Search Results (499)

Disentangling the coupled, nonlinear impacts of climate change and anthropogenic activities on vegetation dynamics is critical yet challenging for global change research. The Qinghai–Tibetan Plateau (QTP), a highly climate-sensitive and ecologically strategic region, serves as a vital arena for examining such complex socio-ecological attributions. Based on multi-source environmental datasets from 2000 to 2020, this study developed an integrated, spatially explicit framework coupling residual trend analysis (RESTREND) and GeoDetector to quantify individual drivers and nonlinear climate–human interactions. The QTP exhibited a significant, widespread greening trend during 2000–2020, featuring prominent spatial clustering with “High–High” clusters in the southeast and “Low–Low” clusters in the northwest. Attribution modeling revealed that vegetation dynamics were governed not by isolated variables, but by multifaceted, nonlinear synergies among precipitation, temperature, topography, vegetation type, and land-use change. Key interactive pairs, particularly elevation–temperature and slope–precipitation, dramatically increased explanatory power over single-factor models. Crucially, climate–human synergies explained substantially more variance than climate variables alone, bounded by a distinct elevational threshold: human activities dominated vegetation dynamics at mid-elevations (2500–3500 m), while climate factors took over as the primary controller at high altitudes (above 3500 m). Quantitatively, human activities induced vegetation improvement across 38.6% of the plateau, maintained stability in 35.8%, and caused degradation in 25.6%. By successfully merging trend decomposition with spatial stratified heterogeneity analysis, this study provides a transferable approach to uncoupling complex environmental interactions. These insights highlight the intensifying human footprint on alpine ecosystems and advocate for zone-specific adaptive management: mitigating human disturbances at mid-elevations and fostering climate adaptation in higher zones to preserve plateau resilience. Full article

This study investigates the spatiotemporal evolution of ecological environment quality and its driving mechanisms in the Sichuan section of the Yellow River Basin using Landsat imagery from 2000 to 2023. The Remote Sensing Ecological Index (RSEI) was constructed on the Google Earth Engine platform, and a comprehensive evaluation model was developed using principal component analysis. Sen’s slope, the Mann–Kendall test, and the Hurst exponent were applied to assess temporal trends and future persistence, while the optimal parameter-based Geodetector model was used to identify the driving factors of spatial differentiation. Results show that: (1) ecological environment quality exhibits a fluctuating but overall increasing trend, with a multi-year mean RSEI of 0.58, indicating a transition from “moderate” to “good–excellent” conditions; (2) spatially, ecological quality demonstrates significant heterogeneity and clear altitudinal gradients, with better conditions in the northwest than in the southeast, where low- and mid-altitude areas show higher ecological quality and stronger improvement, whereas high-altitude areas remain relatively poor due to strong natural constraints; (3) the spatial differentiation is jointly driven by multiple factors, among which precipitation and temperature are dominant, elevation exerts a fundamental constraint, and human activity plays a relatively minor role, while the interaction between climate and topographic factors shows the strongest explanatory power. These findings provide insights into the evolution and drivers of ecological environment quality in high-altitude regions and support ecological protection and regional management in the upper Yellow River Basin. Full article

