Search Results (259)

This study analyzes spatiotemporal aridity dynamics in Central Kazakhstan (1960–2022) using a monthly Aridity Index (AI = P/PET), where P is precipitation and PET is potential evapotranspiration, Mann–Kendall trend analysis, and climate zone classification. Results reveal a northeast–southwest aridity gradient, with Aridity Index ranging from 0.11 to 0.14 in southern deserts to 0.43 in the Kazakh Uplands. Between 1960–1990 and 1991–2022, southern regions experienced intensified aridity, with Aridity Index declining from 0.12–0.15 to 0.10–0.14, while northern mountainous areas became more humid, where Aridity Index increased from 0.40–0.44 to 0.41–0.46. Seasonal analysis reveals divergent patterns, with winter showing improved moisture conditions (52.4% reduction in arid lands), contrasting sharply with aridification in spring and summer. Summer emerges as the most extreme season, with hyper-arid zones (8%) along with expanding arid territories (69%), while autumn shows intermediate conditions with notable dry sub-humid areas (5%) in northwestern regions. Statistical analysis confirms these observations, with northern areas showing positive Aridity Index trends (+0.007/10 years) against southwestern declines (−0.003/10 years). Key drivers include rising temperatures (with recent degradation) and variable precipitation (long-term drying followed by winter and spring), and PET fluctuations linked to temperature. Since 1991, arid zones have expanded from 40% to 47% of the region, with semi-arid lands transitioning to arid, with a northward shift of the boundary. These changes are strongly seasonal, highlighting the vulnerability of Central Kazakhstan to climate-driven aridification. Full article

As an integral component of humanity’s cultural heritage, traditional villages universally confront challenges such as population loss and cultural discontinuity amid rapid urbanization. Cluster-based protection models have increasingly become the international consensus for addressing the survival crisis of such settlements. This study selects the Central Yunnan region of Southwest China—characterized by its complex geography and multi-ethnic habitation—as the research area. Employing ArcGIS spatial analysis techniques alongside clustering algorithms, we examine the spatial distribution characteristics and clustering patterns of 251 traditional villages within this region. The findings are as follows. In terms of spatial distribution, traditional villages in Central Yunnan are unevenly dispersed, predominantly aggregating on mid-elevation gentle slopes; their locations are chiefly influenced by rivers and historical courier routes, albeit with only indirect dependence on waterways. Regarding single-cluster attributes, the spatial and geomorphological features exhibit a composite “band-and-group” pattern shaped by river valleys; culturally, two dominant modes emerge—“ancient-route-dependent” and “ethnic-symbiosis”—reflecting an economy-driven cultural mechanism alongside latent marginalization risks. Concerning construction characteristics, the “Qionglong-Ganlan” and Han-style “One-seal” residential features stand out, illustrating both adaptation to mountainous environments and the cumulative effects of historical culture. Based on these insights, we propose a three-tiered clustering classification framework—“comprehensive-element coordination”, “feature-led”, and “potential-cultivation”—to inform the development of contiguous and typological protection strategies for traditional villages in highland, multi-ethnic regions. Full article

Forest drought monitoring tools are crucial for managing tree water stress and enhancing ecosystem resilience. The Forest Drought Response Index (ForDRI) was developed to monitor drought conditions in forested areas across the contiguous United States (CONUS), integrating vegetation health, climate data, groundwater, and soil moisture content. This study evaluated ForDRI using Pearson correlations with the Bowen Ratio (BR) at 24 AmeriFlux sites and Spearman correlations with the Tree-Ring Growth Index (TRSGI) at 135 sites, along with feedback from 58 stakeholders. CONUS was divided into four forest subgroups: (1) the West/Pacific Northwest, (2) Rocky Mountains/Southwest, (3) East/Northeast, and (4) South/Central/Southeast Forest regions. Strong positive ForDRI-TRSGI correlations (ρ > 0.7, p < 0.05) were observed in the western regions, where drought significantly impacts growth, while moderate alignment with BR (R = 0.35–0.65, p < 0.05) was noted. In contrast, correlations in Eastern and Southern forests were weak to moderate (ρ = 0.4–0.6 for TRSGI and R = 0.1–0.3 for BR). Stakeholders’ feedback indicated that ForDRI realistically maps historical drought years and recent trends, though suggestions for improvements, including trend maps and enhanced visualizations, were made. ForDRI is a valuable complementary tool for monitoring forest droughts and informing management decisions. Full article

