80%
发文量
520
审稿时长
19.87 days
期刊介绍: ISPRS International Journal of Geo-Information (ISSN 2220-9964) provides an advanced forum for the science and technology of geographic information. ISPRS International Journal of Geo-Information publishes regular research papers, reviews and communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. The 2018 IJGI Outstanding Reviewer Award has been launched! This award acknowledge those who have generously dedicated their time to review manuscripts submitted to IJGI. See full details at http://www.mdpi.com/journal/ijgi/awards.
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