Search Results (24)

In the rapidly changing Urban Agglomeration on the Northern Slope of the Tianshan Mountains (UANSTM), urbanization and oasis ecosystem degradation have intensified the need for ecological security planning. However, traditional ecosystem service assessments often struggle to capture the spatial heterogeneity of these fragile landscapes. This study integrates revised ecosystem service value (RESV), ecological sensitivity, and circuit-theory-based connectivity analysis to identify ecological sources and construct an ecological security pattern (ESP). Results indicate: From 2000 to 2020, land conversion among exposed areas, irrigated farmland, and grassland dominated regional change, with 5902 km² of exposed land converting to grassland and 4554 km² to irrigated farmland. RESV declined initially but rose overall from 1104 to 1255 billion yuan, yielding a net increase of about 14%. Ecologically sensitive areas were concentrated in the northeast, covering roughly 19,300 km² and dominated by irrigated farmland. In total, 23 ecological sources, 47 ecological corridors, 28 ecological barrier points, and 61 ecological bottleneck points were identified, forming the basis for a targeted point–line–area protection strategy to guide ecological zoning and restoration. This study provides scientific basis for ecological conservation and territorial spatial planning in arid urban clusters. Nonetheless, limitations related to data resolution and indicator selection remain. Future research should incorporate higher-resolution ecological data and scenario-based simulations to further refine ESP construction. Full article

Rapid and uncoordinated urban expansion in arid oasis city clusters intensifies land use conflicts and ecological pressure, threatening regional sustainability. This study investigates the Urban Agglomeration on the Northern Slopes of the Tianshan Mountains (UANSTM) in Xinjiang, northwestern China—an arid region urban cluster. A multi-source spatial data framework was established to delineate urban built-up areas and to construct land use efficiency (LUE) indicators, thereby facilitating an integrated analysis of the spatial coupling between urban expansion intensity (UEI) and LUE from 2000 to 2020. The results indicate that: (1) The urban built-up area expanded from 322 km² to 1096 km², shifting northward and northwestward, producing fragmented and decentralized patterns; (2) LUE improved but exhibited clear spatial disparities. Core cities like Urumqi showed strong synergy between rapid expansion and rising efficiency, whereas peripheral cities such as Wusu expanded quickly without corresponding efficiency gains, reflecting evident trade-offs; (3) The relationship between UEI and LUE exhibited a nonlinear evolution—trade-offs dominated during 2000–2005, synergy strengthened from 2005 to 2015, and trade-offs resurged again after 2015.These findings reveal the cyclical vulnerability of arid region urbanization and highlight the effectiveness of the proposed framework for diagnosing spatial mismatches and guiding compact, efficiency-oriented urban development toward long-term sustainability. Full article

Ecosystem services play a crucial role in sustaining human life, providing numerous benefits that are indispensable for our well-being. However, these vital functions are increasingly compromised by land use changes that have been instigated by human activities. This study aims to evaluate the spatiotemporal variability of ecosystem service value (ESV) within the urban agglomeration located on the northern slope of the Tianshan Mountains over a historical period stretching from 1990 to 2020, utilizing land use data to conduct a thorough analysis. Subsequently, the Future Land Use Simulation (FLUS) model was employed to forecast ESV in 2030 under three developmental pathways: Ecological Protection Scenario (EPS), Cultivated Land Protection Scenario (CLPS), and Natural Development Scenario (NDS). The evaluation incorporated six primary land classes: cultivated land, forest land, grassland, water bodies, construction land, and unused land. The FLUS model was validated with strong accuracy (overall accuracy = 0.97, Kappa = 0.94). ESV was estimated using the value coefficient method based on equivalent factors, adjusted with a local economic coefficient for crop production. All values are expressed in constant 2020 CNY without further price normalization. Our results show that between 1990 and 2020, cultivated land expanded by 27.18% (17,721 to 22,538 km²) and construction land increased by 75.91% (1926 to 3388 km²), while grassland decreased from 63,502 to 59,027 km² and unused land declined from 106,292 to 104,690 km². Minor changes occurred in forest land and water bodies. Total ESV decreased from 679.06 × 10⁸ CNY in 1990 to 657.67 × 10⁸ CNY in 2020, a decline of 3.15%. Regulating, supporting, and cultural services all decreased, while provisioning services increased. Spatially, vegetated areas functioned as ESV hot spots, whereas construction-degraded areas were identified as cold spots. Scenario projections for 2030 show that under the CLPS and NDS, ESV would further decline by 11.49 × 10⁸ CNY (−1.75%) and 10.18 × 10⁸ CNY (−1.55%), respectively. In contrast, the EPS is projected to increase ESV by 4.53 × 10⁸ CNY (+0.69%), reaching 662.20 × 10⁸ CNY. Full article