The water–energy–food (WEF) system acts as a critical nexus of social–ecological systems. However, rapid urbanization has intensified the regional imbalance in the supply and demand of ecosystem services (ESs). Clarifying the spatiotemporal matching of ecosystem services supply and demand (ESSD) within the WEF framework and revealing the driving mechanisms behind such imbalances are essential to formulating reasonable zoning schemes and targeted optimization strategies for the coordinated development of the regional WEF system. Taking Zhejiang Province as a case study, this research uses water yield (WY), carbon sequestration (CS), and grain production (GP) to characterize the WEF nexus system. It uses the InVEST model to assess WY and CS, applies spatial allocation methods to characterize GP, and integrates socioeconomic data to quantify the demand for the above three ESs. All indicators were standardized and integrated with equal weights to further clarify the comprehensive levels of ESSD. By integrating the Geodetector and K-Means clustering methods, the study analyzes the supply–demand matching of ecosystem services and its driving mechanisms in Zhejiang Province during this period, thereby exploring ecological management zoning and optimization strategies within the WEF system. The study findings indicate that: (1) From the supply perspective, Zhejiang Province’s WY services demonstrate a trend of elevated activity in the southwest and diminished presence in the northeast; high values for CS services are predominantly found in the vegetation-rich areas of the northwest, while high values for GP services are clustered in the northern Zhejiang Plain; from the demand perspective, high values for all three ESs in Zhejiang Province are primarily located in economically active, densely populated urban areas. (2) The correlation between ESSD within Zhejiang Province’s WEF system exhibits significant spatial heterogeneity and is driven by the combined effects of natural and socioeconomic factors, with the interaction between these two factors often producing a synergistic effect. Specifically, annual average precipitation and population density are the dominant factors influencing WY services, NDVI and human footprint are the dominant factors influencing CS services, and population density and GDP are the dominant factors influencing GP services. (3) From 2000 to 2020, the supply–demand ratio for comprehensive ESs in Zhejiang Province generally followed a pattern of being lower in the east and higher in the west. The supply–demand imbalance of ESs intensified in the core areas of eastern cities, whereas the western regions maintained a relatively sound supply–demand balance. (4) The study classifies the counties in Zhejiang Province into four ecological management zones—ecological stable zones, ecological conservation zones, ecological control zones, and ecological restoration zones—and explores differentiated approaches to optimizing these zones and implementing control strategies. Full article

Climate change and rapid urbanization increasingly threaten water security in large river basins, yet existing assessments often fail to capture the multi-scale interactions between hydroclimatic extremes and human activities. To address this gap, we developed an integrated framework combining risk assessment, multi-method driver diagnosis (Geodetector, Multi-Scale Geographically Weighted Regression (MGWR), and Structural Equation Modeling (SEM)), and Zoned Management. Using a landscape-derived Ecological Risk Index (ERI) as a proxy indicator of runoff and non-point source potential, based on established empirical linkages between landscape metrics and hydrological processes, we applied the framework to three major urban agglomerations in the Yangtze River Basin from 2000 to 2020. Our results reveal three distinct risk mechanisms: in the Chengdu–Chongqing area (CYUA), a 165.8% increase in impervious surfaces drives altered runoff; in the Middle Reaches (MRC), the q-value of the Standardized Precipitation Index (SPI) rose from 0.017 in 2000 to 0.146 in 2020, corresponding to a 759% relative increase. Although the absolute q-value of SPI remains moderate at around 0.15, its rapid rise suggests increasing hydrological sensitivity of the MRC’s river–lake system to precipitation extremes; in the Yangtze River Delta (YRD), socioeconomic activities exert overriding pressure. Based on these diagnostics, we propose tailored strategies for water environment management, adaptive planning, and disaster mitigation. This framework offers a scientific basis for differentiated water governance in large river basins facing coupled anthropogenic and hydroclimatic pressures. Full article

This study aims to reveal the spatial-temporal evolution rule and driving mechanism of cropland multifunctionality in major grain-producing areas. Taking Henan Province as the research case, we establish a comprehensive evaluation index system covering production, living, ecological and cultural functions based on multi-source datasets spanning 2013–2022. It adopts the entropy weight method, spatial analysis and geographical detector (GeoDetector) model to analyze the spatial-temporal differentiation characteristics and influencing mechanism of cropland multifunctionality systematically. The results show that the overall level of cropland multifunctionality in Henan Province rose from 2013 to 2022. Its spatial pattern presents a feature of high in the south and low in the north, with obvious agglomeration in southern Henan. The production function is high in the east and low in the west with a stable pattern. The living, ecological and cultural functions all show a distribution of high in the south and low in the north, with prominent regional differences. Factor detection results indicate that average slope, population density and average annual temperature are the core driving factors. The overall influence of natural factors is stronger than that of socio-economic factors. Interaction detection shows that all factors produce a strengthening effect, mainly in the form of nonlinear enhancement effects. Based on this, the research has proposed targeted and differentiated strategies for the management of cultivated land. Specifically, southern Henan should consolidate its inherent multifunctional advantages and strengthen the coordinated development of production, ecological and cultural functions. Northern and western Henan needs to mitigate terrain and climatic constraints, optimize agricultural infrastructure, and improve overall cropland service capacity. Eastern plain areas should further stabilize grain production function while balancing ecological protection. Central urban agglomerations should coordinate urban expansion and cropland protection to restrain multifunctional degradation. Full article

