Analysis of Spatial Patterns and Socioeconomic Activities of Urbanized Rural Areas in Fujian Province, China

Guo, Qinghai; He, Zhichao; Li, Dawei; Spyra, Marcin

doi:10.3390/land11070969

Cited by 6 publications

(3 citation statements)

References 53 publications

(79 reference statements)

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“…The influence of the proliferation of these traditionally developed cities predicts a significant growth trend in the future [82]. Concurrently, most regions in Xiamen, Fuzhou, Quanzhou, Zhangzhou, and Putian in Fujian also exhibit an upward trend, demonstrating the pattern of urban cluster development [83]. Thus, for these cities showing a clear increasing trend, we predict a persistent advancement of the urbanization process.…”

Section: Spatiotemporal Variation Characteristics Of Nighttime Light ...mentioning

confidence: 71%

Spatiotemporal Characteristics of Urbanization in the Taiwan Strait Based on Nighttime Light Data from 1992 to 2020

Yun

et al. 2023

Remote Sensing

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Urbanization is a crucial indicator which reflects the socio-economic development of a country or region. The regions across the Taiwan Strait (TSR) have garnered attention worldwide as being representative of typical urbanization development along the southeastern coast. Currently, research in the TSR predominantly focuses on individual regions, with limited academic achievements comparing urbanization paths across the strait. In particular, the domain of comparative analysis of the spatiotemporal characteristics of urbanization dynamics in TSR by using long time series of nighttime light data remains largely underexplored. Therefore, this study focused on comparing the urbanization paths in the TSR and analyzing the spatiotemporal characteristics of urbanization by using the long-term nighttime light data from 1992 to 2020. Additionally, some methods such as Theil–Sen median trend analysis, Mann–Kendall significance test, Hurst exponent, spatial statistics, and time series were used to quantitatively analyze the spatial distribution patterns and temporal trends of nighttime lights in the TSR since 1992. The results were as follows: (1) From 1992 to 2020, the spatial distribution of nighttime light data in TSR exhibited significant spatial heterogeneity, with high-value areas mainly located in southeastern Fujian and northwestern Taiwan, while low-value areas were concentrated in Fujian’s inland regions; (2) During this period, nighttime lighting data increased from 729,863 in 1992 to 2,729,052 in 2020, and the percentage of its high-value (40–063) increased from 2.59% in 1992 to 12.22% in 2020; (3) Comparison of nighttime light data across representative cities from Taiwan (Taipei, Hsinchu) and Fujian (Xiamen, Fuzhou) uncovered distinct growth patterns—while Taiwanese cities had a high initial brightness value (the lowest value in the last 30 years was 518,379.4), their growth was relatively slow (average growth rate of 17%); Fujian cities, on the other hand, started from lower initial brightness value (the lowest value in the last 30 years was 35,123.1), but displayed substantial growth vigor (average growth rate of 222%); (4) During the study period, the nighttime light data of the vast majority of cities in the TSR demonstrated a significant increasing trend, particularly in coastal areas and urban centers; (5) Predictions of future trend variation suggest that the significantly increasing trend of cities surrounding Taiwan’s primary metropolitan areas will intensify, whereas metropolitan regions such as Keelung may witness a decline in future trend variations. However, only a mere 0.03% of the nighttime light data show a significant decreasing trend. Additionally, there are distinct differences in the urbanization development stages of the TSR. Fujian is currently undergoing rapid urbanization, while Taiwan’s urbanization has entered a stable stage. The study reveals that factors such as geographical location, natural resources, transportation infrastructure, population size, and industrial structure collectively influence the urbanization characteristics of the TSR. This research bears substantial significance for deepening the comprehension of the patterns and processes of urbanization development in the TSR and provides valuable insights for urban construction and development across the strait.

