Recognizing the transformation characteristics of resource-based cities using night-time light remote sensing data: Evidence from 126 cities in China

He, Tingting; Song, Haipeng; Chen, Wenqi

doi:10.1016/j.resourpol.2023.104013

Cited by 12 publications

(5 citation statements)

References 37 publications

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“…In this paper, the following variables are selected as control variables: 1 ⃝ Government intervention (GOV): the ratio of the general budget expenditure of local finance to GDP is used to reflect the degree of government intervention; 2 ⃝ population size (POP), which is characterized by the permanent urban resident population; 3 ⃝ environmental regulation (ENR), using the proportion of employees in water conservation, environment, and public facilities management in the total population; 4 ⃝ infrastructure (INF), which is characterized by the ratio of the urban road area to the total population; and 5 ⃝ market size (SIZ), which is characterized by the product of population per square kilometer and GDP per capita.…”

Section: Methods For the Analysis Of The Carbon Emission Reduction Ef...mentioning

confidence: 99%

“…The examination of transformation performance encompasses resourcebased transformation and digital-intelligent-service-oriented transformation. Research on resource-based transformation delves into the characteristics and evaluation of the transformation performance [4][5][6], carbon emission reduction effects [7], and dynamic assessments [8] of resource-based cities. Meanwhile, digital-intelligent-service-oriented transformation focuses on the influence of big data resources [9,10] and data empowerment [8,11] on transformation performance.…”

Section: Introductionmentioning

confidence: 99%

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Investigation into the Performance Characteristics of the Organic Dry Farming Transition and the Corresponding Impact on Carbon Emissions Reduction

Wang,

Zhao,

Zhao

2024

Agriculture

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Global warming affects food security and ecological security, and it threatens economic stability and sustainable agricultural development. The transformation and development of agriculture have significant implications for the achievement of the “dual-carbon” goals and the promotion of sustainable agricultural development. Based on panel data on organic dry farming in China from 2005 to 2020, this study aimed to comprehensively assess the transformation performance of organic dry farming (TRODF) in 15 provinces. It explored the impact of the transformation of organic dry farming on carbon emissions by utilizing a spatial Markov chain and spatial measurement models. Our findings are as follows: (1) The performance of the organic dryland agriculture transformation has gradually improved and is accompanied by a corresponding trend of fluctuating regional disparities, which are on the rise. Moreover, the disparities between the five major regions mainly stem from intra-regional differences. (2) TRODF agriculture presents the possibility of state transfer during different periods, featuring four convergent zones: a lagging zone, a starting zone, a crossing zone, and an advanced zone. The spatial Markov chain indicates that state transitions typically occur between adjacent levels, with fewer instances of “jump”-type transitions. Moreover, there is a clear trend of differentiation in the state transitions between non-adjacent areas. (3) The organic dry farming transformation exhibits a significant carbon reduction effect, which is characterized by heterogeneity across different stages of agricultural development, provinces, and time periods. This study emphasizes that economic and industrial transformation, along with the transformation of the ecological environment, represents a crucial direction for conserving resources and achieving a further reduction in carbon emissions.

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Section: Methods For the Analysis Of The Carbon Emission Reduction Ef...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Investigation into the Performance Characteristics of the Organic Dry Farming Transition and the Corresponding Impact on Carbon Emissions Reduction

Wang,

Zhao,

Zhao

2024

Agriculture

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“…We selected indicators that are relevant to the transformation of the Northeast Stateowned Forest Areas based on scientific rigor, practicality, comprehensiveness, representativeness, operability, and data availability. The indicators selected originate from well-established frameworks, including the modern forestry development index system [51][52][53][54][55][56], economic transformation index system [57][58][59], resource-based city transformation ability index system [60][61][62], and transformation index system of state-owned forest areas [3,[6][7][8]10,36,37,63], as suggested by several scholars. The indicators are organized based on three characteristics that reflect the capacity of state-owned forestlands to undergo change.…”

