Search Results (16,193)

The overexploitation of groundwater resources is a significant concern due to the potential risks associated with a decline in freshwater availability. Future planning and policymaking should consider long-term groundwater availability and urban expansion patterns to understand urban growth. This study aims to investigate the impact of land cover change on groundwater depletion. Further, the land surface temperature (LST) and vegetation change using Normalized Difference Vegetation Index NDVI analysis have been performed to find the spatial spread of urbanization and its impact on surface temperature in the area. For groundwater assessment, the Gravity Recovery and Climate Experiment (GRACE) data have been used, while for land cover, NDVI, and LST assessment, Landsat data have been used. The GRACE-based groundwater storage (GWS) anomaly has been correlated with Global Precipitation Measurement (GPM) data. An annual groundwater storage decline of ~7.01 mm/year was identified. Groundwater and land-cover changes were evaluated at five-year intervals from 1990 to 2025. The urban expansion from 838 to 1470 km² coverage shows the rapid expansion and its impact on vegetation and groundwater recharge in the area. The results demonstrate a rapid increase in the urban area, which affected the vegetation and increased the surface temperature in the area. Urban expansion reduced vegetation cover and infiltration, contributing to elevated land surface temperature and groundwater depletion. This study focused on integrating the groundwater impacts due to other environmental variables, i.e., temperature increase and vegetation decrease. The temporal increase in urban expansion decreases the infiltration rate, which impacts the groundwater storage and depletion, as shown by the linear trend. These findings underscore the urgent need for effective groundwater management and vegetation management policies and integrated urban planning strategies to ensure the long-term sustainability of freshwater resources. Full article

The shrinking of glaciers is drastically transforming headwater catchments, exposing new land surfaces and forming new water bodies, characterized by marked environmental gradients and the activation of potential geochemical hazards. The aim of this study was to characterize and compare the geochemical patterns of soil and water in areas deglaciated between 1970/1984 and 2025 within the Llaca and Gueshgue valleys of the Cordillera Blanca, Peru. Systematic soil and water sampling was conducted, and data were analyzed using descriptive statistics and multivariate techniques. The analyses revealed a clear and statistically significant geochemical differentiation between the two areas (p ≤ 0.05). Gueshgue was identified as a system in transition, exhibiting geochemical signatures of acid rock drainage (ARD), with loamy soils rich in Fe and Al, and acidic waters featuring high redox potential and elevated concentrations of SO₄²⁻, EC, Co, Cu, Mn and Mg. In contrast, Llaca exhibited greater stability, with neutral waters and sandy soils dominated by silicate weathering signatures (SiO₂) and trace elements (Al, Li, Ba, K, and Ti). These findings indicate that the impact of glacier retreat on proglacial ecosystems is heterogeneous; identifying these geochemical patterns is fundamental to establishing baseline monitoring and guiding the sustainable management of these climate-change-sensitive ecosystems. Full article

Spodoptera frugiperda is a highly polyphagous pest that poses a serious threat to global agricultural production. Understanding its species distribution is of great importance under the current context of climate change. In this study, we used the biomod2 platform to integrate six models, namely XGBOOST, Maxnet, Maxent, MARS, GBM, and GLM, to construct an ensemble model. This ensemble model was used to simulate the potential distribution of S. frugiperda under current and three future climate scenarios, and to analyze the main environmental factors influencing its distribution and their change trends. The results indicated that Bio08, Bio16, Bio09, and Bio03 were the major environmental factors affecting the species’ distribution. Under the current scenario, the suitable area was approximately 2026.05 × 10⁴ km², accounting for about 10% of the global land area, and was mainly concentrated in East Asia and central North America. The expansion of S. frugiperda varied among the three future climate scenarios; under the SSP5-8.5 scenario, the expansion toward higher latitudes was the most pronounced, with the total suitable area increasing by 91.8%. Analysis of the three climate scenarios revealed that the expansion trend of S. frugiperda intensified with increasing carbon emissions. Under the most conservative SSP1-2.6 scenario, even a slight reduction in suitable area was possible. This study provides an in-depth exploration of the distribution characteristics of S. frugiperda and its responses to environmental factors from a geographical perspective. These findings contribute to a better understanding of the species’ potential distribution and the influence of environmental variables from a spatial standpoint. They offer a scientific basis for the prevention and control of this pest in specific regions, and may also serve as a reference for future studies on similar invasive insect pests. Full article

