Search Results (5,846)

Myanmar, an agriculture-based economy, is one of the most important agricultural countries in mainland Southeast Asia. Although previous studies have documented changes in agricultural land-use and cropping patterns, trends in farmland area, cropping patterns, and food sufficiency across Myanmar’s 14 states/regions remain limited. This study addresses these gaps by using land-cover data from the global 30 m dynamic dataset and statistical data from 2000 to 2025, and household surveys from selected areas. GIS-based spatial analysis, trend analysis, and multivariate analysis of variance were applied to analyze both the direction and magnitude of farmland and cropping pattern changes over time. The results showed that Myanmar’s farmland area increased significantly (τ = +0.52, p < 0.01), expanding by 23.6% over the study period. Double cropping remained an important system, increasing by 55.9%. In the central dry zone, sufficient water availability showed the strongest effect on crop production and farmland area (F = 11.191, p < 0.001, η²p = 0.037), followed by soil fertility loss (F = 10.263, p < 0.001, η²p = 0.034). The analysis estimated that domestic consumption requirements were approximately 7.97 million tons of rice, 3.12 million tons of wheat, and 0.42 million tons of maize. These findings can support sustainable farmland use planning and inform food security policy decisions in Myanmar. Full article

Rainfall characteristics, differences in catchment storage, soil moisture dynamics, and geophysical properties influence spatial and temporal variability of runoff generation thresholds. This study addresses two questions: (1) Are there nonlinear thresholds of rainfall or antecedent moisture that trigger abrupt changes in agricultural catchments’ hydrological response? (2) What physical characteristics determine runoff generation? We analyzed precipitation and streamflow variability during the 2025–2026 hydrological year at three agricultural catchments (36.4–70.8 km²) in central Chile. Relying on high-resolution observational data and statistical segmented regression, this study focuses on how rainfall, soil moisture, and physical characteristics trigger runoff activation after exceeding specific thresholds. Based on 63 rainfall events, runoff occurred in only 16 events, demonstrating a strong nonlinear response governed by antecedent moisture. Segmented regression revealed consistent activation thresholds across all catchments when combined precipitation and deep soil moisture (PTOT + ASM100) exceeded ~505 mm, evidencing strong subsurface control. However, runoff efficiency diverged sharply along the land-use gradient. The most intensively agricultural catchment exhibited the highest specific peak discharge and a unique rainfall intensity threshold (14.6 mm/h), indicating rapid infiltration-excess runoff driven by degraded soil permeability. Conversely, catchments with higher headwater or riparian forest cover buffered these rapid flows, sustaining baseflow and extending recession times. Full article

The role of land use/land cover (LULC) dynamics in predisposing slopes to shallow landsliding is widely acknowledged but seldom translated into operational susceptibility modelling. Most data-driven approaches still treat LULC as a static factor, neglecting the legacy effects of recent transitions. This study presents a methodological framework to quantify the influence of multi-temporal LULC changes on shallow landslide initiation and to incorporate this information into susceptibility mapping. The procedure was tested in the Metropolitan City of Messina (formerly known as the Province of Messina), Southern Italy, a representative Mediterranean area repeatedly affected by rainfall-triggered slope failures. Freely available LULC maps from 1990 to 2006 were processed through post-classification change detection to identify dominant land cover trajectories. Preliminary analyses within buffer areas showed higher landslide indices (LI, LAI) and Frequency Ratios for some transition classes, suggesting a potential role of LULC changes. These findings motivated the comparison between a static LULC configuration and a dynamic one incorporating the detected transitions within a Frequency Ratio susceptibility model. The dynamic model did not improve the mean Area Under the Curve (AUC) compared to the static model (0.7774 vs. 0.7742), and the observed reduction in variability across five independent random splits (standard deviation 0.012 vs. 0.064) should be considered preliminary. The proposed workflow, based entirely on open data and GIS-based processing, offers a transparent and reproducible methodology for integrating LULC transitions into dynamic susceptibility maps. The use of higher-resolution input data could potentially reduce the scale mismatch and improve the detection of fine-scale transitions, supporting more effective landslide risk mitigation and evidence-based land planning. Full article

