Sustainable Development Evaluation and Its Obstacle Factors of the Weihe River Basin in Shaanxi Province, China

Wang, Yirui; Song, Jinxi; Zhang, Xuexian; Sun, Haotian

doi:10.3389/feart.2021.744224

Cited by 8 publications

(7 citation statements)

References 52 publications

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“…However, urbanization and industrialization have increased the pressure on the eco-environment quality in the Weihe River Basin. In addition, soil erosion, serious water pollution, and ecological degradation limit the sustainable development of the study area [ 56 , 57 , 58 , 59 ]. The combined influence of multiple factors has accelerated the urgent need to improve the eco-environment quality in the Weihe River Basin.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Driving Factors of Remote Sensing Ecological Index Changes from the Perspective of Geospatial Differentiation: A Case Study of the Weihe River Basin, China

Zhang

Feng

Zhang

et al. 2022

IJERPH

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Using the Google Earth Engine (GEE) platform, Moderate-resolution image spectroradiometer (MODIS) data of the Weihe River Basin from 2001 to 2021 were acquired, four ecological indicators, namely, greenness, wetness, heat, and dryness, were extracted, and the remote sensing ecological index (RSEI) was constructed through principal component analysis. In addition, the geographic detectors and a multi-scale geographic weighted regression model (MGWR) were used to identify the main driving factors of RSEI changes and capture the differences in spatial changes from different perspectives using multiple indicators. The results show that (1) the quality of the eco-environment in the Weihe River basin improved as a whole from 2001 to 2021, and the RSEI increased from 0.376 to 0.414. In terms of the RSEI grade, the medium RSEI and high RSEI areas increased significantly and the growth rate increased significantly, reaching 26.42% and 27.70%, respectively. (2) Spatially, the quality of the eco-environment in the Weihe River Basin exhibited a spatial distribution pattern that was high in the south and low in the north, among which the quality of the eco-environment in the Weihe River Basin in northern Shaanxi and northwestern Ningxia and Gansu was relatively low. In addition, during the study period, the RSEI of the Qinling Mountains in the southern part of the Weihe River Basin and the Jinghe River and Luohe River areas improved significantly. The urban area on the Guanzhong Plain in the Weihe River Basin experienced rapid economic growth, and urban expansion led to a significant decrease in the quality of the eco-environment. (3) The eco-environment quality in the Weihe River Basin is the result of the interaction of natural, anthropogenic, and landscape pattern factors. All of the interactions between the influencing factors had a stronger influence than those of the individual factors. There were significant differences between the individual drivers and the spatial variation in RSEI, suggesting that different factors dominate the variation in RSEI in different regions, and zonal management is crucial to achieving sustainable management of RSEI. The study shows that to improve the eco-environment quality of the Weihe River Basin, it is necessary to further strengthen ecological protection projects, reasonably allocate landscape elements, and strengthen the resistance and resilience of the ecosystem.

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Section: Introductionmentioning

confidence: 99%

Exploring the Driving Factors of Remote Sensing Ecological Index Changes from the Perspective of Geospatial Differentiation: A Case Study of the Weihe River Basin, China

Zhang

Feng

Zhang

et al. 2022

IJERPH

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“…We introduced the obstacle degree model to examine the obstacle indicators to determine the direction of enhancing green transformation to understand the influence of various indicators on green development. The obstacle degree model is a frequently used mathematical statistical model for a thorough assessment of ecological resources and the environment [21] [6] . The obstacle degree is calculated by formulas (16) and (17) .…”

Section: Methodsmentioning

confidence: 99%

Green development level assessment and obstacle analysis of China's coal-resource-based regions

Chun,

Zhang,

Han

2023

Heliyon

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“…The difference between 1 and

indicates the difference between the actual value of the index and the optimal value. w j is the weight of the index ( 64 , 65 ).…”

Section: Methodology and Datamentioning

confidence: 99%

Coupling coordination analysis of low-carbon development, technology innovation, and new urbanization: Data from 30 provinces and cities in China

Liu

2022

Front. Public Health

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Technology innovation capability as an endogenous driving force plays an increasingly important role in the low-carbon transformation of new urbanization. This paper's purpose is to delve into the coupling coordination relationship among the three variables, and promote system's and region's synergy development. Based on the coupling coordination degree model, spatial autocorrelation model and obstacle degree model, this paper investigated the coupling coordination of low-carbon development (LCD) quality, technology innovation (TI) capability and new urbanization (NU) level in China from 2009 to 2019. The results indicate: (1) The coupling coordination degree (CCD) of LCD quality, TI capability and NU level in all regions of the country were fluctuating for a long time, and the regions that reach the coordinated development level showed a slow rising trend with obvious regional differences. (2) Three subsystems' CCD showed significant spatial correlation characteristics, and the degree of spatial agglomeration was constantly increasing. (3) The obstacles affecting the systems' synergy mainly reflected in economic and social indexes. In the end, this paper proposed that policy coordination and linkage should be strengthened, emphasizing the integrated development of the three subsystems. It is necessary to formulate development plans in combination with geographic location and resource endowment to enhance the regional driving effect.

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Sustainable Development Evaluation and Its Obstacle Factors of the Weihe River Basin in Shaanxi Province, China

Cited by 8 publications

References 52 publications

Exploring the Driving Factors of Remote Sensing Ecological Index Changes from the Perspective of Geospatial Differentiation: A Case Study of the Weihe River Basin, China

Exploring the Driving Factors of Remote Sensing Ecological Index Changes from the Perspective of Geospatial Differentiation: A Case Study of the Weihe River Basin, China

Green development level assessment and obstacle analysis of China's coal-resource-based regions

Coupling coordination analysis of low-carbon development, technology innovation, and new urbanization: Data from 30 provinces and cities in China

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