Asset Details
Do you wish to reserve the book?
Spatial Distribution and Influencing Factors of Industrial Heritage in Hebei Province: An Integration of GeoDetector and Geographically Weighted Regression
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Spatial Distribution and Influencing Factors of Industrial Heritage in Hebei Province: An Integration of GeoDetector and Geographically Weighted Regression
Do you wish to request the book?
Spatial Distribution and Influencing Factors of Industrial Heritage in Hebei Province: An Integration of GeoDetector and Geographically Weighted Regression
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Spatial Distribution and Influencing Factors of Industrial Heritage in Hebei Province: An Integration of GeoDetector and Geographically Weighted Regression
2026
Overview
Industrial heritage, as a vital carrier of industrial civilization, is a key resource for advancing regional sustainable development. Understanding its spatial distribution and influencing factors is essential for effective conservation and revitalization. This study examines 207 industrial heritage sites in Hebei Province, one of the birthplaces of modern industry in China. By integrating multiple spatial analytical methods, it explores the spatial patterns and influencing factors of industrial heritage. A progressive analytical framework combining GeoDetector, Ordinary Least Squares, and Geographically Weighted Regression models was established to interpret formation mechanisms from factor identification to global and local heterogeneity. Results show that industrial heritage in Hebei forms high-density clusters along the eastern coast and southwestern hinterland, with lower densities in the north and central regions. The spatial centroid shifted from the center to the northeast, then to the southwest, and finally returned to the center. The distribution is shaped by the synergistic interaction of multiple factors: railway networks exert the strongest influence, natural conditions provide fundamental constraints, cultural factors play a reinforcing role, and historical development and policy orientation act as regulatory forces. Region-specific strategies are proposed to guide the conservation and sustainable transformation of industrial heritage in old industrial cities.
Publisher
MDPI AG
Subject