As a core karst region in Southwest China, Guanling County plays a crucial role in regional ecological governance. This study integrates the InVEST model, landscape pattern index analysis, and the MGWR spatial model to systematically explore the dynamic mechanisms of habitat quality in Guanling’s karst mountains. Key findings include: (1) Landscape pattern alterations exhibit significant impacts on habitat quality, characterized by strong spatial heterogeneity; (2) Expansion of forest and grassland effectively buffers the negative effects of construction land expansion, forming an ecological compensation mechanism through enhanced landscape connectivity; (3) Between 2000 and 2020, the proportion of high-importance habitat quality zones increased from 54.79% to 56.16%, with moderate-importance zones stabilizing at approximately 7.80% and general-importance zones growing to 2.46%. The results provide a multi-scale analytical framework for habitat protection and land use optimization in fragile karst ecosystems. Full article

The southwestern mountainous region of China (SMRC), characterized by complex geological environments, experiences frequent landslide disasters that pose significant threats to local residents. This study focuses on the Qijiang District of Chongqing, where we conduct a systematic evaluation of wavelength and observation geometry effects on InSAR-based landslide monitoring. Utilizing multi-sensor SAR imagery (Sentinel-1 C-band, ALOS-2 L-band, and LUTAN-1 L-band) acquired between 2018 and 2025, we integrate time-series InSAR analysis with geological records, high-resolution topographic data, and field investigation findings to assess representative landslide-susceptible zones in the Qijiang District. The results indicate the following: (1) L-band SAR data demonstrates superior monitoring precision compared to C-band SAR data in the SMRC; (2) the combined use of LUTAN-1 ascending/descending orbits significantly improved spatial accuracy and detection completeness in complex landscapes; (3) multi-source data fusion effectively mitigated limitations of single SAR systems, enhancing identification of small- to medium-scale landslides. This study provides critical technical support for multi-source landslide monitoring and early warning systems in Southwest China while demonstrating the applicability of China’s SAR satellites for geohazard applications. Full article

Karst mountain areas, as complex geological systems formed by carbonate rock development, possess unique three-dimensional spatial structures and hydrogeological processes that fundamentally influence regional ecosystem evolution, land resource assessment, and sustainable development strategy formulation. In recent years, through the implementation of systematic ecological restoration projects, the ecological degradation of karst mountain areas in Southwest China has been significantly curbed. However, the research on the fine-grained land use mapping and quantitative characterization of spatial heterogeneity in karst mountain areas is still insufficient. This knowledge gap impedes scientific decision-making and precise policy formulation for regional ecological environment management. Hence, this paper proposes a novel methodology for land use mapping in karst mountain areas using very high resolution (VHR) remote sensing (RS) images. The innovation of this method lies in the introduction of strategies of geographical zoning and stratified object extraction. The former divides the complex mountain areas into manageable subregions to provide computational units and introduces a priori data for providing constraint boundaries, while the latter implements a processing mechanism with a deep learning (DL) of hierarchical semantic boundary-guided network (HBGNet) for different geographic objects of building, water, cropland, orchard, forest-grassland, and other land use features. Guanling and Zhenfeng counties in the Huajiang section of the Beipanjiang River Basin, China, are selected to conduct the experimental validation. The proposed method achieved notable accuracy metrics with an overall accuracy (OA) of 0.815 and a mean intersection over union (mIoU) of 0.688. Comparative analysis demonstrated the superior performance of advanced DL networks when augmented with priori knowledge in geographical zoning and stratified object extraction. The approach provides a robust mapping framework for generating fine-grained land use data in karst landscapes, which is beneficial for supporting academic research, governmental analysis, and related applications. Full article