High-density valley residential areas face poor ventilation and heat island effects. Taking Lanzhou’s Xin’an Residential Area as a case, this study integrates land use and cover change (LUCC), circuit theory, and CFD to construct a resistance surface, identify corridors and key nodes, reveal coupling mechanisms and propose collaborative optimization strategies. Results show the following: (1) Ventilation resistance presents a pattern of “low in the north, high in the south, permeable at the periphery, obstructed in the interior”, with high-resistance zones accounting for 18% of the grid area; green plot ratio is the most sensitive regulatory factor (standardized regression coefficient = −0.679). (2) The fishbone-like ventilation network has primary hub nodes undertaking 80% of airflow transport, while tertiary terminal nodes (73% of total nodes) are the main ventilation bottlenecks. (3) Built-up land morphological indicators show strong spatial collinearity, and the positive effect of road plot ratio is masked in the regression model. The proposed hierarchical micro-renewal strategy provides an operable technical pathway for wind environment optimization, low-carbon renewal and climate-adaptive retrofitting of high-density valley residential areas. This study extends circuit theory to micro-scale ventilation analysis and establishes a replicable quantitative framework for ventilation diagnosis in analogous valley residential contexts. Full article

Understanding land-cover change in savanna systems requires approaches that account for ecological gradients and human land use across multiple spatial scales. This study examines land-cover dynamics in Niassa Special Reserve (NSR), Mozambique, and its surrounding buffer from 2000 to 2024. Land cover was classified from satellite imagery using random forest, achieving ~98% overall accuracy, and change was quantified across landscape, management, and local scales. Model robustness was assessed across 1000 iterations, and classification uncertainty was propagated through 10,000 Monte Carlo simulations. Results show a shift toward denser vegetation within NSR, with increases in open and dense woodland and declines in grass-dominated areas. Closed-canopy forest increased by approximately 552 km² within NSR (95% MCSI: 375–586 km²), but declined by approximately 1549 km² in the surrounding buffer (95% MCSI: −1499 to −1226 km²). Community-use areas within NSR collectively lost approximately 969 km² of closed-canopy forest (95% MCSI: −1014 to −954 km²). Dominant transitions occurred between adjacent vegetation classes, indicating structural change rather than discrete categorical conversion. These results indicate that protection is associated with greater persistence and expansion of woody vegetation at the landscape scale, while localized human use areas show contrasting trajectories. Full article

Accurate retrospective, spatially explicit land-use reconstruction is essential for Land Use, Land-Use Change and Forestry (LULUCF) greenhouse gas accounting. However, the suitability of historical geospatial databases as information sources for such reconstruction has rarely been evaluated systematically. This study proposes an objective framework for assessing their correspondence with land-use observations from the Lithuanian National Forest Inventory (NFI). The analysis was based on a reference set of 16,351 systematically distributed NFI sample points and 19 database-year datasets covering the period 1990–2022. Original database classes were harmonised with the national hierarchical LULUCF classification, and correspondence was evaluated using overall accuracy, Cramér’s V and Normalized Mutual Information (NMI), complemented by category-specific representation, precision, recall and F1 score. Correspondence varied substantially among databases according to thematic scope, spatial completeness, mapping characteristics and land-use category. Among the multi-category databases, the Georeferenced Base Cadastre (GRPK) showed the strongest overall correspondence with the NFI reference data, whereas the CORINE Land Cover series provided the longest consistent multi-temporal record extending back to 1990. Forest land and settlements, as well as particularly water-related wetland classes, were represented comparatively reliably, while grassland remained the most difficult major land-use category to identify consistently. Temporal analysis showed that database performance also varied between database versions, while boundary sensitivity analysis demonstrated that observations near mapped polygon boundaries contributed to disagreement without changing the relative advantage of GRPK over CORINE. The results demonstrate that the evaluated historical databases provide substantial and complementary information for spatially explicit LULUCF land-use reconstruction and that the proposed framework provides a transparent basis for identifying and selecting suitable information sources according to land-use category and historical period. Full article