This study investigates the spatiotemporal changes in land use within the urban agglomeration on the northern slopes of the Tianshan Mountains (TNUA), aiming to identify the driving factors and provide a scientific basis for regional ecological protection, rational land use planning, and sustainable resource utilization. Using land use data, we analyzed transitions, dynamics, intensity, and gravity shifts in land use, examined driving mechanisms using geographic detectors, and simulated future land use patterns with the Patch-generating Land Use Simulation (PLUS) model. The results indicate that between 2010 and 2020, forest, water body, and unused land areas decreased, while cropland, grassland, and construction land expanded. The rate of land use change accelerated significantly, increasing from 0.0955% during 2010–2015 to 0.3192% during 2015–2020. The comprehensive land use dynamic degree index rose from 157.8371 to 161.1008, with Shayibake District exhibiting the most rapid growth. Precipitation, temperature, economic development, and elevation were the dominant driving factors throughout the study period. Population density had the strongest influence on the expansion of water body, while slope was the most significant factor for cropland expansion. Nighttime light was the primary driver of construction land growth. Projections for 2025, 2030, and 2035 suggest a continued decline in unused land and forest areas, alongside increases in cropland, grassland, water body, and construction land. Full article

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

In past decades, urbanization has entered a phase of rapid development, resulting in an intensified utilization of land resources. The finite nature of these resources has led to increased pressure on land availability, giving rise to a phenomenon known as land use conflict. This conflict is particularly evident in the frequent conversion of land categories, with urban impervious surfaces increasingly encroaching upon forests, grasslands, and agricultural land. Such encroachments trigger a series of land use conflict issues, which subsequently impact the function and structure of regional ecosystems. This paper analyzes the spatial and temporal changes in land use and land cover (LULC) within the urban agglomeration on the northern slope of Tianshan Mountain. It measures and evaluates the spatial and temporal evolution of land use conflicts in the study area from 1990 to 2020, utilizing conflict-related theories and the landscape risk evaluation model. Additionally, the paper explores the spatial and temporal dimensions of land use conflicts under three scenarios—natural development (ND), cultivation priority (CP), and ecological priority (EP)—for the years 2030 and 2050, informed by the Future Land Use Simulation (FLUS) model. The results indicate that unused land constitutes the predominant land use type, accounting for over 50% of the total area. The areas of cultivated land, water bodies, and urban land are experiencing an increasing trend, while the areas of forestland, grassland, and unused land are witnessing a decreasing trend. The level of land use spatial conflicts during the study period showed a decreasing and then increasing trend, with an overall upward trend and an increase in the average value of 0.03. In terms of the proportion of spatial units, mild and general conflicts exhibited a decreasing trend, with reductions of 4.21% and 2.95%, respectively. Conversely, the proportion of medium conflicts increased significantly, rising by 7.33%, while severe conflicts experienced a slight increase of 0.23%. Under the ND, CP, and EP scenarios, the spatial and temporal dynamics of future land use conflicts varied. However, the study area was predominantly characterized by general conflicts in both 2030 and 2050. In 2030, the proportions of spatial units experiencing general conflicts in the three scenarios are projected to be 61.20%, 60.39%, and 57.51%, respectively. In comparison, these proportions are projected to be 59.24%, 62.70%, and 56.29% in 2050, respectively. The anticipated future changes in land use spatial conflicts vary across different scenarios. Notably, the ND scenario indicates a rising conflict level in the study area over the next 30 years, with an overall increase of 0.03 in the mean value. In contrast, the changes in the index under the CP and EP scenarios are relatively stable. 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

Revealing the relationship between intensive land use (ILU) and land ecological security (LES) is crucial for achieving high-quality land resource development and ensuring the sustainability of land ecosystems, especially in arid regions with fragile human–land relationships. In this study, we evaluated ILU and LES in the urban agglomeration on the northern slope of the Tianshan Mountains (UANSTM) and analyzed the evolution of ILU and LES using Pearson correlation analysis, four-quadrant model, and coupling coordination degree model. The results indicated that from 2012 to 2022, ILU and its three subsystems generally showed an upward trend in the UANSTM, with an average annual growth rate of 2.96%, 2.50%, 3.32%, and 0.289%, respectively, and with ILU levels significantly higher in the eastern and central counties compared to other areas. LES and its three subsystems also exhibited a general increase, with average annual growth rates of 1.63%, 0.86%, 3.10%, and 1.51%, respectively, although high-level areas displayed distinct spatial variations. The Pearson correlation analysis showed that the land input level had a significant negative effect on the pressure, but the positive effects of state and response enhanced the LES. The number of double-high cities increased significantly from 1 to 6, and the number of double-low cities decreased from 6 to 0. Compared with other cities and counties, the LES-lagging counties and cities faced the challenge of coordinating urban development and ecological conservation. While coupling coordination levels across all counties improved to varying degrees, none reached the optimal coordination stage. The findings and methodologies of this study provide helpful insights into human–land relationships in arid regions, supporting the goals of high-quality urban development and sustainability. 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 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

