Evaluation of urban comprehensive carrying capacity: case study of the Beijing–Tianjin–Hebei urban agglomeration, China

Zhao, Lingling; Shao, Qinglong

doi:10.1007/s11356-020-08463-3

Cited by 21 publications

(18 citation statements)

References 15 publications

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“…The entropy method determines the weight according to the degree of change in the original index data. As an objective weighting method, it avoids the shortcomings of the index weight tending to the subjective consciousness of the evaluators from weighting methods such as the analytic hierarchy process (AHP) and the Delphi method (Zhao et al 2020a;Yang et al 2020). The TOPSIS method was first proposed by Hwang and Yoon (1981).…”

Section: Topsis Model Based On Entropy Weightmentioning

confidence: 99%

Comprehensive partitions and optimisation strategies based on tourism urbanisation and resources environment carrying capacity in the Yellow River Basin, China

Wang

Chen

2021

Environ Sci Pollut Res

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Section: Topsis Model Based On Entropy Weightmentioning

confidence: 99%

Comprehensive partitions and optimisation strategies based on tourism urbanisation and resources environment carrying capacity in the Yellow River Basin, China

Wang

Chen

2021

Environ Sci Pollut Res

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“…After the scholars have continuously enriched the definition of RECC, they have begun to study methods and models. At present, the evaluation methods of RECC mainly include entropy method and analytic hierarchy process (Zhao et al 2020, Jayanthi et al 2020, Diao et al 2019, strategic environmental assessment, and environmental impact assessment (Martinez-Grana et al 2014), ecological footprint method (Volodya et al 2018), fuzzy evaluation method (Yin et al 2020) (Cui et al 2019), logistic growth model (Streimikiene and Girdzijauskas 2008), artificial neural network model (Wu et al 2019, state-space model (Tang et al 2016), dynamic modeling (Lane et al 2014) and other models are used to evaluate the status quo and predict the future of RECC. The entropy-weight-based TOPSIS method has high credibility and accuracy and avoids the subjectivity of weight determination (Li et al 2019).…”

Section: Interactive Framework Of Reccmentioning

confidence: 99%

Temporal and Spatial Evolution and Obstacle Diagnosis of Resource and Environment Carrying Capacity in the Loess Plateau

Huang

Wang

et al. 2021

Preprint

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In the Loess Plateau, natural resources are scarce and the ecological environment is fragile. Sustainable development requires special attention paid to resource and environmental carrying capacity (RECC). This paper selects 24 representative cities in five natural areas of the Loess Plateau, uses the entropy-weight-based TOPSIS method to evaluate and analyze the RECC of each city and region from 2013 to 2018, establishes a diagnosis model to identify the obstacle factors restricting the improvement of RECC and constructs the theoretical framework of RECC' system mechanism. Results show that the RECC of Loess Plateau is increasing in general but relatively small. The environmental and social subsystem have the highest and lowest carrying capacity respectively. There is an obvious contradiction between economic development and the environment. Population density, investment in technological innovation, per capita sown area of crops, and per capita water resources are the main obstacles affecting the improvement of RECC in the Loess Plateau. Such evaluation and diagnosis could support ecological civilization and sustainable development.

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“…At present, the main evaluation methods for resource and environmental sustainability are environmental impact assessment [ 30 ], ecological footprint method [ 31 ], emergy analysis [ 32 , 33 ], and cluster analysis [ 34 , 35 ]. The main methods for determining the weight of the RECC index system are entropy method and analytic hierarchy process [ 36 – 38 ]. The entropy-weight-based TOPSIS method has high credibility and accuracy, and avoids the subjectivity of weight determination [ 39 ].…”

Section: Interactive Framework Of Reccmentioning

confidence: 99%

Temporal and spatial evolution and obstacle diagnosis of resource and environment carrying capacity in the Loess Plateau

Huang

Wang

et al. 2021

PLoS ONE

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Natural resources are scarce in the Loess Plateau, and the ecological environment is fragile. Sustainable development requires special attention to resource and environmental carrying capacity (RECC). This study selected 24 representative cities in five natural areas of the Loess Plateau; used the entropy-weight-based TOPSIS method to evaluate and analyze the RECC of each city and region from 2013 to 2018; established a diagnosis model to identify the obstacle factors restricting the improvement of RECC; and constructed the theoretical framework of the RECC system mechanism. The results show that the RECC of the Loess Plateau is increasing in general but is relatively small. The environmental and social subsystems have the highest and lowest carrying capacities, respectively. There is an evident contradiction between economic development and the environment. Population density, investment in technological innovation, per capita sown area, and per capita water resources are the main obstacles affecting the improvement of RECC in the Loess Plateau. Such evaluations and diagnoses can support ecological civilization and sustainable development.

show abstract

Evaluation of urban comprehensive carrying capacity: case study of the Beijing–Tianjin–Hebei urban agglomeration, China

Cited by 21 publications

References 15 publications

Comprehensive partitions and optimisation strategies based on tourism urbanisation and resources environment carrying capacity in the Yellow River Basin, China

Comprehensive partitions and optimisation strategies based on tourism urbanisation and resources environment carrying capacity in the Yellow River Basin, China

Temporal and Spatial Evolution and Obstacle Diagnosis of Resource and Environment Carrying Capacity in the Loess Plateau

Temporal and spatial evolution and obstacle diagnosis of resource and environment carrying capacity in the Loess Plateau

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