Urban heat mitigation in megacities depends not only on cooling sources, but also on the connectivity through which cooling effects are transmitted across heterogeneous landscapes. However, existing studies have mainly focused on the static patterns of urban cold islands (UCIs), while the connectivity and disturbance response of urban cooling systems remain poorly understood. Taking Landsat-based summer thermal observations in Beijing, this study developed an integrated framework to assess the structure and resilience of the urban cold island network (CIN) by combining thermal source identification, resistance-surface construction, connectivity modeling, and disturbance simulations. Land surface temperature (LST) was extracted from Landsat 8 OLI/TIRS Collection 2 Level-2 surface temperature products acquired in July–August 2022, and cold island core sources (CICS) were subsequently identified by integrating thermal conditions with land-use characteristics. GeoDetector was used to quantify the explanatory power and interaction effects of natural, land-use, and socio-economic factors on LST spatial heterogeneity, serving as an attribution tool for interpreting thermal-environment drivers. These factors were then integrated into a resistance surface for circuit-theory-based connectivity analysis. Under the summer heat-stress scenario, 202 CICS covering 6416.95 km² were identified, mainly concentrated in peripheral mountainous areas. A total of 401 corridors were identified, including 70 primary corridors forming the structural backbone of the CIN. This spatial distribution reveals a mountain–plain cooling structure in Beijing, in which mountainous CICS constitute the regional cooling-supply base, while potential cooling transmission toward the urban core mainly depends on a limited number of backbone corridors. LULC was the dominant driver of LST, and its interactions with PD, NTL, and vegetation-related factors substantially enhanced explanatory power. Compared with random disturbance, targeted node removal led to an earlier and sharper decline in network resilience, with substantial deterioration already evident after approximately 20–30% of critical nodes were removed. These summer-based findings provide spatially explicit evidence for prioritizing cooling corridors, critical nodes, and restoration areas in connectivity-oriented urban heat mitigation and climate-responsive planning, thereby supporting hierarchical maintenance and restoration strategies based on their relative importance within the cooling network. Full article

Rapid urbanization exerts profound pressure on urban biodiversity, yet long-term assessments integrating multi-source remote sensing data remain scarce. Objective: Focusing on the Hangzhou Bay Urban Agglomeration, a rapidly developing region in China’s Yangtze River Delta, this study aims to construct a remote sensing-based Biodiversity Index (BI) and analyze its spatiotemporal evolution and underlying drivers. Six Essential Biodiversity Variables derived from satellite observations (2000–2024) were integrated using Principal Component Analysis. Spatial autocorrelation and Geodetector models were then applied to examine BI dynamics and driving factors. The regional BI declined gradually from 0.80 in 2000 to 0.72 in 2024, with the rate of decline slowing after 2020 and a partial recovery observed in Zhoushan. Marked inter-city heterogeneity exists: Huzhou retains the highest and most stable BI due to extensive forest cover, whereas Jiaxing exhibits the lowest BI and the most pronounced decline, driven by rapid expansion of construction land. Land use/cover (LULC) and fractional vegetation cover (FVC) emerge as the dominant drivers (average q-values of 0.196 and 0.208, respectively), and their interaction explains over 46% of the spatial variance in BI. Road density shows a consistently increasing influence over time. This study demonstrates the utility of remote sensing-based frameworks for monitoring urban biodiversity dynamics and provides actionable insights for evidence-based land use planning and ecological restoration. Full article