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. Full article

It is of great significance for scientific land use planning and ecological security protection to clarify the impacts of land use changes on an ecosystem’s health. Based on the dynamic evolution of land use and ecosystem health on the Northern Slope of Tianshan Mountain (NSTM) from 2000 to 2020, this study utilized the patch-generating land use simulation (PLUS) model, the Vitality–Organization–Resilience–Services (VORS) model, and the elasticity approach to assess the impacts of land use changes on ecosystem health under four different scenarios: Natural Development Scenario (ND), Farmland Conservation Priority Scenario (FP), Ecological Conservation Priority Scenario (EP), and Urban Development Priority Scenario (UD). The results indicate that (1) land use on the NSTM from 2000 to 2020 was predominantly characterized by barren land and grassland. (2) The overall level of ecosystem health on the NSTM was poor from 2000 to 2020 but showed a gradual improvement trend. (3) Ecosystem health levels vary greatly across scenarios. In general, ecosystem health improves under FP and EP scenarios but deteriorates significantly under ND and UD scenarios. The resilience of ecosystem health varies significantly across different land categories. In the future, optimizing the current land use pattern and refining the ecological protection policy are essential to enhance ecosystem health and services in the NSTM. Full article

The serious problem of soil erosion not only has a profound impact on people’s lives but also results in a series of ecological and environmental challenges. To determine the impact of changes in land use type on soil erosion in the urban agglomeration on the northern slopes of the Tianshan Mountains, this study commences by employing the InVEST-SDR (integrated valuation of ecosystem services and tradeoffs–sediment delivery ratio) model to calculate soil erosion levels spanning from 2000 to 2020. Subsequently, it forecasts land use and land cover (LULC) conditions for the year 2030 under three scenarios: Q1 (natural development), Q2 (ecological protection), and Q3 (economic priority). This projection is accomplished through the integration of a coupled Markov chain and multi-objective planning model (MOP) alongside patch-generating land use simulation (PLUS) models. Ultimately, based on these outcomes, the study predicts soil erosion levels for the year 2030. There has been a consistent decline in soil erosion from 2000 to 2020 with high-intensity erosion concentrated in the Tianshan Mountain region. Grasslands, glaciers, and permafrost are identified as the most erosion-prone land types in the study area, with forests exhibiting the highest capacity for soil retention. Converting from grassland and barren land to forest within the same area results in a substantial reduction in soil erosion, specifically by 27.3% and 46.3%, respectively. Furthermore, the transformation from barren land to grassland also leads to a noteworthy 19% decrease in soil erosion. Over the past two decades, the study area has witnessed a significant decline in the area of grasslands, with a notable shift towards barren and impervious surfaces due to economic development and mining activities. The three predicted scenarios depict significant expansion towards barren land, grassland, and impervious area, respectively. Soil erosion decreases under different shared socio-economic pathway (SSP) scenarios relative to 2020. There is an increase in soil erosion in the Q1 scenario and in the Q3 scenario, whereas the amount of soil erosion in the Q2 scenario exhibits a continued decrease when only the effect of land change on soil erosion is considered. Persistently rapid economic development can exacerbate soil erosion problems, underscoring the need to find a balance between economic growth and ecological conservation. As economic expansion slows down, greater emphasis should be placed on environmental protection to maintain ecological stability. Full article

Understanding the responses of vegetation phenology to natural and human disturbances is essential for better understanding ecosystems. In this study, Moderate Resolution Imaging Spectroradiometer data and products were used together with other relevant data to analyse vegetation phenological responses to urbanisation and natural factors in the major urban agglomerations of the Urumqi-Changji, Shihezi-Manasi, and Wusu-Kuidun-Dushanzi regions on the Urban Agglomeration on the Northern Slope of the Tianshan Mountains (UANSTM). Vegetation phenology distributed along an urban-rural gradient showed distinct variability, with start of growing season (SOS), end of growing season (EOS), and growing season length (GSL) occurring earlier, later, and longer, respectively, in urban areas than those in suburban and rural areas. In the Urumqi-Changji region, the earliest SOS, the later EOS, and the longest GSL occurred. Surface urban heat island intensity (SUHII) was most pronounced in the Urumqi-Changji region, with a heat island intensity of 1.77–3.34 °C. Vegetation phenology was influenced by both urbanisation and natural factors, whose contributions were 44.2% to EOS and 61.8% to SOS, respectively. The results of this study emphasise the importance of quantifying the vegetation phenological responses to human disturbances, including climate change, along the urban-rural gradient on the UANSTM. 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