Search Results (11)

The northern slope of the Tianshan Mountains city cluster (NSTM), as a key urban agglomeration for the development of western China, has experienced rapid regional economic development and high population concentration since the twenty-first century. Accompanied by the increase in human activities in the NSTM, it has significantly altered the land use structure, leading to varying levels of habitat disturbance and degradation. In this paper, based on the land use and land cover (LULC) of NSTM from 2000 to 2020. The InVEST model was employed to assess habitat quality, revealing notable spatial and temporal variations. A geoprobe was further employed to explore the key drivers of the spatially distributed pattern of habitat quality in the research region. The results show that (1) from 2000 to 2020, the NSTM was largely characterized by grassland, unused land, and cropland in terms of land use, with a notable expansion of cropland and construction land; (2) the overall habitat quality in the study area is poor, with a clear spatial distribution pattern of high in the south and low in the north, with a predominance of low grades, and a trend of decreasing and then increasing is shown in the temporal direction; (3) under the influence of rapid urbanization in the region, the degradation degree of habitat quality on the NSTM shows a distinct radial structure, with high degradation in the middle and low degradation at the edges, and shows the trend of “increase-decrease-increase” over time; and (4) the results of the geodetector show that altitude and land use type have the greatest influence on habitat quality on the NSTM, indicating that the habitat quality of the research region is primarily influenced by the type of land use. Full article

As one of the 19 key regions for comprehensive land development in China, the Tianshan North Slope urban agglomeration is significant for China’s urban development when calculating the land subsidence and analyzing the impact factors. This study focused on eight cities in the Tianshan North Slope urban agglomeration, calculating the land subsidence rate from 18 January 2018 to 12 April 2023 using Sentinel-1A data and analyzing the spatiotemporal patterns and impact factors of land subsidence. The results showed that (1) the average land subsidence rate is mainly distributed between −30 and 10 mm/a, and the maximum subsidence rate can reach −358 mm/a. Land uplift mainly occurs in Hutubi County and Manas County. (2) From the transition matrix, landscape pattern index, and Moran’s I, the spatiotemporal patterns of the land subsidence rate are obvious, with a spatial positive correlation. During the monitoring period, each administration experienced varying degrees of land subsidence or uplift processes. (3) Using GeoDetector to perform quantitative analyses, it was found that the hydrological environment is significant to land subsidence, and human activities, such as road network density and nighttime lighting, contribute the least to land subsidence, suggesting that it is related to the arid climate of the study area. This paper aims to provide theoretical support for the stable development of and production activities in the study area. This approach not only offers technical support but also provides guidance for evaluating, monitoring, and the early warning of land subsidence in the region. Full article

Although it promotes national economic development, urbanization causes regional ecosystems to suffer from disturbances and impacts that cannot be completely avoided. Ecosystems urgently need to improve their resilience; however, existing studies lack an analysis of the interaction between urbanization and ecological resilience. In this study, the interaction between urbanization and ecological resilience is investigated, taking the urban agglomeration on the north slope of Tianshan Mountain (UANST) as a study area and using the entropy value method to construct an urbanization evaluation system. Based on land use change data, an ecological resilience evaluation model is constructed using the InVSET model, the landscape pattern index, and the unit area value equivalent factor method. The degree of coupling and coordination of the interaction coupling between urbanization and ecological resilience are measured for the years 1990–2020, and their internal action mechanisms are analyzed. The results show that (1) with the development of urbanization, ecological resilience shows a decreasing and then increasing double “U”-shaped change characteristic. (2) The coupling degree of urbanization and ecological resilience in the UANST increased from 0.6888 to 0.9485, and the coordination degree increased from 0.3367 to 0.4410. (3) There are three types of coupling coordination: basic coordination, basic dysfunction, and serious dysfunction. Basic coordination is mainly distributed in the central part of the urban agglomeration, and basic dysfunction and serious dysfunction are mainly concentrated on the east and west sides; the overall trend is to shift from dysfunction to coordination. (4) Economic urbanization plays a driving role, and population urbanization, spatial urbanization, and social urbanization have an inhibitory role in the degree of coupling coordination; base quality and structural stability have a driving role in the degree of coupling coordination, while ecological services have an inhibitory role; and the population density, the proportion of built-up area to the total land area of the city, and the value of ecosystem services have a stronger influence on the level of coupling coordination. Full article