As an important infrastructure for the construction of a new power system, pumped-storage hydropower stations may exert certain impacts on the surrounding fractional vegetation cover (FVC) during their construction. Based on Landsat remote sensing imagery and China Land Cover Dataset (CLCD) land use data from 2013 to 2024, this study investigated the dynamic changes in FVC and the spatial extent of engineering disturbance associated with the Zhen’an Pumped-Storage Hydropower Station in Shaanxi Province, China. The analysis integrated the Pixel Dichotomy Model, Theil-Sen trend analysis, Mann–Kendall significance test, coefficient of variation, landscape pattern indices, and correlation analysis. The results showed that: (1) FVC in the study area exhibited distinct stage-dependent evolution characteristics that were highly consistent with the construction timeline of the project. (2) The spatial influence of engineering disturbance on FVC was mainly concentrated within 1250 m, with the 0–250 m zone identified as the core impact area. Landscape fragmentation in this zone was higher than in other distance ranges, and vegetation degradation gradually weakened with increasing distance from the project. (3) Land use change within the study area was primarily characterized by the conversion of forest to cropland and impervious surfaces, resulting in a reduction in high coverage vegetation areas. Landscape patterns exhibited pronounced buffer-gradient characteristics. Within 500 m, the Largest Patch Index (LPI) decreased while the Shannon Diversity Index (SHDI) increased, indicating weakened continuity of dominant landscape patches. Beyond 500 m, LPI generally increased and SHDI decreased, suggesting a trend toward a more stable landscape structure. (4) Both air temperature and precipitation exhibited interannual fluctuations, but neither showed a significant long-term trend. The correlations between climatic factors and FVC were relatively weak, and the multiple regression model demonstrated limited explanatory power for FVC variation. Full article

Digital transformation is changing agricultural information access, market connectivity, and factor allocation, but its implications for crop-planting structure remain underexamined. Using a prefecture-level panel of 291 Chinese cities from 2000 to 2023, this study investigates whether the digital economy is associated with relative non-grain cropping, measured as the share of non-grain crop sown area in total crop sown area. The results show that a one-standard-deviation increase in the digital economy index is positively associated with relative non-grain cropping. Area decomposition indicates that this relationship reflects selective contraction and factor reallocation rather than unrestricted absolute expansion of non-grain acreage. Moderation and heterogeneity analyses further show that platform-commerce and digital-payment environments strengthen the association, while major grain-producing area status and stronger agricultural resource endowments weaken it. Robustness and endogeneity-mitigation checks support the positive association but also indicate important identification boundaries. The findings contribute to debates on sustainable land-use transition by showing how digitalization can reshape crop allocation under market opportunities, factor constraints, and food-security institutions. Full article

Water quality analysis plays an essential role in maintaining the health and sustainability of river ecosystems, especially in semi-arid regions like the Arroyo Colorado Watershed in South Texas. Since the river is a vital source of water supply for local communities, agriculture, and wildlife, it faces significant challenges and pollution from land use changes, climate variation, and agricultural runoff. Continuous monitoring and assessment of water quality parameters and their temporal variability are essential to ensure the drinking water supply and aquatic ecosystem health. However, comprehensive laboratory-based water quality investigations are often constrained by higher costs, logistical complexity, and limited manpower. As a result, monitoring datasets are often not available for all water quality parameters, or the datasets may be incomplete. To address such challenges, the objective of this study was to evaluate the potential of water quality index (WQI)-based assessment supported by machine learning algorithms as an alternative decision-support tool for water quality evaluation. The analysis compared four monitoring stations in the Austin and Arroyo Colorado Watersheds, with particular emphasis on one gauging station at Port Harlingen. Datasets were collected from the Texas Commission of Environmental Quality (TCEQ). A complete exploratory data analysis (EDA) was performed to understand the TCEQ water quality datasets containing sixteen parameters, and seven water quality parameters were selected based on multicollinearity checks. It was observed that seven independent water quality parameters (dissolved oxygen, ammonia, nitrate, phosphorus, temperature, fecal coliform, and residual non-filterable material concentrations) were identified as sufficient to define the WQI of the Austin monitoring stations. Moreover, U.S. Environmental Protection Agency (EPA)-based guidelines were utilized to scale individual parameters to a range of 0–100 to remove their magnitude and correlation-based bias. These parameters were further analyzed using machine learning techniques, i.e., principal component analysis, K-means, and one-class support vector machine, to compute the relative importance based on their fluctuation within the temporal dataset. Finally, the mean WQI model was developed for Port Harlingen and achieved a strong agreement with the National Sanitation Foundation (NSF) WQI (R² = 0.91). These findings demonstrate the applicability of the proposed data-driven WQI framework for regional water quality assessment and comparative analysis across watersheds. Full article