Section: Descriptive Statisticsmentioning

confidence: 99%

Calculation and Cause Analysis of Hidden Unemployment—A Case Study of the Northeast State-Owned Forest Areas in China

Wang,

Cao,

Wen

2024

Sustainability

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The Northeast State-owned Forest Areas comprise the largest region of resources in China. The transformation of the Northeast State-owned Forest Areas is due to various stimuli, such as policies, systems, and markets. In the context of ecological construction and the reform of the state-owned forest system in Northeast China, these have undergone a transformation in terms of economy, society, and ecology. However, a mismatch persists between employment and industrial structures, leading to hidden unemployment. This study employs the framework of hidden unemployment theory, utilizing the Cobb–Douglas production function to quantify the hidden unemployment rate, revealing the relationship between transformation and hidden unemployment. Through this analysis, the underlying causes of hidden unemployment in Northeast China’s state-owned forest regions are scrutinized. There is a bidirectional causal relationship between ecological transformation and hidden unemployment, while there is a unidirectional causal relationship between economic transformation and hidden unemployment. Variance decomposition analysis highlights the substantial contribution of social transformation, followed by economic transformation, with ecological transformation playing a comparatively smaller role. Based on the above research, this article proposes expediting the reforms within the forest industry groups, facilitating the separation of governmental and corporate interests. Additionally, it advocates for strategic forestry development planning to effectively absorb surplus labor, and proposes three policy directives aimed at supporting forest area employees, including provisions for job transfers and reemployment opportunities.

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“…Academic research on this issue focuses on the impact of changes in the land use structure and layout of resource-based cities on the ecological environment 33 , sustainable development 34 , multifunctional carrying capacity 35 , urban security elasticity 36 , and other aspects. Tingting He et al used nighttime light remote sensing data to identify the transformation of spatial patterns in resource-based cities in China and found that the land use expansion of most resource-based cities has been shrinking in recent years 37 . When monitoring the surface temperature of resource cities, Wei Chen et, al.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Chinese land spatial pattern in the transformation process of resource-based cities: a case study in Tongling City, China

Ye,

Qin,

et al. 2024

Sci Rep

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Optimizing the spatial layout of the national territory is crucial for realizing the transformation and development of resource-oriented cities in the context of high-quality development in the new period. This paper takes Tongling City as a case study, based on the analysis of the historical development foundation, then uses the SD-FLUS comprehensive model to carry out a systematic analysis of the transformation in five dimensions of economy, society, population, science and technology, resources and environment, and discusses the optimization of spatial pattern under the contextual simulation. The conclusions are as follows: ① The hierarchical framework of “system-indicator-element” is not only internally interconnected, but also inextricably linked with the relationship between the various categories of the land use system. ② Decrease of cropland, forest, water, grassland, and barren decreases from the economic development, social progress, and comprehensive development, and there is a small increase in the area under the scenario of resource and environmental protection, and the direction of the change of the impervious is in the opposite direction. ③ Cultivated land is retained in situ and concentrated to a small extent, forested land is reduced to a small extent while the status quo is maintained, and the Yangtze River water system will be retained and protected to a large extent, but part of the waters of Zongyang County will give way to the expansion of construction land under the development objectives of the new county. Building land will be expanded and extended to the northeast in the original site area, while the southwest corner of the original county center will be expanded to some extent in Zongyang County to promote the county’s economic development.

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Recognizing the transformation characteristics of resource-based cities using night-time light remote sensing data: Evidence from 126 cities in China

Cited by 12 publications

References 37 publications

Investigation into the Performance Characteristics of the Organic Dry Farming Transition and the Corresponding Impact on Carbon Emissions Reduction

Investigation into the Performance Characteristics of the Organic Dry Farming Transition and the Corresponding Impact on Carbon Emissions Reduction

Calculation and Cause Analysis of Hidden Unemployment—A Case Study of the Northeast State-Owned Forest Areas in China

Optimization of Chinese land spatial pattern in the transformation process of resource-based cities: a case study in Tongling City, China

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