The economic belt on the north slope of the Tianshan Mountains is a highly productive area in Xinjiang, but with the rapid development of the economy and industry and the acceleration of urbanization in recent years, the fragile ecological environment in the region has further deteriorated. Exploring shifts in land utilization across different eras and regions, along with the transformation of terrain configurations, provides key perspectives that can propel sustainable societal and environmental growth within this particular area. The research analyzed four periods (1990, 2000, 2010, 2020) of remote sensing image data combined with field monitoring data using methods such as land use variability, landscape pattern index, and grey relational model. Focusing on investigating the dynamics of the ecological environment in high-intensity human activity areas, examining alterations in land use patterns over time and space, transitions in land use types, and trends in landscape pattern indices. (1) The dominant land environments situated in the economic zone adjacent to the northern base of the Tianshan mountain range encompass extensive expanses of grassy plains and unexploited landscapes, making up 45% and 38% of the area, correspondingly. The single dynamic change degree of construction land was the largest due to the implementation of long-term land development and urbanization policies. Land use transfer change mainly occurred among cultivated land, grassland, forestland, and unused land. With strong human activities, the construction land area has expanded by 145.16% (2089.7 km²), and this number is still increasing. (2) The spatial landscape structure on the north slope of Tianshan Mountain is becoming more complicated and diversified; the cities with the highest degree of fragmentation were concentrated in the middle and western sections. Grassland is the most dominant patch type in the landscape. The shape of patches tends to be irregular and complex in general, and the fragmentation degree and dispersion degree of landscape patches are enhanced as the proportion of different landscape types increases. (3) Grey correlation analysis indicates that grasslands, cultivated land, and unused land are key elements in the landscape pattern changes on the northern slope of the Tianshan Mountains. Central urban agglomeration is an area with strong landscape pattern changes, and ecological protection should be emphasized while promoting economic development. Full article

The rational allocation of land use space is crucial to carbon emissions reductions and economic development. However, previous studies have either examined inter-objective trade-offs or intra-objective trade-offs within a single objective and lacked multilevel and comprehensive studies. Therefore, this paper integrates inter- and intra-objective carbon mitigation and economic efficiency trade-offs to comprehensively study the interaction between land pattern demand and space due to policies. The research methods were mainly multi-objective planning, a gray model, and patch-generating land use simulation model, and the study area was the less-developed urban agglomeration—the Tianshan north slope urban agglomeration. The results of the study show that the total change area of the study area from 2000 to 2020 was 5767.94 km², the grassland area was transferred out the most, 3582.59 km², accounting for 62.11%, and the cultivated land area was transferred in the most, 3741.01 km². Compared with 2020, the simulated land use pattern obtained for 2030 has significantly changed. In addition, the total economic benefits and total carbon emissions under the economic and low-carbon objectives changed in the opposite direction. The four landscape patterns under the three scenarios of economic and low-carbon objectives changed in the same direction, and the degree of landscape fragmentation, agglomeration, and regularity under the low-carbon objective was better than that under the economic objective. The study results are essential references for future land resource management, carbon mitigation, and sustainable development of urban agglomerations. Full article