Non-grain production of cultivated land has increasingly affected regional food security and the stability of agricultural ecosystems. In traditional rice-producing regions, changes associated with non-rice cultivation, fallow land, rice-fishery integrated farming, and intensive agricultural management are reshaping the spatial structure of paddy landscapes. To identify the long-term spatiotemporal evolution of paddy systems, this study investigated Northern Jiangxi, China, using Landsat surface reflectance imagery from 2000, 2005, 2010, 2015, and 2020 on the Google Earth Engine (GEE) platform. The Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI) were used to construct a phenology-based Flooding Frequency (FF) indicator. Based on the annual frequency with which pixels satisfied the condition LSWI > EVI, cultivated land was classified into three categories: non-flooded cropland, standard rice paddy, and high-frequency flooded cropland. In this study, non-flooded cropland was used as an indicator of potential non-rice cultivation rather than as direct evidence of confirmed non-grain production. Landscape metrics, transition matrices, gravity center migration, standard deviation ellipses, and geographically weighted regression (GWR) were then used to examine paddy landscape dynamics, fragmentation patterns, and county-level spatial associations with socioeconomic factors. The results suggest that the paddy system in Northern Jiangxi experienced marked stage-based fluctuations between 2000 and 2020. Standard rice paddy recovered during 2005–2010, whereas non-flooded cropland expanded considerably during 2010–2015, accompanied by intensified paddy landscape fragmentation. Non-flooded cropland was mainly distributed around urban fringes, transport corridors, and some hilly margins. Standard rice paddy was concentrated in traditional grain-producing areas, including the Poyang Lake Plain and the Gan-Fu Plain. High-frequency flooded cropland was primarily located in low-lying lake areas, where its dynamics were likely associated with rice-fishery integrated farming, continuous irrigation, and hydrological fluctuations. Landscape metrics showed that the largest patch index and mean patch size of standard rice paddy declined after 2010, indicating reduced spatial continuity of core paddy fields. The GWR analysis provided auxiliary evidence that total population, per capita gross domestic product (GDP), and urbanization rate were spatially associated with changes in non-flooded cropland at the county level; however, the results should be interpreted as exploratory associations rather than causal mechanisms. Overall, paddy landscape change in Northern Jiangxi was expressed not only through changes in cultivated land area, but also through the reorganization of paddy function, spatial continuity, and land-use intensity. Future cropland protection should therefore move beyond area-based control toward integrated management of quantity, quality, function, and spatial configuration. Future research should further verify these findings using dynamic cropland boundaries, higher-resolution imagery, and more detailed socioeconomic data. Full article

Terrestrial water storage in semi-arid basins is increasingly affected by the combined pressures of climate variability, land use change and intensive human activities. However, how landscape composition and configuration interact with climatic forcing to shape basin-scale terrestrial water storage anomalies (TWSA) remains insufficiently understood, particularly in rapidly urbanising tributary basins of the Yellow River. This study integrates GRACE/GRACE-FO-derived TWSA, meteorological observations and multi-period land use data to examine the coupled relationships among climate variability, landscape patterns and water storage in the human-dominated Yiluo River Basin. The results show that basin-averaged TWSA experienced a significant long-term decline during the GRACE/GRACE-FO period (−4.47 mm yr⁻¹), with a statistically detectable transition around 2012 and stronger depletion in the northern and eastern parts of the basin. Precipitation exhibited a cumulative and delayed relationship with TWSA, with the strongest raw association occurring under a six-month accumulation and one-month lag (Pearson’s r = 0.44, p < 0.001, n = 134). After removing the seasonal cycle, the relationship remained significant but weaker (r = 0.30, p = 0.001, n = 129), indicating that precipitation explains part, but not all, of the interannual variability in water storage. Landscape composition showed stronger associations with TWSA than landscape configuration. Construction land was negatively associated with water storage, whereas cultivated land and grassland showed positive associations, suggesting that impervious surface expansion and the loss of permeable land may weaken the basin’s water retention capacity. These findings indicate that water storage change in the Yiluo River Basin is shaped by both climatic forcing and human-induced land surface transformation. Basin management should therefore prioritise the control of urban impervious surface expansion, the protection of permeable agricultural and ecological land, and the integration of land use planning with adaptive water resource regulation. Full article