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Section: Spatiotemporal Variation Characteristics Of Nighttime Light ...mentioning

confidence: 71%

Spatiotemporal Characteristics of Urbanization in the Taiwan Strait Based on Nighttime Light Data from 1992 to 2020

Yun

et al. 2023

Remote Sensing

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“…The interest-tendencies model is used to classify the scenic water spots of the tourist city, and then a classification model for the scenic water spots is constructed. In order to ensure that the selected scenic water spots have the optimal spatial distribution, a spatial accessibility model for the scenic water spots in the tourist city is set up, and then the spatial accessibility intensity for each scenic spot is calculated [21][22][23][24][25][26]. Combining the classification of scenic water spots and the spatial accessibility intensities, scenic water spots that optimally match the tourists' interests, and have the strongest spatial accessibility intensities, can be recommended for tourists, and then the tourist spatial decision-making model is set up.…”

Section: Methodsmentioning

confidence: 99%

A Low-Carbon Decision-Making Algorithm for Water-Spot Tourists, Based on the k-NN Spatial-Accessibility Optimization Model

Zhou

Bao

et al. 2022

Water

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This study presents a low-carbon decision-making algorithm for water-spot tourists, based on the k-NN spatial-accessibility optimization model, to address the problems of water-spot tourism spatial decision-making. The attributes of scenic water spots previously visited by the tourists were knowledge-mined, to ascertain the tourists’ interest-tendencies. A scenic water-spot classification model was constructed, to classify scenic water spots in tourist cities. Then, a scenic water spot spatial-accessibility optimization model was set up, to sequence the scenic spots. Based on the tourists’ interest-tendencies, and the spatial accessibility of the scenic water spots, a spatial-decision algorithm was constructed for water-spot tourists, to make decisions for the tourists, in regard to the tour routes with optimal accessibility and lowest cost. An experiment was performed, in which the tourist city of Leshan was chosen as the research object. The scenic water spots were classified, and the spatial accessibility for each scenic spot was calculated; then, the optimal tour routes with optimal spatial accessibility and the lowest cost were output. The experiment verified that the tour routes that were output via the proposed algorithm had stronger spatial accessibility, and cost less than the sub-optimal ones, and were thus more environmentally friendly.

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“…However, previous studies that explicitly stated that spatial changes in the village could have a significant impact on changes in rural communities' lifestyles had not been conducted (Mutunga 2018). Previous research has shown that climate change (Ajani & van der Geest 2021), globalization, modernization, technology (Hidayah 2017, Babbage et al 2020, and urbanization are all influencing changes in rural communities' lifestyles (Guo et al 2022, Raj & Shekhar 2022.…”

Section: Introductionmentioning

confidence: 99%

Lifestyle changes in rural communities through spatial reproduction practices: A case study in Madiun Regency

Damayanti

Egalita

2023

JSD

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The production of space in rural areas as a result of modernization changes lifestyles not only within families but also at a broader level, namely between communities. This study aimed to examine how spatial reproduction occurs in villages in Madiun Regency by identifying the dominant agent and the stages of the process of spatial reproduction. This study employed qualitative methods. This study found that there are four stages in the spatial reproduction process in Madiun Regency, including outreach, coordination, mutual cooperation, and synergy. These four stages occurred because of the presence of the village head as the initiating agent and Village Owned Enterprises (BUMDes) and the Tourism Awareness Group as organizations that oversee various community activities in the tourism sector. According to the findings of this study, technology has accelerated the process of spatial reproduction, which is reflected in the existence of four regionalizations, including economic, social, housing, and public services. This study concludes that the reproduction of space does not always lead to conflict and social inequality in society. On the contrary, people are able to work together in building shared prosperity with the value of mutual cooperation.

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Analysis of Spatial Patterns and Socioeconomic Activities of Urbanized Rural Areas in Fujian Province, China

Cited by 6 publications

References 53 publications

Spatiotemporal Characteristics of Urbanization in the Taiwan Strait Based on Nighttime Light Data from 1992 to 2020

Spatiotemporal Characteristics of Urbanization in the Taiwan Strait Based on Nighttime Light Data from 1992 to 2020

A Low-Carbon Decision-Making Algorithm for Water-Spot Tourists, Based on the k-NN Spatial-Accessibility Optimization Model

Lifestyle changes in rural communities through spatial reproduction practices: A case study in Madiun Regency

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