The urban agglomeration on the north slope of the Tianshan Mountains is a pivotal place in Western China; it is essential for the economic growth of Xinjiang and acts as a critical bridge between China’s interior and the Asia–Europe continent. Due to unique natural conditions, the local population distribution exhibits distinct regional characteristics. This study employs the spatial lag model (SLM) from conventional spatial analysis and the random forest model (RFM) from contemporary machine learning techniques. It integrates traditional geographic data, including land cover data and nighttime light data, with geographical big data, such as POI (points of interest) and OSM (OpenStreetMap), to build a comprehensive indicator database. Subsequently, it simulates the spatial population distribution within the urban agglomeration on the northern slopes of the Tianshan Mountains in 2020. The accuracy of the results is then compared and assessed against the accuracy of other available population raster datasets, and the spatial distribution pattern in 2020 is analyzed. The findings reveal the following: (1) The result of SLM, combined with multi-source data, predicts the population distribution as a relatively uniform and nearly circular structure, with minimal spatial differentiation. (2) The result of RFM, employing multi-source data, better captures the spatial population distribution, resulting in irregular boundaries that are indicative of strong spatial heterogeneity. (3) Both models demonstrate superior accuracy in simulating population distribution. The spatial lag model’s accuracy surpasses that of the GHS and GPW datasets, albeit still trailing behind WorldPop and LandScan. Meanwhile, the random forest model significantly outperforms the four aforementioned population raster datasets. (4) The population spatial pattern in the urban agglomeration on the north slope of the Tianshan Mountains predominantly consists of four distinct circles, illustrating a “one axis, one center, and multiple focal points” distribution characteristic. Combining the random forest model with geographic big data for spatialized population simulation offers robust scientific validity and practicality. It holds potential for broader application within the urban agglomeration on the Tianshan Mountains and across Xinjiang. This study can offer insights for studies on regional population spatial distributions and inform sustainable development strategies for cities and their populations. Full article

Based on land-use change data, this paper constructed an ecological resilience evaluation model from the three dimensions of resistance, adaptability, and regeneration capacity. The spatial and temporal evolution characteristics of the ecological resilience of urban agglomeration on the northern slope of Tianshan Mountain (UANST) from 1990 to 2020 were studied. The key factors affecting the spatial distribution of ecological resilience were detected. The results showed that (1) from 1990 to 2020, the mean ecological resilience values of the UANST were 0.3371, 0.3326, 0.3330, and 0.3240, showing an overall decreasing trend. The regions with low and medium values of ecological resilience contributed the most to these values. (2) The spatial distribution of the ecological resilience of the UANST was uneven, showing a “sandwich”-type distribution with low values in the south and north of the study area and high values in the middle of the study area. During the study period, the ecological resilience in the north part of the study area declined overall, while the ecological resilience in the south part of the study area increased continuously. (3) The results of the Geodetector model showed that natural and human factors jointly influenced the spatial distribution of the ecological resilience of the UANST, with natural factors dominating and temperature changes being the most sensitive. Finally, the impact of intense human activities on the ecological resilience of the UANST is increasing. Full article

Assessing how land use change will affect water production ecosystem services is essential to developing sound water resource management and ecosystem conservation. The results of a coordination analysis of land-use intensity and water yield based on future land-use simulation projections are useful for future land-use planning. To effectively assess water production rates, the PLUS and InVEST models were used to dynamically assess the changes in water production occurring in the urban agglomeration on the northern slopes of the Tianshan Mountains from 2000 to 2030 under different scenarios of land-use change. The results show that the water-production rates in the study area from 2000 to 2020 were 517.26 × 10⁶ m³, 582.28 × 10⁶ m³, and 456 × 10⁶ m³, showing an increasing and then decreasing trend, with the water production function decreasing from the foothills of the Tianshan Mountains to the north and south, with values of 509.10 × 10⁶ m³³, 510.90 × 10⁶ m³, and 502.28 × 10⁶ m³ being presented for the three scenarios in 2030. The rapid economic development scenario presents the lowest water yield values and the ecological conservation development scenario presents the highest water yield values. Changes in water production rates are closely related to changes in land use, which can be verified further by an analysis of the coordination between land- use intensity and water production. For this study area, the ecological conservation development scenario may be more in line with the future urban development pattern, and the results of the present study can provide some scientific references for land-use planning. Full article