Understanding the interactions between vegetation dynamics and surface water availability is essential for assessing the resilience of tropical floodplain ecosystems under increasing hydroclimatic variability. This study analyzes the spatio-temporal dynamics of vegetation cover, surface water, and land use in Zambrano, a floodplain-dominated sector of the lower Magdalena River basin (Colombian Caribbean), over the period 1990–2025. Multi-temporal Landsat imagery was used to derive the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI), enabling the evaluation of seasonal and interannual ecohydrological variability under contrasting dry and rainy conditions. In addition, land-use classification was performed using a CORINE Land Cover methodology adapted for Colombia (CLC-C) to characterize the spatial organization of the landscape and its influence on vegetation–water interactions. Results show that vegetation dynamics are strongly controlled by hydroclimatic seasonality. Dense vegetation consistently expands during rainy periods, while dry seasons promote the expansion of open and sparse vegetation, reflecting seasonal vegetation stress rather than long-term degradation. NDWI patterns indicate that surface water and soil moisture are highly seasonal and spatially constrained, with open water largely confined to the Magdalena River channel and localized floodplain depressions. Extreme hydroclimatic events associated with the El Niño–Southern Oscillation (ENSO) produce abrupt but temporary changes in vegetation structure and surface moisture distribution. A strong inverse correlation between NDVI and NDWI reflects the contrasting spectral responses of vegetation and water surfaces resulting from the shared near-infrared (NIR) band in both indices. This spectral relationship is consistent with the observed seasonal variations in vegetation greenness and surface moisture across the floodplain. Land-use analysis reveals the progressive consolidation of the landscape, where the agropastoral matrix expanded from ~18,000 ha in 1990 to over 22,000 ha by 2025, driving a systematic reduction in natural and semi-natural forest structures. Forest conservation areas serve as critical ecological buffers, exhibiting lower seasonal variability in vegetation greenness. Overall, the results indicate that the Zambrano floodplain functions as a structurally stable yet highly responsive ecohydrological system, where vegetation dynamics and surface water availability are predominantly governed by interannual hydroclimatic pulses rather than long-term directional degradation. These findings demonstrate that while the structural matrix of the floodplain exhibits strong baseline resilience, its ecological functioning remains critically coupled with, and vulnerable to, the extreme phase shifts in ENSO cycles. Full article

The sustainable management of land resources and the formulation of land policies are closely linked to the stability and health of terrestrial ecological systems, which in turn underpin sustainable regional economic, social, and environmental development. However, land use change has a time effect on the environment and requires long-term observation to discover its impact on landscape patterns. The Yellow River Basin functions as a critical ecological barrier in northern China, where land use changes are particularly intense in the transitional zone between its middle and lower reaches. Using Landsat imagery as the data source, this study adopts the Random Forest (RF) algorithm to classify eight sets of sequential data covering a 35-year period from 1990 to 2025 in the study area. Landscape pattern metrics and transfer matrices are employed to conduct qualitative and quantitative analyses of the spatiotemporal dynamics of land use changes. Additionally, land expansion analysis strategies and the RF algorithm are applied to identify the relative importance of different driving factors. The results show that: (1) The classification accuracy based on the Google Earth Engine (GEE) cloud platform remains consistently high, exceeding 90% across all phases. (2) Patch density decreases significantly, while the largest patch index continues to decline; the Shannon diversity index shows a fluctuating upward trend, and the aggregation index exhibits a slight increase. (3) Mutual conversions among farmland, forest, and grassland are the dominant processes driving land use changes in the region. (4) The Digital Elevation Model (DEM), construction land area distribution, and distance to primary roads are the key factors influencing land use patterns, with human activities acting as the primary driver of land use type transformations in the area. Full article