Promoting the high-quality development of farmers’ specialized cooperatives and narrowing regional development gaps is critical for advancing China’s rural revitalization strategy. Based on provincial panel data covering 30 Chinese regions from 2015 to 2023, this paper constructs a five-dimensional evaluation index system including standardized operation, operational performance, service scope, driving effect, and industrial upgrading, and adopts the entropy weight method to quantify the comprehensive development level of cooperatives. By combining spatial autocorrelation, kernel density estimation, the Dagum Gini coefficient and the Geodetector model, this paper explores the spatio-temporal evolution, regional disparities and multi-factor coupled driving mechanism of cooperative development. The main findings are as follows: (1) While the total quantity of cooperatives keeps expanding nationwide, their overall development level presents an evolutionary feature of declining first and then rising; industrial upgrading gradually becomes a new growth engine, whereas operational performance and driving effect slip downward. (2) The spatial layout of cooperatives maintains a typical pyramid structure; high-value agglomeration shifts from the Yangtze River Delta to southeast coastal regions, and low-value clusters are persistently concentrated in Northeast China. (3) The overall Dagum Gini coefficient reflects widening-then-shrinking regional gaps, and intra-eastern provincial differences constitute the primary source of nationwide spatial divergence. (4) Household consumption and rural labor force stock serve as core driving factors; regional economic development, agricultural production efficiency, rural human capital and land resource allocation form a coupled driving system, and all explanatory variables show mutual enhancement effects without offsetting interactions. Targeted policy suggestions are put forward to realize balanced and high-quality development of farmers’ specialized cooperatives across China. Full article

The sustainable development of human settlements in mountainous Southwest China hinges on the coordinated evolution of their production–living–ecological spaces (PLES). This study investigated the distribution evolution and coupling characteristics of the PLESs within the human settlements of Xiushan Tujia and Miao Autonomous County, Chongqing. Utilizing land use data from 1990 to 2020, GIS spatial analysis, a coupling coordination degree model, and the Geodetector method were employed to systematically investigate PLES’ spatial patterns, evolutionary characteristics, and underlying mechanisms. The results reveal the following: (1) The PLES structure underwent a distinct phased and heterogeneous distribution evolution, shaped by socioeconomic development and ecological conservation policies. (2) Primarily driven by the dual forces of economic and policy factors, the transformation between ecological and production spaces was predominant, followed by that between production and living spaces. (3) The coupling coordination degree (CCD) improved from extreme imbalance toward near coordination, exhibiting a zoned structure characterized by high levels in the central core and low levels in peripheral mountainous areas. (4) Socioeconomic factors generally have greater explanatory power than natural factors do in terms of driving PLES changes. The interaction effects between any two drivers are stronger than the individual effects, with economic growth and population agglomeration being the core restructuring forces and transportation accessibility a key catalyst. The distribution evolution of PLES and the coupling approach to PLES at the human settlements scale are deciphered, providing a scientific foundation for coordinating spatial conflicts, optimizing territorial spatial planning, and implementing differentiated governance strategies in ecologically sensitive mountainous regions. Full article

The Qinghai Lake Basin represents a critical ecological security barrier in the northeastern Qinghai–Tibet Plateau. Water yield and carbon storage within this basin are closely linked to regional ecological security and sustainable development. To investigate their spatiotemporal patterns, influencing factors, and spatial interrelationships from 1995 to 2020, this study integrated the InVEST model, the Optimal Parameter Geodetector model, and spatial autocorrelation analysis. The results indicate that water yield exhibited a fluctuating yet generally increasing trend over the study period, rising from 1.42 × 10⁹ m³ to 1.97 × 10⁹ m³. High water yield values were predominantly concentrated in high-altitude headwater areas, whereas low values mainly occurred in the lake area and its surroundings. Elevation, annual mean temperature, and precipitation were identified as the primary drivers of water yield. Carbon storage increased from 1.76 × 10⁸ t in 1995 to 2.14 × 10⁸ t in 2020. High carbon storage values were mainly concentrated in grassland and forested areas, while low values were largely distributed in built-up land, unused land, and the lake area. Elevation, NDVI, and water yield emerged as the main influencing factors of carbon storage. A significant positive spatial correlation was observed between water yield and carbon storage. Persistent patterns of high-carbon-storage–high-water-yield clusters and low-carbon-storage–low-water-yield clusters demonstrate a clear spatial synergy. These findings provide scientific support for ecological conservation, water resource management, and carbon sink enhancement in the Qinghai Lake Basin and are of practical significance for sustaining regional ecosystem services and safeguarding sustainability. Full article