The near-surface air temperature lapse rate (SATLR) is a crucial parameter in climate, hydrology, and ecology research conducted in mountainous regions. However, existing research has difficulty characterizing its dynamic changes on an hourly scale. Obtaining data with high spatiotemporal resolution in complex terrains using existing methods poses challenges. This study introduces a hierarchical method for estimating SATLR at high spatiotemporal resolutions based on Fengyun-4A (FY-4A) Advanced Geostationary Radiation Imager (AGRI) land surface temperature (LST) data and machine learning techniques. Based on reconstructed FY-4A AGRI LST data, this study downscales the 4 km resolution data to a 1 km resolution using machine learning. It then estimates the spatial distribution of near-surface air temperature (SAT) and normalized near-surface air temperature (nSAT) by integrating station observations. Subsequently, high spatiotemporal resolution SATLRs are estimated, and their spatial and temporal distribution characteristics in the Beijing–Tianjin–Hebei mountainous region are analyzed. The results indicate that the SATLR exhibits a predominant distribution of 2~6 °C/km annually across the study area. However, in specific regions such as Taihang Mountains in the southwest, Damajun Mountain in the northwest, and certain areas of central Beijing City, the SATLR exceeds 6 °C/km in depth. Conversely, in Chengde City in the northeast and Huapiling in Damajun Mountain in the northwest, the SATLR is shallower than 2 °C/km. Seasonally, the average SATLR displays significant variation, with 3~5 °C/km being prevalent in spring, summer, and autumn, and 2~4 °C/km in winter. Moreover, the diurnal SATLR patterns from the second to fifth altitude grades exhibit consistency throughout the year and across seasons, albeit with varying overall values at different altitudes. Notably, the SATLR of the first altitude grade demonstrates stability within a day at lower elevations. Full article

Rural tourism plays a crucial role in promoting industrial revitalization in mountainous regions. Drawing inspiration from the site selection mechanisms of nature reserves, this study constructs a gap analysis framework tailored to rural tourism destinations, aiming to provide technical support for their spatial layout and systematic planning. By integrating a potential evaluation system based on tourism resources, market demand, and synergistic factors, the study identifies rural tourism priority zones and proposes a development typology and spatial optimization strategy across five provinces in Southwest China. The findings reveal: (1) First- and second-priority zones are primarily located in the core and periphery of provincial capitals and prefecture-level cities, while third-priority zones are concentrated in resource-rich areas of Yunnan and Guizhou and market-oriented areas of Sichuan, Chongqing, and Guangxi. (2) The Chengdu Plain emerges as the core region for rural tourism development, with hotspots clustered around Chengdu, northern and western Guizhou, central Chongqing, eastern Guangxi, and northwestern Yunnan, whereas cold spots are mainly situated in the western Sichuan Plateau and the Leshan–Liangshan–Zhaotong–Panzhihua–Chuxiong–Pu’er belt. (3) The alignment between tourism resources and rural tourism destinations is highest in Yunnan and Guizhou, while Chongqing exhibits the strongest match between destinations and tourism market potential and synergistic development conditions. Overall, 79.35% of rural tourism destinations in the region are situated within identified priority zones, with Chongqing, Guizhou, and Sichuan exhibiting the highest proportions. Based on the spatial mismatch between potential and existing destinations, the study delineates four development types—maintenance and enhancement, supplementation and upgrading, expansion, and reserve development—and offers regionally tailored planning recommendations. The proposed framework provides a replicable approach for spatial planning of rural tourism destinations in complex mountainous settings. Full article

Against the historical background of the rural revitalization strategy and coordinated regional development, rural characteristic industries constitute the fundamental impetus and strategic avenue for rural spatial commodification processes in the mountainous region of southwest China. As a crucial pathway for enhancing rural spatial value, the driving mechanisms and implementation approaches of rural spatial commodification require urgent theoretical elucidation. This study employs spatial production theory as its analytical framework and adopts a case study approach focusing on Zhongxin Village in the mountainous region of southwest China. Through in-depth interviews, participatory observations, and textual analyses, this study endeavors to unpack the intricate internal logic underpinning the process by which rural characteristic industries propel rural spatial commodification. The research findings demonstrate that under the collaborative mechanism of “government guidance–elite mobilization–villager participation–market penetration,” the systematic synthesis of regional resource endowments, cultural legacies, and market imperatives has culminated in the reconfiguration of local economic structures and the reproduction of rural landscapes. This study further elucidates the structural constraints and potential solutions encountered in the process of rural spatial commodification in southwest China’s mountainous hinterlands. This research provides region-specific implementation pathways for developing characteristic industries and advancing spatial commodification in these regions with geographical location disadvantages and weak economic development, offering significant policy implications for rural revitalization strategies. Full article

