Spatial scanning of traditional villages and geographical exploration of spatial differentiation mechanism: a case study of Gansu Province

Jin, Jianglei; Yan, Haowen; Wang, Guigang; Su, Gazangjia

doi:10.1109/ieeeconf54055.2021.9687633

Cited by 4 publications

(8 citation statements)

References 7 publications

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“…In our specific study, we conducted a statistical analysis using ArcGIS to quantify the distribution characteristics of industrial heritage [34]. Additionally, we identified the influencing factors of Italy's industrial heritage through information collected from databases [87]. This systematic review aids in a clearer understanding of the features of Italy's industrial heritage, thereby supporting further efforts to promote its preservation and management.…”

Section: Discussionmentioning

confidence: 99%

Geographic Distribution Characteristics and Influencing Factors for Industrial Heritage Sites in Italy Based on GIS

Fan,

Sun

2024

Sustainability

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A comprehensive understanding of industrial legacy, considering its social, economic, and environmental aspects, is crucial for its preservation. This study scrutinizes 120 industrial heritage sites, investigating spatial–temporal patterns and influential factors. The aim is to provide a scientific basis for the conservation and management of the Italian industrial heritage. (1) The research underscores Italy’s industrial legacy’s tendency for clustering and uneven dispersion, prominently concentrated in the northern regions while notably sparse in the south. (2) Geographical advantages, a history of advanced industrialization, higher economic levels, greater population density, and supportive policies foster a concentration of industrial development and greater diversity of heritage types in the North. (3) The recommendations advocate for tailored conservation and management strategies tailored to the distinct characteristics of Italian industrial history. These strategies advocate for increased public involvement, reinforced legislative protection, and the promotion of tourism and cultural education to sustainably develop heritage assets. The findings and methodologies of this study can effectively identify the causes of the formation of the Italian industrial heritage, thereby offering a broader perspective to bolster its preservation and administration. It also provides a valuable reference for global industrial heritage preservation and management strategies.

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Section: Discussionmentioning

confidence: 99%

Geographic Distribution Characteristics and Influencing Factors for Industrial Heritage Sites in Italy Based on GIS

Fan,

Sun

2024

Sustainability

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“…The ArcGIS Kernel Density tool was applied to generate the overall kernel density map of the heritage [28,29], see Figure 5. The degree of aggregation was categorized into four levels according to the Jenks optimization method: high aggregation (kernel density of eight levels), medium aggregation (kernel density of six levels), average aggregation (kernel density of four levels), and low aggregation (kernel density of two levels).…”

Section: Spatial Agglomeration 421 Overall Spatial Clustering Of Heri...mentioning

confidence: 99%

Research on the Spatiotemporal Distribution of Railway Architectural Heritages Based on Heritage Database—Taking the Jinqin Section of the Peking–Mukden Railway as an Example

Liu,

Lu,

Wang

2024

Sustainability

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This research analyzes the development and evolution of the Jinqin section of Peking–Mukden railway. Based on defining the scope of the study, the project to make “The List of Architectural Heritage of Jinqin section in Peking–Mukden Railway” is proposed. Data acquisition, data processing, and heritage information visualization are completed after the survey. ArcGIS was applied to build the database, which was used to analyze the spatiotemporal distribution. The following conclusions were obtained after analyzing spatial distribution characteristics, spatial agglomeration, and spatial equilibrium: ① The overall spatial distribution of architectural heritage is characterized by significant “cohesion”, while the three major categories of heritage in three time sections show obvious spatial distribution direction. ② The integral architectural heritage is characterized by an agglomeration pattern of six points connected by railway. ③ Both the integral heritage and the three major categories have a large gap in distribution, a low degree of balance, and a high degree of agglomeration. The research can support the study of regional protection strategy and sustainable use of railway architectural heritage.

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“…The geodetector is a quantitative method used to determine whether a geographical factor influences the spatial distribution of a given index and its weight [44]. This test evaluates the effectiveness of the evaluation index X on the dependent variable Y and can be quantified using the index QD and H. The higher the value, the greater the influence of the influencing factors and vice versa.…”

Section: The Geographical Concentration Coefficient Analysismentioning

confidence: 99%

“…. L. Nh and N represent the elements of layer h and the whole region, respectively [44]. The variances of the Y values of stratum h and the whole region are represented by σ 2 h and σ 2 [39].…”

Section: The Geographical Concentration Coefficient Analysismentioning

confidence: 99%

“…The paper uses a macro perspective and quantitative analysis to present a data-based analysis of traditional villages in Hebei Province by presenting a study of 206 traditional villages in Hebei Province [44], analysing their spatial distribution and the mechanisms that influence it [19]. The evolution of the spatial distribution of traditional villages is found to follow a clear pattern of aggregation in different periods [48], from the Pre-Qin to the Song-Liao-Jin, forming a concentrated core area of Shijiazhuang, Zhangjiakou and Xingtai-Handan.…”

Section: Overall Spatial Distribution Of Traditional Villages In Hebe...mentioning

confidence: 99%

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GIS-Based Analysis of the Spatial Distribution and Influencing Factors of Traditional Villages in Hebei Province, China

et al. 2023

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Traditional villages are a valuable cultural asset that occupy an important position in Chinese traditional culture. This study focuses on 206 traditional villages in Hebei Province and aims to explore their spatial distribution characteristics and influencing factors using ArcGIS spatial analysis. The analysis shows that traditional villages in Hebei Province were distributed in clusters during different historical periods, and eventually formed three core clusters in Shijiazhuang, Zhangjiakou and Xingtai-Handan after different historical periods. Moreover, the overall distribution of traditional villages in Hebei Province is very uneven, with clear regional differences, and most of them are concentrated in the eastern foothills of the Taihang Mountains. To identify the factors influencing traditional villages, natural environmental factors, socio-economic factors, and historical and cultural factors are considered. The study finds that socio-economic and natural environmental factors alternate in the spatial distribution of traditional villages in Hebei Province. The influence of the interaction of these factors increases significantly, and socio-economic factors have a stronger influence on the spatial distribution. Specifically, the spatial distribution of traditional villages in Hebei Province is influenced by natural environmental factors, while socio-economic factors act as drivers of spatial distribution. Historical and cultural factors act as catalysts of spatial distribution, and policy directions are external forces of spatial distribution. Overall, this study provides valuable insights into the spatial distribution characteristics and influencing factors of traditional villages in Hebei Province, which can be used to develop effective strategies for rural revitalisation in China.

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Spatial scanning of traditional villages and geographical exploration of spatial differentiation mechanism: a case study of Gansu Province

Cited by 4 publications

References 7 publications

Geographic Distribution Characteristics and Influencing Factors for Industrial Heritage Sites in Italy Based on GIS

Geographic Distribution Characteristics and Influencing Factors for Industrial Heritage Sites in Italy Based on GIS

Research on the Spatiotemporal Distribution of Railway Architectural Heritages Based on Heritage Database—Taking the Jinqin Section of the Peking–Mukden Railway as an Example

GIS-Based Analysis of the Spatial Distribution and Influencing Factors of Traditional Villages in Hebei Province, China

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