Evaluation of ecological space and ecological quality changes in urban agglomeration on the northern slope of the Tianshan Mountains

Aizizi, Yimuranzi; Kasimu, Alimujiang; Liang, Hongwu; Zhang, Xueling; Zhao, Yongyu; Wei, Bohao

doi:10.1016/j.ecolind.2023.109896

Cited by 41 publications

(16 citation statements)

References 46 publications

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“…This study considered four key categories of data as drivers of land use change, including geomorphic data (DEM and slope), climate data (temperature and precipitation), spatial accessibility (distance to the road), and socio‐economic data (GDP and population). To enhance computational efficiency, the LULC data were resampled to a 90 m spatial resolution (Wei, Kasimu, Reheman, et al, 2023). Simultaneously, to ensure consistency in spatial accuracy, a series of preprocessing steps including clipping and resampling were performed using ArcGIS software.…”

Section: Methodsmentioning

confidence: 99%

Research on habitat quality in arid urban agglomerations: Influencing mechanisms and multi‐scenario simulations

Han,

Zheng,

Han

et al. 2024

Land Degrad Dev

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In the context of climate change and rapid urbanization, there have been unparalleled changes in land use and land cover (LULC), resulting in substantial impacts on the surrounding habitat quality (HQ), particularly in ecologically vulnerable arid regions. However, previous studies on the influencing mechanisms of HQ in arid urban agglomerations and future multi‐scenario simulations remain limited. To fill this knowledge gap, this study aimed to reveal the influencing mechanisms in HQ changes and to develop a multi‐scenario HQ assessment framework within arid urban agglomerations. We assessed the spatiotemporal variations in HQ using the InVEST model and three periods of LULC data for the urban agglomeration on the northern slope of the Tianshan Mountains (UANSTM), and the partial least squares structural equation model was introduced to explore the interactions between natural and non‐natural factors and their impacts on HQ. Additionally, we coupled multi‐objective programming and PLUS models to predict the LULC under different optimization scenarios (natural development scenario (NDS), ecological protection scenario (EPS), ecological–economic coordinated scenario, and economic development scenario) for the UANSTM in 2030, and to assess HQ. Results show that (1) the HQ index of the UANSTM was 0.507, 0.520, and 0.495 in 2000, 2010, and 2020 respectively, with a spatial distribution pattern of high values in the west, low values in the east, and high in the central and low in the north and south; (2) geomorphic, climatic, and LULC factors have direct positive effects on HQ, while socio‐economic factors have a direct negative effect on HQ. In addition, geomorphic, socio‐economic, and climatic factors also influence HQ through potential indirect paths. Climatic and LULC factors enhance the positive effect of geomorphic on HQ while counteracting the direct negative effect of socio‐economic factors on HQ. Climatic factors have the largest negative effect on HQ through their influence on LULC; (3) according to the four scenarios in 2030, the highest HQ index (increased by 0.13%) was found under the EPS, which also aligns more closely with SDGs. Conversely, NDS showed the lowest HQ index (declined by 2.59%). The research results could provide a scientific basis for promoting sustainable land management and ecological conservation for the UANSTM.

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Section: Methodsmentioning

confidence: 99%

Research on habitat quality in arid urban agglomerations: Influencing mechanisms and multi‐scenario simulations

Han,

Zheng,

Han

et al. 2024

Land Degrad Dev

View full text Add to dashboard Cite

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“…The greenhouse effect, significantly driven by human activities, has emerged as the principal contributor to global warming over the past century, with carbon dioxide emissions at the forefront [ 1 ]. This relentless warming trend poses a formidable challenge to the sustainable development of societies worldwide [ 2 , 3 ]. As main carriers of human activities, the cities are deviating from sustainable development goals under the effect of urban heat islands (UHIs) [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

Studying regional low-carbon development: A case study of Sichuan Province in China