Small water bodies serve as fundamental units and key conduits for material cycling and hydrological processes at the watershed scale. However, quantitatively identifying the mechanisms driving their area evolution under multi-factor coupling in different scenario simulations remains challenging. This study focused on the small water bodies in the Chaohu Lake Basin. An Otsu algorithm was applied to establish a basin-scale database of small water bodies, while the GeoDetector model was integrated to reveal the spatiotemporal driving mechanisms of multi-factor coupling behind their evolution. Furthermore, a Long Short-Term Memory (LSTM)–Transformer model was modified to simulate future scenarios of small water body area dynamics. The results indicated that, from 1995 to 2024, the area of small water bodies in the Chaohu Lake Basin exhibited a fluctuating decreasing trend (wet season: 186–269 km²; dry season: 110–253 km²). In terms of spatial distribution, the small water bodies exhibited an unbalanced distribution pattern characterized by wide dispersion alongside regional clustering. Results from the GeoDetector model revealed that land use type (q = 0.711) and evapotranspiration (q = 0.526) were the dominant drivers of variations in small water body areas. LSTM–Transformer simulations (R² = 0.92, p < 0.01) suggested that, under temperature, precipitation, and land use change scenarios, the small water body areas in the Chaohu Lake Basin will exhibit distinct seasonal variation characteristics, with scenario-dependent differences in fluctuation amplitude and peak–trough timing. These results offer theoretical support for the protection of small water bodies and integrated water resource management in the Chaohu Lake Basin. Full article

Against the background of industrial transformation and urban regeneration in old industrial bases, understanding the spatial pattern and driving mechanisms of industrial heritage is essential for its conservation and sustainable use. This study investigates 277 industrial heritage sites in Liaoning Province (including nationally designated sites, potential heritage within cultural relic protection units at all levels, and sites recognized by the China Association for Science and Technology) using kernel density estimation, standard deviation ellipse, and the GeoDetector model. The results reveal a significantly clustered distribution characterized by “dense in central–southern Liaoning, sparse in the periphery,” forming three major agglomerations: the Shenyang core, the Anshan–Benxi–Liaoyang heavy industry triangle, and the Dalian coastal industrial belt. Temporally, the distribution shows distinct phases closely linked to industrial development history and major socio-political events. Land use, GDP, and climatic factors dominate the spatial differentiation, with GDP and annual average temperature exhibiting the strongest combined explanatory power (41.67%). Based on these dominant factors and the identified core agglomeration areas, differentiated protection and utilization strategies should be formulated for core versus peripheral areas, different industrial types, and various historical periods. This provides direct empirical evidence for industrial heritage management and cultural revitalization in old industrial regions. Full article

The relationship between humans and the land has always been a topic in geographical studies. Northeast China, one of the regions with the shortest history in China, is also one of the regions most representative of changes in human–land relationships. However, scholars have rarely conducted quantitative region-scale research on the dynamic changes in, and drivers of, human–land relationships in this region. This study utilizes Landsat remote sensing imagery to identify changes in the distribution of land use types in Northeast China from 1990 to 2022. By constructing a human–land coordination model, it measures the intensity of human activity and levels of human–land coordination, analyzes their spatiotemporal dynamic characteristics, and further uses the Geodetector model to explore the factors driving and interactions influencing this evolution. (1) The results show that, from 1990 to 2022, the level of human–land coordination in Northeast China generally exhibited a spatial distribution pattern decreasing from northwest to southeast. The area of imbalanced human–land relationships continuously decreased, while coordinated areas steadily increased, indicating gradual improvement in human–land relations. The predominant type of coordination was moderate imbalance, with high imbalance as a secondary level. (2) The results also demonstrate that population size, GDP, and tertiary industry output have significant explanatory power regarding levels of human–land coordination. The importance of economic development level, natural resource endowment, and natural environmental characteristics to the evolution of human–land has progressively increased. Full article