This study analyses long-term land cover changes in the Trnava District, Slovakia, with particular emphasis on urban expansion and agricultural land loss. CORINE Land Cover datasets from 1990, 2006 and 2018 were analysed in the TerrSet Land Change Modeler environment, and future land cover development up to 2064 was simulated using a CA–Markov modelling framework. The model incorporated four spatial explanatory variables: distance from built-up areas, distance from the road network, distance from wate courses, and elevation. Between 1990 and 2018, Non-irrigated arable land recorded the largest absolute net loss, decreasing by 962 ha (−1.9%). Urban and industrial categories expanded during the same period: Industrial or commercial units increased by 456 ha (+75.2%), Discontinuous urban fabric by 378 ha (+7.7%), and Continuous urban fabric by 70 ha (+175.0%). Broad-leaved forest increased by 796 ha (+6.9%), whereas Transitional woodland-shrub decreased by 487 ha (−76.7%), demonstrating that gross gains and losses within individual categories did not necessarily correspond to their net area changes. The scenario-based projection to 2064 indicates a continued reduction in arable land and further expansion of discontinuous urban fabric and industrial or commercial areas, particularly around existing settlements and transport corridors. The results demonstrate the simultaneous effects of urbanisation, agricultural land conversion and changes in semi-natural and forest categories. The study highlights the importance of distinguishing gross land cover turnover from net area change and provides spatially explicit information to support agricultural land protection, spatial planning and sustainable landscape management in rapidly urbanising regions. Full article

The Dongting Lake Region is a major river-connected lacustrine ecosystem and ecological security barrier in the middle Yangtze River Basin, where land use change has important implications for ecosystem service provision. However, how land use transition pathways and spatial clustering jointly shape land-cover-based ecosystem service value (ESV) estimates remains insufficiently understood, particularly under a coefficient-based valuation framework. This study used land-use data for 2005, 2010, 2015, 2020, and 2025 (with the 2025 layer being not fully observation-based but derived from remote-sensing interpretation and model-assisted updating rather than direct field observations). The analytical framework integrated land-use transition analysis, land-use dynamic degree analysis, equivalent-factor-based ESV estimation, spatial autocorrelation analysis, one-way parametric sensitivity analysis with a ±50% variation, and stage-specific comparisons aligned with policy implementation timelines. These methods were applied to investigate the spatiotemporal dynamics of estimated ESV in the Dongting Lake Region. Cropland, forestland, and water bodies remained the dominant land use types, while built-up land expanded through the conversion of agricultural and ecological land. Estimated total ESV declined during the study period, although the annual rate of decline was lower during 2015–2025 than during 2005–2015. Under the adopted equivalent-factor framework, water-body-related transitions contributed most to estimated ESV change, reflecting both the ecological importance of water-related systems and the high coefficients assigned to water bodies, especially for hydrological regulation. Estimated ESV showed persistent positive spatial autocorrelation, with High–High clusters concentrated around East Dongting Lake, South Dongting Lake, and West Dongting Lake. These findings provide land-cover-based evidence for territorial spatial optimization and SDG-related ecosystem management. However, the identified clusters should be interpreted as candidate lake-centered high-value ecological spaces for further assessment, rather than as definitive conservation priorities or ecological zoning boundaries. Full article

Land and industrial systems form the cornerstone of regional sustainable development. Widespread misuse of land often accompanies industrial structure evolution (ISE), making the promotion of comprehensive land use benefits (LUB) a pivotal obstacle to regional sustainability. This study establishes an integrated framework to evaluate the dynamic characteristics of ISE and its interactive responses to multidimensional (ecological, social, and economic) LUB. The ISE assessment covers long-term changes in industrial investment, employment, and economic output, while LUB systematically integrates the ecological, social, and economic values of land resources. Combined with an enhanced genetic algorithm, a multi-objective optimization model is constructed and applied to 33 counties in Zhejiang Province, China. The results indicate that regional LUB exhibits obvious spatial heterogeneity and staged evolution from 2000 to 2020, with the regional industrial structure transforming from industrial-driven to service-oriented. The proposed model formulates targeted industrial adjustment pathways to resolve tertiary industry overinvestment and unbalanced secondary industry development. The optimization effectively promotes comprehensive land use sustainability, realizing differentiated regional progress including economic upgrading in the east, multidimensional coordination in the south, social benefit improvement in the north, and ecological sustainability promotion in the west. This study provides theoretical and practical references for high-quality regional sustainable development. Full article