Mountain forests in biodiversity hotspots show complex responses to climate and topographic gradients. However, the effect of synergistic controls of elevation and climate on Net Primary Productivity (NPP) dynamics remain insufficiently quantified in complex mountains. Southwest China’s mountains are Asia’s most biodiverse temperate region with pronounced vertical ecosystem stratification, representing a critical continental carbon sink. This study investigated the spatiotemporal dynamics and driving mechanisms of NPP in Southwest China’s typical mountain ecosystems over the past three decades using a high-resolution modeling framework integrated with relative importance analysis, a Geodetector, and an elevation-dependent model. The results showed that (1) NPP revealed a significant increasing trend, rising from 634 ± 325 to 748 ± 348 g C m⁻² yr⁻¹ (mean rate 4 g C m⁻² yr⁻¹) from 1990 to 2018. Spatially, the most rapid increases occurred in eastern regions. (2) Rising CO₂ and climate warming (dominate 17% regions) drove interannual NPP growth, with elevation thresholds dictating driver dominance. The CO₂ governed low elevation, while temperature controlled higher elevation (>4800 m). (3) The elevation-dependent model revealed a more complex and nonlinear relationship between NPP and elevation, identifying three distinct phases: the saturation phase (<500 m) with negligible decay of NPP; the transition phase (500–3500 m) with linear decline (NPP loss of 29 g C m⁻² yr⁻¹ per 100 m); and the collapse phase (>3500 m) with continuously attenuated NPP losses (NPP average loss of 10.5 g C m⁻² yr⁻¹ per 100 m) reflecting high-elevation vegetation adaptation to extreme conditions. (4) Land cover dominated NPP spatial heterogeneity and was amplified by interactions with elevation and temperature, highlighting a vegetation–climate–topography coupling mechanism that critically shapes productivity patterns. Biodiversity-rich widespread mixed forests underpinned the region’s high productivity. Mountain protection should focus on protecting existing evergreen forests from fragmentation, while forestation should prioritize the establishment of biodiversity-rich mixed forest. These findings established a comprehensive framework for spatiotemporal analysis of driving mechanisms and enhanced the understanding of NPP dynamics in complex mountain ecosystems, informing sustainable management priorities in mountain regions. Full article

By constructing a comprehensive evaluation index system for the development level of Agricultural Machinery Socialization Services (AMSS) in China’s hilly and mountainous areas, the article adopts the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) entropy weight method to carry out a comprehensive evaluation of the development level of AMSS in China’s 17 major hilly mountainous provinces, and utilizes the obstacle degree model and the Dagum Gini coefficient decomposition method to deeply explore the developmental constraints and regional differences in characteristics. The results of the study show that the development level of AMSS in all provinces is generally on the rise, and the overall development level of the Southwest region is relatively lagging behind, with significant differences from other regions. The obstacle degree model shows that industrial development, Government funding, and farmland construction are the main factors constraining AMSS in hilly and mountainous areas, specifically, the degree of coverage of AMSS, the percentage of agricultural machinery professional cooperatives, the degree of land fragmentation, and the level of agricultural machinery extension inputs have a greater impact on the level of development of AMSS. Dagum Gini coefficient calculations show that the overall relative differences in development levels have a tendency to decrease, but the level of development of agricultural machinery socialization in the southwestern hilly and mountainous second-maturity areas is still low, with an imbalance in development within the region and a more significant gap with the development levels of other hilly and mountainous regions. Full article

An urban–rural–natural imbalance is evident; investigating the spatiotemporal evolution of the transitional geo-space (TG) between them facilitates the integration of urban–rural land use planning. In this study, we proposed a complex system model to explore the interactive dynamics between the social–economic systems and natural ecosystems of Changning County, Southwest China, with the TG being identified and classified across the two systems. Based on a three-dimensional “direction–speed–pattern” framework, we further quantified production–living–ecological space (PLE) changes and examined the impacts of these changes on the TG from 2000 to 2022. The results are as follows: (1) The TG was classified into five categories that were stratified according to the coupling intensity and orientation of the socioeconomic system and natural ecosystems in Changning County. (2) The transition type with the most complex socio-ecological coupling was the type of semi-socioeconomic process–semi-natural ecological process, occupying 32.6% (309.4 km²) of the county’s total area in 2000 and demonstrating the most pronounced spatial dynamics, exhibiting a reduction of 78.6 km² during the study period. (3) Negative impacts on TG dynamics were observed for the conversion of ecological space into agricultural production space (p < 0.01; R² > 0.24) and the dynamic degree of PLE transformations (p < 0.01; R² > 0.13). (4) The impacts of trends in PLE on the TG varied significantly across temporal phases, whereas the CONTAG index exhibited consistently non-significant effects throughout all study periods. This study provides a new insight into understanding the optimization of spatial development patterns in urban–rural–natural regions and offers theoretical support for the governance of national land space and high-quality economic and social development in mountainous areas. Full article

