Review of the evaluation methods of regional eco-environmental vulnerability

Xueling, 张学玲 Zhang; Wenbo, 余文波 Yu; Haisheng, 蔡海生 Cai; Xiaomin, 郭晓敏 Guo

doi:10.5846/stxb201708211502

Cited by 8 publications

(9 citation statements)

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“…Although many experts have carried out substantial research on ecological vulnerability in recent years, the following problems still remain: (1) there is a lack of innovation in research methods; (2) a single index is used, which renders realizing ecological vulnerability evaluation difficult; (3) the effectiveness of the evaluation results is greatly influenced by subjective factors; and (4) there is a lack of rationality analysis of the evaluation results [44]. Based on the PSR and VSD models, this study innovatively constructed the ESSR model "Exposure-Sensitivity-state-Response".…”

Section: The Rationality Of the Essr Urban Green-space System's Ecolo...mentioning

confidence: 99%

Ecological Vulnerability Assessment and Spatiotemporal Characteristics Analysis of Urban Green-Space Systems in Beijing–Tianjin–Hebei Region

Fu,

Liu

2024

Sustainability

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The evaluation and analysis of the ecological vulnerability of urban green-space systems are conducive to the sustainable development of urban green-space systems. Taking the urban green-space system in the Beijing–Tianjin–Hebei region in 2010, 2015, and 2020 as the research object, an ESSR model was first constructed, and a total of ten types of impact factors were integrated into the four dimensions of “Exposure, Sensitivity, State and Response”. The weight of the impact factors was objectively determined via spatial principal component analysis, and the ecological vulnerability of the urban green-space system was evaluated via superposition analysis; the evaluation’s results were graded. Moreover, the transfer matrix, center-of-gravity migration model, standard deviation ellipse, and spatial autocorrelation analysis were used to study the temporal and spatial variation characteristics of the evaluation results; then, the driving force of impact factors was analyzed based on a geographical detector. Finally, the rationality of the evaluation results was verified using the changing trend of the remote sensing ecological index (RSEI). The results show that the ecological vulnerability of the urban green-space system in the Beijing–Tianjin–Hebei region has decreased year by year for the past ten years. The distribution law of “Hebei surrounds Beijing and Tianjin” is presented in this space, and 2015 is the mutation node. In 2010, the moderately and severely vulnerable areas of Hebei surrounded the mildly vulnerability areas of Beijing and Tianjin. Moreover, in 2015 and 2020, the mildly vulnerable areas of Hebei surrounded the severely vulnerable areas of Beijing and Tianjin. Vulnerability expands slightly in the east–west direction and shrinks slightly in the north–south direction, and the center of gravity shifts towards Beijing year by year along the northeast direction. Moreover, the spatial distribution of vulnerability shows significant positive spatial autocorrelations and exhibits very obvious agglomeration. In addition, vulnerability is the result of the combined effect of various factors, and education degree, human disturbance index, and annual average precipitation are the dominant factors. The analysis results provide a reference for the effective application and sustainable development of urban green-space ecological functions.

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Section: The Rationality Of the Essr Urban Green-space System's Ecolo...mentioning

confidence: 99%

Ecological Vulnerability Assessment and Spatiotemporal Characteristics Analysis of Urban Green-Space Systems in Beijing–Tianjin–Hebei Region

Fu,

Liu

2024

Sustainability

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“…The comprehensive index weighted by greenness, wetness, dryness, and heat can not only overcome the disadvantages of using a single index, but also makes the integration of each subindex more reasonable. In addition, the index weights were objectively determined using PCA, which can reduce the uncertainty caused by human factors and avoid the ecological vulnerability caused by the subjective weight setting [2,33,62,91,92].…”

Section: Limitations and Future Trendsmentioning

confidence: 99%

“…Global change and the intensification of human activity have a significant impact on the ecosystems [1]. With the increasing concerns on the global environmental change, ecological fragile belts and ecological vulnerability and its impact factors have become global research topics [2,3]. Ecological vulnerability assessments and spatial correlations reveal the spatial and temporal characteristics of regional ecological vulnerability and have important practical significance for ecological and environmental protection, rational use of resources, and sustainable development [2,4].…”