As the core water source area of the Middle Route of the South-to-North Water Diversion Project, the Danjiangkou Reservoir Area plays a critical role in regional ecological security and water resource security. Its land use transitions and associated ecosystem service dynamics are examined. Based on land use, ecological sensitivity, and ecosystem service value data from 2000 to 2020, this study employed the FLUS model to simulate four scenarios—natural development, cropland protection, ecological protection, and ecological–cropland synergy—for 2050, systematically revealing the characteristics of land use transition, the coupled evolution of ecological sensitivity and ecosystem service value, and the trade-off mechanisms between ecological security and food security under multiple scenarios. The results show that: (1) From 2000 to 2020, land use in the reservoir area exhibited an ecological transition characterized by “two expansions and three contractions”: forestland and water bodies increased by 764.16 km² and 324.36 km², respectively, while cropland and grassland decreased by 664.33 km² and 547.08 km², the comprehensive index of land use degree declined by approximately 1.0%, indicating continuously weakening development intensity. (2) The overall hierarchical structure of ecological sensitivity improved, with the area of highly sensitive zones decreasing from 5201.60 km² to 3729.91 km²; however, the concentration risk of highly sensitive forestland and the unexpected increase in extremely sensitive cropland persisted. (3) Total ecosystem service value increased from CNY 51.92 billion to CNY 58.35 billion (+12.38%), with hydrological regulation contributing 79.83% of the total increment; regulating services remained the core functional type. Sensitivity analysis indicated that the coefficient of sensitivity (CS) values were below 1, confirming the robustness of the findings. (4) Multi-scenario simulations revealed a rigid ecological–food security trade-off: under natural development, ESV increased by 15.44% but cropland loss reached 1033.29 km²; under cropland protection, ESV decreased by 1.50%, the only scenario with negative ecological outcomes; under ecological protection, ESV increased by 16.59% but with the most severe cropland loss (−1072.98 km²); under ecological–cropland synergy, water bodies expanded the most substantially (+562.75 km²) while cropland loss was the most severe (−1118.19 km²), indicating that the synergy goal was not achieved, as gains in regulating services came at the cost of further provisioning services losses. The study confirms the positive effects of ecological land use transition in the reservoir area, while also highlighting the intensifying conflict between ecological protection and food security against the backdrop of ecological improvement. Full article

The tourism sector in the Sultanate of Oman is central to “Oman Vision 2040”, with a strategic focus of the government on its dynamic transformation. Coastal regions, vital to tourism, are affected by changes to the coastline due to flash floods, sea-water flooding, and erosion. Despite its implications for tourism and the economy, this topic remains relatively under-explored, especially as to use of Sentinel-1 satellite images. This study assesses water-level changes due to erosion in the urban coastal region of the Al-Batinah governorate via land cover classification. Using the Support Vector Machine (SVM) classification technique, the overall accuracy is found to be 97.7% and the Kappa coefficient value for the year 2018 is 1.0. Although, when using the Random Forest (RF) classification technique, the accuracy is nearly identical, there is varying precision for the water area. A critical observation is made, showing significant increase of the water area from 2.99% in the year 2017 to 12.36% in the year 2025, suggesting water encroachment. With fixed-effect and combined-effect size meta-analysis models, the confidence levels were identified as 95.0% and 0.37, respectively, indicating a consistent variation in water area that supports the outcomes of image classification. This study offers a valuable insight for policymakers as to managing coastal regions, along with providing assistance to vulnerable coastal communities. The study focuses on a particular governorate, given the satellite images, whereas a broader regional comparison would address the limitation of the generalizability of results. In the future, the research could integrate surveys from coastal communities and businesses for a comprehensive qualitative data perspective on the region’s tourism sector. Full article