The southwest region of China is characterized by numerous rugged mountains and valleys, which create favorable conditions for landslide disasters. The landslide-influencing factors show different sensitivities regionally, which induces the occurrence of disasters to different degrees, especially in small sample areas. This study constructs a framework for the identification, analysis, and evaluation of landslide hazards in complex mountainous regions within small sample areas. This study utilizes small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technology and high-resolution optical imagery for a comprehensive interpretation to identify landslide hazards. A geodetector is employed to analyze disaster-inducing factors, and machine-learning models such as random forest (RF), gradient boosting decision tree (GBDT), categorical boosting (CatBoost), logistic regression (LR), and stacking ensemble strategies (Stacking) are applied for landslide sensitivity evaluation. GMLCM stands for geodetector–machine-learning-coupled modeling. The results indicate the following: (1) 172 landslide hazards were identified, primarily concentrated along the banks of the Lancang River. (2) A geodetector analysis shows that the key disaster-inducing factors for landslides include a digital elevation model (DEM) (1321–1857 m), rainfall (1181–1290 mm/a), the distance from roads (0–1285 m), and geological rock formation (soft rock formation). (3) Based on the application of the K-means clustering algorithm and the Bayesian optimization algorithm, the GD-CatBoost model shows excellent performance. High-sensitivity zones were predominantly concentrated along the Lancang River, accounting for 24.2% in the study area. The method for identifying landslide hazards and small-sample sensitivity evaluation can provide guidance and insights for landslide monitoring and harnessing in similar geological environments. Full article

The southwestern region of China is tectonically situated within the Tethyan tectonic domain, with the eastern part comprising the Upper Yangtze Block, while the western orogenic belt forms the main part of the Tibetan Plateau. This belt was formed by the subduction of the Paleo-Tethys Ocean and subsequent arc-continent collision, and was later further modified by the India-Asia collision, resulting in complex geological structures such as the Hengduan Mountains. The lithostratigraphy in this region can be divided into six independent units. In terms of mineralization, the area encompasses two first-order metallogenic domains: the Tethyan-Himalayan and the Circum-Pacific. This study synthesizes extensive previous research to systematically investigate representative rare earth element (REE) deposits (e.g., Muchuan and Maoniuping in Sichuan; the Xinhua deposit in Guizhou; the Lincang deposit in Yunnan). Through comparative analysis of regional tectonic-metallogenic settings, we demonstrate that REE distribution in Southwest China is fundamentally controlled by Tethyan tectonic evolution: sedimentary-weathered types dominate in the east, while orogenic magmatism-related types prevail in the west. These findings reveal critical metallogenic patterns, establishing a foundation for cross-regional resource assessment and exploration targeting. The region hosts 32 identified REE occurrences, predominantly light REE (LREE)-enriched, genetically classified as endogenic, exogenic, and metamorphic deposit types. Metallogenic epochs include Precambrian, Paleozoic, and Mesozoic-Cenozoic periods, with the latter being most REE-relevant. Six prospective exploration areas are delineated: Mianning-Dechang, Weining-Zhijin, Long’an, Simao Adebo, Shuiqiao, and the eastern Yunnan-western Guizhou sedimentary-type district. Notably, the discovery of paleo-weathering crust-sedimentary-clay type REE deposits in eastern Yunnan-western Guizhou significantly expands regional exploration potential, opening new avenues for future resource development. Full article

Optimizing the allocation of basic educational facilities in mountainous rural areas is important for narrowing the education gap between urban and rural areas, constructing high-quality regional education systems, and achieving sustainable education development. This paper considered preschool, primary, and secondary schools in Qixingguan District, which is located in a mountainous area of China, using vector data of rural residential areas and educational facility points as a source of information on supply and demand. The study combined travel modes and acceptable time of rural school-age population, and applied the Gaussian two-step mobile search method to calculate the level of accessibility of basic educational facilities at the scale of residential areas. Location optimization and scale optimization models were used to determine the optimal location and service qualities for basic educational facilities. Our results yielded three main conclusions. First, the spatial pattern for the distribution density and accessibility of basic educational facilities in Qixingguan differed at all stages, but all of them showed a strong orientation toward the central urban area. Service capacity in each stage tended to extend toward the northeast and southwest, except for a certain orientation toward the central urban area. Second, the main reason for the low spatial accessibility of schools was that the density and service capacity of the available schools did not align with the distribution of the school-age population. Third, after optimizing for location and service capacity, schools at all stages shifted to the northeast of Qixingguan, which reduced the difference in service capacity between schools and improved the accessibility and balance of schools in the northeast and southwest. Full article