Section: Introductionmentioning

confidence: 99%

“…The indicator system includes the systems of natural causes-result performance, influencing factors-performance factors-stress factors, and the natural-ecological-socioeconomic system [17]. Evaluation methods include the analytic hierarchy process (AHP) method [18], comprehensive index method [19], fuzzy mathematics method [20], principal component analysis (PCA) method [21], neural network method [22], entropy weight method [6], the method of landscape ecology [23], and the fuzzy matter-element evaluation method [2].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Ecological Vulnerability of Tourism Scenic Spots: Based on Remote Sensing Ecological Index

Shi¹,

Shi²,

Liu³

et al. 2021

Pol. J. Environ. Stud.

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The assessment of ecological vulnerability plays an important role in the protection and management of scenic tourism sites. In this study, using remote sensing image data in the same month of 2000 and 2017, ecological vulnerability in the Tianchi Scenic Area (TSA) was analyzed by calculating the remote sensing ecological index (RSEI), and the influencing factors of ecological vulnerability were detected using the geographical detector model. From 2000 to 2017, the values of wetness, dryness, and temperature in the study area increased, and the value of greenness and RSEI decreased. Spatial correlations of the RSEI were significant, showing strong spatial agglomeration and alternating cold spots-hot spots-cold spots-hot spots from north to south. The impact factors of land use type, temperature, and precipitation showed greater contribution to ecological vulnerability. In addition, the local government implemented policies such as prohibition of mining, grazing prohibition, and landscape protection, which decreased ecological vulnerability in the study area. This study provides a reference for the formulation of ecological vulnerability protection measures in the TSA and theoretical basis for defining the monitoring indicators for heritage sites around the world.

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“…The fierce global warming and human activities have had significant impacts on vegetation [1], and vegetation degradation is an important external expression of vulnerability [2]. Land use changes and intensified environmental pollution caused by human activities can both result in vegetation degradation [3,4] and further increase vegetation vulnerability.…”

Section: Introductionmentioning

confidence: 99%

Prediction and Transition of Vegetation Vulnerability in the Mara River Basin under Different Shared Socio-Economic Pathways (SSPs), East Africa

Zhu,

Zhang,

Feng

et al. 2024

Forests

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The Mara River basin (MRB) has a world-famous ecosystem, but the vegetation has been damaged due to economic development in recent years, and there is little known about the area that will experience severe vegetation damage in the future. Based on the vegetation vulnerability system, principal component analysis, and three Shared Socio-Economic Pathways (SSP1-2.6, SSP2-4.5, SSP5-8.5), vegetation vulnerability was calculated for the base period (2010–2019), near future period (2020–2059) and distinct future period (2060–2099) in the MRB. The spatial cluster of vegetation vulnerability was revealed by spatial correlation analysis, and the transition of vegetation vulnerability of different periods was analyzed by stochastic matrix. The results showed that for all periods, the vulnerability showed a high–high cluster in the east, and a low–low cluster midstream and downstream. From the stochastic matrix, the area of high vulnerability increased the least under the SSP1-2.6, while it increased the most under the SSP5-8.5. The vegetation vulnerability upstream increased the most from the base period to the near future period and distinct future period in the MRB. By comparing the vegetation vulnerability under different scenarios and pointing out the areas with the highest vulnerability increase, this study can better provide comprehensive decision-making for vegetation protection in the MRB.

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Review of the evaluation methods of regional eco-environmental vulnerability

Cited by 8 publications

References 0 publications

Ecological Vulnerability Assessment and Spatiotemporal Characteristics Analysis of Urban Green-Space Systems in Beijing–Tianjin–Hebei Region

Ecological Vulnerability Assessment and Spatiotemporal Characteristics Analysis of Urban Green-Space Systems in Beijing–Tianjin–Hebei Region

Ecological Vulnerability of Tourism Scenic Spots: Based on Remote Sensing Ecological Index

Prediction and Transition of Vegetation Vulnerability in the Mara River Basin under Different Shared Socio-Economic Pathways (SSPs), East Africa

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