Accurately capturing the changing patterns of ecological quality in the urban agglomeration on the northern slopes of the Tianshan Mountains (UANSTM) and researching its significant impacts responds to the requirements of high-quality sustainable urban development. In this study, the spatial and temporal distribution patterns of remote sensing ecological index (RSEI) were obtained by normalization and PCA transformation of four basic indicators based on Landsat images. It then employed geographic detectors to analyze the factors that influence ecological change. The result demonstrates that: (1) In the distribution of land use conversions and degrees of human disturbance, built-up land, principally urban land, and agricultural land, represented by dry land, are rising, while the shrinkage of grassland is the most substantial. The degree of human disturbance is increasing overall for glaciers. (2) The overall ecological environment of the northern slopes of Tianshan is relatively poor. Temporally, the ecological quality changes and fluctuates, with an overall rising trend. Spatially, ecological quality is low in the north and south and high in the center, with high values concentrated in the mountains and agriculture and low values in the Gobi and desert. However, on a large scale, the ecological quality of the Urumqi–Changji–Shihezi metropolitan area has worsened dramatically compared to other regions. (3) Driving factor detection showed that LST and NDVI were the most critical influencing factors, with an upward trend in the influence of WET. Typically, LST has the biggest influence on RSEI when interacting with NDVI. In terms of the broader region, the influence of social factors is smaller, but the role of human interference in the built-up area of the oasis city can be found to be more significant at large scales. The study shows that it is necessary to strengthen ecological conservation efforts in the UANSTM region, focusing on the impact of urban and agricultural land expansion on surface temperature and vegetation. Full article

Nighttime lights remote sensing has a significant advantage in exploring the economic development of cities. Based on nighttime lighting data, this study employed spatial direction analysis, exploratory spatial data analysis, and social network analysis to explore the spatial characteristics of economic development and analyzed the economic connection network structures within urban agglomerations in the New Western Land-sea Corridor (NWLSC) in western China. The results show that the spatial pattern of the Tianshan North slope urban agglomeration, Guanzhong Plain urban agglomeration, and Lanzhou–Xining urban agglomeration shrank, while other urban agglomerations expanded. The city economy of the Chengdu–Chongqing urban agglomeration (CCUA) and the Beibu Gulf urban agglomeration varied dramatically according to a LISA space-time transition analysis, which indicates a strong spatial dependence between cities in the local space. Within urban agglomerations, the economic connection between cities increased significantly, and central cities were at the core of the network and significantly influenced other cities. Among the urban agglomerations, economic connections among neighboring urban agglomerations in geographic space increased during the study period. The CCUA gradually developed into the center of the economic network in the NWLSC. Network density positively influenced economic connections. The degree centrality, closeness centrality, and betweenness centrality significantly enhanced the economic connections between city agglomerations. The study’s conclusions and methods can serve as the policy support for the cooperative development of urban agglomerations in NWLSC serve as a guideline for the development of other economically underdeveloped regions in the world. Full article

The ecological protection and sustainable development of Urumqi have become an important part of the high-quality growth of the urban agglomeration on the northern slope of Tianshan Mountain. Under the impacts of multi-source factors, the ecological landscape pattern of Urumqi has changed due to it being in a fragile eco-environment, so an ecological network is desperately needed to enhance ecological security patterns. Taking Urumqi city as the study area, the ecological risk evaluation model and the minimum cumulative resistance model were integrated to analyze the spatial and temporal features of landscape ecological risk from 2000 to 2020, and the future land use simulation model was used to predict the ecological risk pattern of Urumqi in 2030, construct a landscape ecological network, and propose ecological security protection strategies. Since 2000, land use in Urumqi has undergone drastic changes: the built-up land area has increased significantly, the landscape has diversified, and landscape fragmentation has shown a decreasing trend from the main urban area as the core to the urban fringe. The high-risk landscape ecology shows a decreasing trend from east to west, mainly in the bare land areas with sparse vegetation, whereas the risk is relatively low in woodland, arable land, and built-up areas. The change of risk in the study area is mainly influenced by the typical defective factors of oasis cities such as urban expansion, land desertification, and sparse vegetation. The landscape ecological network is mainly located in the southwest, central, and east of the study area, whereas there is no corridor distribution in the north and southeast, which is mainly caused by the special geographical location and climatic conditions. The ecological network mainly consists of 10 ecological sources and 10 ecological corridors and proposes conservation strategies for the optimization of the landscape pattern and for the construction of the ecological security pattern in Urumqi, providing a guide for the improvement of ecological security. Full article