Major floods following prolonged drought can substantially alter ground cover, soil stability and pasture condition, yet longer-term trajectories of rangeland recovery remain poorly understood. This study assessed land condition at 62 monitoring sites in the Flinders River catchment, north-west Queensland, following the 2019 flood, with re-assessment in 2024. Land condition was evaluated using the A–B–C–D framework alongside rainfall, satellite-derived bare ground, land type, distance to drainage and flood-extent data. In March 2019, 79% of sites were classified as C or D, reflecting the combined influence of prolonged drought and flood disturbance. By 2024, 30 of 62 sites (48%) had improved by at least one class, and median condition shifted from class C to B, though change was spatially variable. Initial land condition was negatively correlated with net change (ρ = −0.47, p < 0.001, n = 62). Rainfall showed no significant association with land condition or net change among sites, whereas dry-season bare ground was significantly associated across multiple temporal windows. These findings indicate that land condition change following drought–flood disturbance is likely associated with site-level factors, particularly residual pasture structure and soil surface condition, and highlight the value of combining field and satellite data for rangeland monitoring following extreme climate events. Full article

Drought is a complex and periodic issue that has a significant impact on agriculture and water resources, particularly in semi-arid areas. This study evaluated meteorological and agricultural drought conditions in the Thanjavur district by combining rainfall data with remote-sensing methods. Meteorological drought was analyzed using 33 years of rainfall data and the Standardized Precipitation Index (SPI) (1992–2024) using 20 rainfall stations for the data available between 1992 and 2024. The spatial variation in rainfall was analyzed using Kriging interpolation in GIS. Agricultural droughts were analyzed using the Normalized Difference Vegetation Index (NDVI) and Vegetation Con0dition Index (VCI) using multi-temporal Landsat satellite images (Landsat 5 and Landsat 8). Land Use and Land Cover (LULC) classification was included to determine drought vulnerability across different land types. The NDVI and VCI indices showed an intensification of agricultural drought in 2010. The results demonstrated temporal and spatial differences in drought conditions for the years 1992, 1997, 2004, 2009, 2014, 2019, and 2024 and indicated that the region experienced periodic severe drought conditions of 3%, 3%, 3%, 8%, 19%, 9%, and 11% in the study area, respectively. During the drought period, the vegetation indices showed a strong sensitivity of agricultural areas to changes in rainfall, and low NDVI and VCI values indicated increased vegetation stress. Meteorological and agricultural droughts were integrated using the Analytical Hierarchy Process (AHP) method by combining various indicators to analyze the drought condition across the Thanjavur district. The multiple criteria decision-making (MCDM) method uses pairwise comparisons of various factors, such as giving high importance to SPI and rainfall, followed by vegetation indices and LULC. The consistency ratio validated the reliability of the weighting term. This method shows that combining meteorological and remote sensing indicators advances a robust framework for monitoring and assessing droughts. Conceptual droughts illustrate how meteorological droughts are associated with the development of agricultural droughts. The results of this study can be adopted for effective drought management, irrigation planning, and sustainable agricultural practices in this region. Full article

Urban resilience (UR) is shaped by multiple interacting factors, yet existing studies have paid limited attention to the differentiated nonlinear and interactive mechanisms across different resilience dimensions. Based on panel data from 110 prefecture-level and above cities in the Yangtze River Economic Belt (YREB) from 2015 to 2024, this study adopts a four-dimensional framework covering social, economic, ecological, and infrastructure resilience. Spatial analysis and the XGBoost-SHAP model are combined to examine the spatiotemporal evolution, key drivers, nonlinear responses, turning point characteristics, and factor interactions of overall UR and its four dimensions. The results show that overall UR increased steadily, while the four dimensions followed distinct evolutionary trajectories: economic and infrastructure resilience improved most rapidly, ecological resilience increased steadily, and social resilience improved relatively slowly. The importance and effects of key drivers also varied across overall resilience and its four dimensions. Major factors, including technological investment, non-registered population, unemployment insurance coverage, land use, and natural population growth, exhibited distinct nonlinear responses and turning point characteristics, with their effects changing across different variable levels. Furthermore, significant interactions were identified among population and industrial structure, population and transportation, industry and technology, and industry and social security across different resilience dimensions. Overall, UR in the YREB is characterized by differentiated development, nonlinear responses, nonlinear transition patterns, and joint influences of multiple factors. Full article

