Spatial and Temporal Distribution Characteristics and Influential Mechanisms of China’s Industrial Landscape Based on Geodetector
Mi Yan,
Qingmiao Li and
Yan Song ()
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Mi Yan: School of Urban Economics and Public Administration, Capital University of Economics and Business, Beijing 100070, China
Qingmiao Li: School of Urban Economics and Public Administration, Capital University of Economics and Business, Beijing 100070, China
Yan Song: Department of City and Regional Planning, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
Land, 2024, vol. 13, issue 6, 1-23
Abstract:
The industrial landscape constitutes a crucial aspect of a region’s historical and cultural identity, serving as a valuable asset in the development of industrial tourism. Exploring the industrial landscape supports initiatives in industrial tourism, acts as a catalyst for community revitalization, and contributes to sustainable urban progress. The primary objective of this research was to investigate the spatial distribution characteristics and underlying determinants of China’s industrial landscape (CIL) to inform urban planning, cultural heritage preservation, and sustainable development initiatives. This study utilized analytical tools, such as the nearest neighbor index, geographic concentration index, and hot spot analysis, to comprehensively examine the spatial distribution of CIL. Additionally, Geodetector was employed to explore the correlating factors behind this distribution. The findings reveal the following: (1) CIL exhibited a pronounced agglomerative spatial pattern characterized by a high degree of concentration, significant disparities, and substantial spatial autocorrelation. (2) Over time, the agglomeration of CIL varied, intensifying initially and then diminishing, with the center of gravity of its distribution shifting eastward before subsequently moving westward in a directional trend resembling “northeast–southwest”. (3) There was a diverse array of industrial landscape types within China, with notable disparities in the prevalence of different categories. The manufacturing and transportation sectors boasted the highest number of heritage sites. (4) The distribution pattern of CIL was shaped by factors such as the level of economic development, socio-demographic conditions, transportation infrastructure, and cultural milieu. The interplay between these factors had a substantial impact on this distribution pattern.
Keywords: industrial landscape; influence mechanism; Geodetector; heritage protection; spatial–temporal patterns (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:13:y:2024:i:6:p:746-:d:1402395
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