Is the New Silk Road Enhancing Urban Expansion? Spatio-Temporal Analysis with Remote Sensing Data

Soltani, Salim and Debray, Henri and Zhu, Xiaoxiang and Taubenböck, Hannes (2021) Is the New Silk Road Enhancing Urban Expansion? Spatio-Temporal Analysis with Remote Sensing Data. CITIES 20.50 – Creating Habitats for the 3rd Millennium: Smart – Sustainable – Climate Neutral. Proceedings of REAL CORP 2021, 26th International Conference on Urban Development, Regional Planning and Information Society. pp. 291-299. ISSN 2521-3938

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Abstract

The world population is growing, and a majority of the population is and will be living in urban areas. Nearly 90 percent of this growth takes place in Asia and Africa. However, urbanisation processes are not distributed evenly. Mostly they are concentrated in prosperous regions, at infrastructural nodes, or along trade routes. The so-called New Silk Roads are new trade routes where massive investments are currently made to connect China with the world. The aim of this study is to analyse the dynamics of spatial urbanisation in spatial proximity to the New Silk Roads. In detail, we want to test the hypothesis whether higher spatial growth rates are recorded for cities along these routes than for cities in the same region but away from the New Silk Roads. For this task, we apply remotely sensed data. In this study, we extracted urban areas from multitemporal Landsat data for the time period of 1990 to 2019. We classify settlements using a Random Forest (RF) supervised classification technique. We used Gray-Level Co-Occurrence Matrix (GLCM) texture features together with spectral indices as feature set. We derive training data for our classifier by a stratified sampling method using geoinformation from the Global Human Settlement Layer (GHSL) and the ESA annual Land-cover data. The resulting consistent classifications of urban areas have temporal intervals of 5 years, i.e. 1990,1995, 2000, 2005,2010,2014, 2019 and feature high accuracies. We selected cities with over 300,000 inhabitants. We define cities in proximity to the New Silk Roads (NSR cities) within a 100 km distance vs. cities with at least 100 km distance from the NSR (non-NSR cities); these cities are located in China, central Asian countries such as Kazakhstan, including Iran, Turkey, and Russia. We quantitively analyse spatio-temporal urban expansion trends for both groups, NSR, and non-NSR cities, for testing our hypothesis. To do so, we applied various urbanisation indices such as Overall Built-up Changed Area (OBAC), Annual Expansion Area (AEA), and urban Expansion Rate (ER). Generally, our results reveal that spatial urbanisation is increasing over the last almost 30 years in all cities among our sample. The spatial comparison of our two groups of cities reveals that our hypothesis can be confirmed: from 2014 to 2019, urban expansion in cities along the New Silk Road was significantly faster with an annual expansion rate of 339 km2 compared to 113 km2 in cities spatially distanced from the New Silk Roads. This trend did not exist before the year 2010.

Item Type:	Article
Uncontrolled Keywords:	Landsat, Remote Sensing, New Silk Road, Urbanization, GHSL
Subjects:	G Geography. Anthropology. Recreation > G Geography (General) G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography H Social Sciences > HD Industries. Land use. Labor Q Science > QA Mathematics > QA76 Computer software
Depositing User:	REAL CORP Administrator
Date Deposited:	27 Sep 2021 12:06
Last Modified:	17 Oct 2021 17:22
URI:	http://repository.corp.at/id/eprint/757

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