Cropland use stability is vital for sustaining the productive and ecological functions of cropland. Existing multidimensional assessment frameworks rarely distinguish between quantity change and spatial change, nor do they examine their interactions across hierarchical scales. Using annual 30 m land cover data for Guangdong Province, China (1990–2024), this study developed a two-dimensional stability framework integrating quantity and spatial indicators, using a pixel-tracking strategy applied within each five-year interval to capture interannual dynamics. Analyses were conducted at provincial, agricultural zone, and city scales. Results showed that provincial stability exhibited a fluctuating upward trajectory, with the lowest point in 2005–2009. Regional patterns diverged markedly, and city-level stability exhibited spatial heterogeneity, with pronounced disparities between high- and low-stability cities. Grade transition and quadrant analyses further revealed that quantity and spatial stability do not always move in tandem, and single-dimension assessments may provide an incomplete picture of cropland use stability. These findings suggest that incorporating both dimensions into monitoring frameworks could support more differentiated cropland management strategies. Full article

Floodplains sustain fisheries, water supply, and climate regulation, and their services depend on the water regime—the extent, depth, frequency, duration, and connectivity of inundation—which dams, drought, and land-use change are altering. Remote sensing and GIS can supply evidence for managing these systems sustainably, yet the methods remain dispersed, and their fit to management needs has not been assessed. Following the PRISMA Extension for Scoping Reviews (PRISMA-ScR) and a publicly posted protocol, we retrieved peer-reviewed studies from Dimensions and OpenAlex (2004–2026), searched on 13 July 2026 and updated on 14 August 2026, and screened them in two stages with two reviewers. We charted data by study area, sensors, methods, variables, and drivers, then mapped them onto the decisions and Sustainable Development Goal targets they inform. Of 137 studies, 53% appeared since 2021; 2026 is only partially covered. Inundation extent dominates (83%), mapped mainly with Landsat (36%) and radar, whereas water level (28%), connectivity (21%), inundation frequency (14%), storage (13%), hydroperiod (12%), and depth (8%) remain scarce, as does evidence from data-scarce transboundary basins, including Central Asia. The attributes most needed for environmental-flow, allocation, and restoration decisions thus appear to be the least observed—a decision–observation mismatch that shapes monitoring priorities. Full article

This study evaluates the structural dynamics of the landscape within the Sierra de San Pedro and Embalse de Cornalvo Special Areas of Conservation between 2006 and 2018 to determine the effect of land-use spatial configuration on ecosystem stability. Methodologically, Corine Land Cover cartography was geoprocessed in QuantumGIS utilising the LecoS plugin to calculate five landscape metrics. The results reveal marked stability within the agroforestry matrix of both protected areas, demonstrating the effectiveness of their conservation status against drastic land-use changes. Nonetheless, contrasting internal trajectories were identified: the Sierra de San Pedro experienced a process of silent reforestation and the unification of natural habitats (characterised by a reduction in patch numbers and an increase in mean patch size), whereas the Cornalvo landscape exhibited strong structural homogeneity dominated by human activity. It is concluded that while the Sierra de San Pedro is evolving towards forest maturation and robust internal connectivity, Cornalvo maintains a structural inertia of absolute stability. These findings demonstrate the importance of incorporating spatial metrics into environmental management to strengthen ecosystem resilience to change. Full article