Sun,

Gao,

Liu

et al. 2024

PLoS ONE

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The unavoidable option for socially sustainable development is a low-carbon economy. One of the essential steps for China to attain high-quality development is reducing carbon emissions. It is necessary to realize low-carbon development in Sichuan, as it is not only an important economic zone but also an ecological protected area. The concurrent relationship among energy consumption, carbon emissions, and economic growth was examined in this study using the Tapio decoupling indicator, and the factors affecting energy consumption and carbon emissions in Sichuan were broken down using the logarithmic mean Divisia indicator (LMDI). The findings demonstrate a fundamental relative decoupling relationship between Sichuan’s energy use and carbon emissions. Analysis of energy consumption and carbon emissions in Sichuan Province from 2005 to 2020 shows distinct patterns. From 2005 to 2012, in 2014, and from 2016 to 2020, the relationship between energy use and carbon emissions was relatively decoupled, with decoupling values ranging between 0 and 1. Absolute decoupling occurred in specific years: 2010, from 2013 to 2018, and in 2020. These periods are characterized by economic growth alongside reductions in carbon emissions. Factors affecting energy consumption and carbon emissions were consistently analyzed, showing similar impacts throughout the study periods. We find that population and economic growth are the main driving forces of these effects. The effects of energy intensity and industrial structure mainly play restraining roles, and the latter has a slightly weaker effect than the former.

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“…However, most of the current studies on the expansion of artificial oases in Xinjiang have focused on the impact of factors such as population [26,27], economy [27], hydrological river network [20,28,29], and road traffic [4,30] on oasis development. There are fewer studies on geomorphological factors, and most of the existing studies face morphological and geomorphological constraints such as altitude [2,25,31], degree of slope [25,32], impact on the density of land use [33], and suitability assessment [34] level. Although the role of morphogenetically coupled geomorphological types in oasis development has been mentioned in relevant studies [9], research on the expansion dynamics of oasis development, including potential quantitative research on the geomorphologic coupling of land use and artificial oases, is still insufficient, while the degree of influence and the relationship between morphogenetic and geomorphological types on the development of artificial oases is not clear.…”

Section: Introductionmentioning

confidence: 99%

Study on the Expansion Potential of Artificial Oases in Xinjiang by Coupling Geomorphic Features and Hierarchical Clustering

Song,

Cheng,

Wang

et al. 2024

Remote Sensing

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The study of the expansion potential of artificial oases based on remote sensing data is of great significance for the rational allocation of water resources and urban planning in arid areas. Based on the spatio-temporal relationship between morphogenetic landform types and the development of artificial oases in Xinjiang, this study explored the development pattern of artificial oases in the past 30 years by using trend analysis and centroid migration analysis, constructing a series of landform–artificial oasis change indices, and investigating the suitability of different landforms for the development of artificial oases based on geomorphological location by adopting a hierarchical clustering method. The following conclusions are drawn: (1) From 1990 to 2020, the area of artificial oases in the whole territory continued to increase, with significant expansion to the south from 2005 to 2010. (2) Six categories of landform types for artificial oasis development were created based on the clustering results. Of these, 7.39% and 6.15% of the area’s geomorphological types belonged to the first and second suitability classes, respectively. (3) The optimal scale for analyzing the suitability of landforms for the development of artificial oases over the past 30 years in the whole area was 8 km, which could explain more than 96% of the changes in the growth of artificial oases. The distribution of landforms of first- and second-class suitability within the 8 km buffer zone of an artificial oasis in the year 2020 was 10.55% and 9.90%, respectively, and landforms of first-class suitability were mainly concentrated in the near plain side of the urban agglomerations located on the northern and southern slopes of the Tianshan Mountains, and the urban agglomerations at the southern edge of Altai Mountains. This study quantified the potential of different geomorphological types for the development of artificial oases and provided a basis for site selection in future artificial oasis planning and urban construction.

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Evaluation of ecological space and ecological quality changes in urban agglomeration on the northern slope of the Tianshan Mountains

Cited by 41 publications

References 46 publications

Research on habitat quality in arid urban agglomerations: Influencing mechanisms and multi‐scenario simulations

Research on habitat quality in arid urban agglomerations: Influencing mechanisms and multi‐scenario simulations

Studying regional low-carbon development: A case study of Sichuan Province in China

Study on the Expansion Potential of Artificial Oases in Xinjiang by Coupling Geomorphic Features and Hierarchical Clustering

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