The spatial heterogeneity and dynamic changes in soil organic matter (SOM) are key indicators for assessing cultivated land quality and the carbon cycle. Currently, large-scale SOM monitoring relies primarily on limited ground sampling, making it difficult to capture continuous spatiotemporal variation patterns. Taking Anhui Province, China as the study area, this research integrates multi-source remote sensing and geostatistical methods to construct a multi-source collaborative SOM inversion model and analyze its spatiotemporal evolution patterns, thereby achieving high-precision, continuous spatiotemporal monitoring of SOM. A total of 3026 sampling points in Huangshan, Chuzhou and Fuyang cities in Anhui Province were selected as model training samples. The study divided the terrain into three elevation zones (<20 m, 20–40 m, >40 m) and employed the Synthetic Minority Oversampling Technique (SMOTE) method to optimize sample distribution. Based on MODIS data, this study screened spectral bands and key phenological periods significantly correlated with SOM. By integrating spectral information from Landsat 8/9 OLI imagery, meteorological data and topographic factors, a random forest (RF) inversion model incorporating multi-source environmental variables was constructed. The results indicate that (1) the RF-based SOM inversion model exhibits moderate predictive accuracy acceptable for regional-scale SOM mapping, with a coefficient of determination (R²) of 0.55 and a root-mean-square error (RMSE) of 3.3 g/kg, effectively enabling the quantitative estimation of SOM at a regional scale. (2) The model’s inversion results reflect the spatial distribution of SOM in cultivated land in Anhui Province for the years 2019, 2022 and 2024. The provincial average SOM value shows an upward trend, with SOM content exhibiting a pattern of higher levels in the south and lower levels in the north, higher levels in the west and lower levels in the east, as well as a tendency to cluster. (3) Analysis using GeoDetector indicates that topography and precipitation are the primary drivers influencing SOM distribution, and the interaction between these two factors provides significantly greater explanatory power for SOM distribution than either factor alone. Through the integration of multi-source remote sensing data and model optimization, this study has validated the feasibility of multi-scale remote sensing-based SOM inversion, revealed the spatial differentiation characteristics and driving mechanisms of SOM in Anhui Province’s cultivated land, and provided a scientific basis for improving cultivated land quality and soil carbon sink management. Full article

Hydro-cultural heritage is shaped by strong hydrological dependence and historical accessibility. To address insufficient identification of river-basin heritage linkages and their weak translation into graded protection, this study develops an analytical framework integrating heritage-site evaluation, cultural source identification, resistance-surface construction, potential corridor extraction, network grading, and protection guidance, and applies it to the Xiangjiang River Basin, China. Heritage sites were evaluated by protection level, historical continuity, spatial proximity, and hydro-cultural relevance. Cultural source areas were identified using weighted kernel density analysis, potential corridors were extracted using the minimum cumulative resistance model, and the graded corridor network was examined using network-structure indices. The results show river-oriented clustering, localized nucleation, and belt-like extension. Eight primary and fourteen supplementary cultural source areas were identified. Potential corridors are concentrated along the Xiangjiang main stem and major tributaries. In the resistance-surface construction, distance to the water system received the highest AHP-derived resistance weight, while GeoDetector showed that it had the highest, although modest, single-factor explanatory power among the tested variables for corridor spatial differentiation. The corridor network exhibits a primary–secondary–tertiary graded structure. This study reveals the spatial continuity and hierarchy of hydro-cultural heritage corridors and provides a methodological reference for river-basin conservation. Full article