Reliable spatial evidence can support quality assurance and quality control for land use, land-use change and forestry (LULUCF), but land-cover and species-distribution layers do not by themselves identify IPCC Forest Land or species-pure stands. We estimated 2010 and 2020 above- and below-ground living biomass carbon within tree-covered European beech (Fagus sylvatica L.) distribution and occurrence footprints in Greece. Our operational hypothesis was that increasingly restrictive species masks would materially alter the mapped extent and carbon estimates. ESA Climate Change Initiative Biomass v6, ESA WorldCover 2021, European Forest Genetic Resources Programme (EUFORGEN) polygons, and Forest Information System for Europe (FISE) relative probability of presence layers were processed in Google Earth Engine. Biomass was converted with IPCC default carbon fractions and root:shoot ratios, and the results were summarized nationally and for GAUL Level-2 units. The broad EUFORGEN footprint covered 22,133 km², whereas the Combined overlap of EUFORGEN, FISE relative probability of presence ≥ 0.50, and tree cover covered 2742 km². Within the Combined footprint, the pixel mean living biomass carbon density was 60.33 Mg C ha⁻¹ in 2010 and 62.50 Mg C ha⁻¹ in 2020, and the area-integrated change was +0.58 Tg C; the area-normalized regional change was positive in 13 of 17 units and negative in 4. Across masks, the mean decadal change ranged from −0.50 to +3.37 Mg C ha⁻¹ and the approximate area-integrated totals from −1.10 to +0.58 Tg C. These scenario-conditioned estimates are neither official national greenhouse gas inventory estimates nor tests of statistical significance; instead, they provide reproducible spatial screening while making mask sensitivity and unpropagated uncertainty explicit. Full article

The increasing tourism pressure on the UNESCO World Heritage Altai Mountains calls for efficient environmental monitoring tools. This study presents a Google Earth Engine framework that couples the Remote Sensing Ecological Index (RSEI) with land use/land cover (LULC) mapping to assess ecological changes in the Lake Manzherok area between 2020 and 2025. RSEI was derived from Sentinel-2 and Landsat imagery by combining four indicators (NDVI, MNDWI, NDBSI, LST) through principal component analysis. LULC classification was carried out using Random Forest trained exclusively on Sentinel-2 spectral bands. The results confirm that RSEI effectively captures ecological gradients in complex mountainous terrain, with the first principal component explaining 57–62% of the total variance. While 92% of the study area remained stable, 5.9% showed a decline in ecological status, spatially coinciding with a near doubling of built-up and bare surfaces from 9.89 km² to 18.17 km². The largest negative RSEI changes were associated with transitions from forestland (ΔRSEI = −0.29) and grassland (ΔRSEI = −0.20) to built-up/bare land, whereas reverse transitions displayed positive ΔRSEI values. These spatial patterns are consistent with the visible development related to tourism. However, because the built-up/bare land class also includes naturally bare surfaces, and because interannual climate variability may affect the RSEI components, it is important to interpret the ΔRSEI values as relative changes rather than absolute measurements of tourism impact. The proposed framework provides a reproducible and transferable tool for monitoring ecological quality in data-scarce mountain regions, delivering spatially explicit evidence that can support conservation and land-use planning. Full article

Assessing the effectiveness of protected areas is crucial for refining conservation policies, yet it remains challenging in remote, biodiversity-rich tropics due to logistical constraints. To address this challenge, we developed a remote sensing-based Pressure–State–Benefit (PSB) framework comprising four dimensions: human activity, ecosystem pattern, ecosystem quality, and ecosystem services. Using the Hainan Tropical Rainforest National Park (HTRNP) as a case study, we evaluated conservation effectiveness at the park scale by comparing ecological changes before (2015–2020) and after (2020–2025) its establishment. We further compared the Core Protection Zone (CPZ) and the General Control Zone (GCZ) to reveal differences in conservation outcomes under distinct management regimes. The establishment of HTRNP effectively curbed cropland and built-up land expansion. During 2020–2025, landscape patterns improved, characterized by enhanced connectivity and reduced fragmentation. Concurrently, fractional vegetation cover increased at an accelerated rate, indicating improved ecosystem quality, while key ecosystem services showed upward trends. Notably, the CPZ maintained superior ecological conditions with steady improvements under strict protection, whereas the GCZ, being more sensitive to human disturbances, exhibited fluctuating outcomes. This study demonstrates the effectiveness of HTRNP in enhancing regional ecosystem conditions and highlights the importance of zoned management. Furthermore, the proposed PSB framework offers a transferable approach for comprehensively assessing conservation effectiveness in other protected areas. Full article