Search Results (47)

The Cao’e-Jiaojiang-Oujiang River Basin possesses abundant vernacular architectural heritage with significant historical–cultural value. However, challenges like dispersed distribution and inconsistent conservation hinder its systematic protection and utilization within territorial spatial planning, necessitating a deeper understanding of its spatiotemporal patterns. Utilizing 570 identified heritage sites, this study employed ArcGIS spatial analysis (Kernel Density Estimation, Nearest Neighbor Index), correlation analysis with DEM data, and suitability analysis (Minimum Cumulative Resistance model, Gravity Model) to systematically examine spatial distribution characteristics, their evolution, and relationships with the geographical environment and historical context. Results revealed a distinct “four cores and three belts” spatial pattern. Temporally, distribution evolved from “discrete” (Song-Yuan) to “aggregated” (Ming-Qing) and then “diffused” (Modern era). Spatially, heritage showed density in plains, preference for low slopes, and settlement along waterways. Suitability analysis indicated higher corridor potential in the northern section (Cao’e-Jiaojiang) than the south (Oujiang), leading to the identification of a “Northern Segment (Shaoxing-Ningbo-Shengzhou-Taizhou)” and “Southern Segment (Wenzhou-Lishui)” corridor structure. This research provides a scientific basis for systematic conservation and integrated heritage corridor construction of vernacular architectural heritage in the basin, supporting Zhejiang’s Poetry Road Cultural Belt initiatives and cultural heritage protection within territorial spatial planning. Full article

Ecological network construction has been widely accepted and applied to guide regional ecological conservation and restoration. For arid regions, ecological networks proposed based on ecological risk assessments are better aligned with the sensitive and fragile characteristics of local ecosystems. This study assesses landscape ecological risk in Wensu County, located on the southern slope of the Tianshan Mountains in the arid region of northwestern China, and it further proposes an optimized ecological network. A multidimensional framework composed of the natural environment, human society, and landscape patterns was employed to construct an ecological risk assessment system. Spatial principal component analysis (SPCA) was applied to identify the spatial pattern of ecological risk. Morphological spatial pattern analysis (MSPA) and a minimum cumulative resistance (MCR) model integrated with circuit theory were used to extract the ecological sources and delineate the ecological corridors. The results reveal significant spatial heterogeneity in terms of ecological risk: Low-risk zones (16.26%) are concentrated in the southwestern forest and water areas. In comparison, high-risk zones (28.27%) are mainly distributed in the northern mountainous mining region. A total of 24 ecological source patches (4105.24 km²), 44 ecological corridors (313.6 km), 39 ecological pinch points, and 38 ecological barriers were identified. Following optimization, the Integral Index of Connectivity (IIC) increased by 89.04%, and the Landscape Coherence Probability (LCP) rose by 105.23%, indicating markedly enhanced ecological connectivity. The current ecological network exhibits weak connectivity in the south and fragmentation in the central region. Targeted restoration of critical nodes, optimization of corridor configurations, and expansion of ecological sources are recommended to improve landscape connectivity and promote biodiversity conservation. Full article

This study focuses on the systematic conservation of historical architectural heritage in Heilongjiang Province, particularly addressing the challenges of point-based protection and spatial fragmentation. It explores the construction of a connected and conductive heritage corridor network, using historical building clusters across the province as empirical cases. A comprehensive analytical framework is established by integrating the nearest neighbor index, kernel density estimation, minimum cumulative resistance (MCR) model, entropy weighting, circuit theory, and network structure metrics. Kernel density analysis reveals a distinct spatial aggregation pattern, characterized by “one core, multiple zones.” Seven resistance factors—including elevation, slope, land use, road networks, and service accessibility—are constructed, with weights assigned through an entropy-based method to generate an integrated resistance surface and suitability map. Circuit theory is employed to simulate cultural “current” flows, identifying 401 potential corridors at the provincial, municipal, and district levels. A hierarchical station system is further developed based on current density, forming a coordinated structure of primary trunks, secondary branches, and complementary nodes. The corridor network’s connectivity is evaluated using graph-theoretic indices (α, β, and γ), which indicate high levels of closure, structural complexity, and accessibility. The results yield the following key findings: (1) Historical architectural resources in Heilongjiang demonstrate significant coupling with the Chinese Eastern Railway and multi-ethnic cultural corridors, forming a “one horizontal, three vertical” spatial configuration. The horizontal axis (Qiqihar–Harbin–Mudanjiang) aligns with the core cultural route of the railway, while the three vertical axes (Qiqihar–Heihe, Harbin–Heihe, and Mudanjiang–Luobei) correspond to ethnic cultural pathways. This forms a framework of “railway as backbone, ethnicity as wings.” (2) Comparative analysis of corridor paths, railways, and highways reveals structural mismatches in certain regions, including absent high-speed connections along northern trunk lines, insufficient feeder lines in secondary corridors, sparse terminal links, and missing ecological stations near regional boundaries. To address these gaps, a three-tier transportation coordination strategy is recommended: it comprises provincial corridors linked to high-speed rail, municipal corridors aligned with conventional rail, and district corridors connected via highway systems. Key enhancement zones include Yichun–Heihe, Youyi–Hulin, and Hegang–Wuying, where targeted infrastructure upgrades and integrated station hubs are proposed. Based on these findings, this study proposes a comprehensive governance paradigm for heritage corridors that balances multi-level coordination (provincial–municipal–district) with ecological planning. A closed-loop strategy of “identification–analysis–optimization” is developed, featuring tiered collaboration, cultural–ecological synergy, and multi-agent dynamic evaluation. The framework provides a replicable methodology for integrated protection and spatial sustainability of historical architecture in Heilongjiang and other cold-region contexts. Full article

The Southwest Region (SWR) is one of Nigeria’s six geo-political zones and comprises six distinct states. It holds considerable significance due to its unique geographical features, economic vibrancy, pastoral heritage, and fragile natural ecosystems. These ecosystems are becoming increasingly susceptible to human activities and the adverse impacts of climate change. This study analyzed the temporal and spatial variations of the Normalized Difference Vegetation Index (NDVI) in relation to key influencing factors in the SWR from 2001 to 2020. The analytical methods included Sen’s slope estimator, the Mann–Kendall trend test, and the Geographical Detector Model (GDM). The analysis revealed significant spatial variability in vegetation cover, with dense vegetation concentrated in the eastern part of the region and low vegetation coverage overall, reflected by an average NDVI value of 0.45, indicating persistent vegetation stress. Human activities, particularly land use and land cover (LULC) changes, were identified as major drivers of vegetation loss in some states such as Ekiti, Lagos, Ogun, and Ondo. Conversely, Osun and Oyo exhibited signs of vegetation recovery, suggesting the potential for restoration. The study found that topographic factors, including slope and elevation, as well as climatic variables like precipitation, influenced vegetation patterns. However, the impact of these factors was secondary to LULC dynamics. The interaction detection analysis further highlighted the cumulative effect of combined anthropogenic and environmental factors on vegetation distribution, with the interaction between LULC and topography being particularly significant. These findings provide essential insights into the biological condition of the SWR and contribute to advancing the understanding of vegetation patterns with critical implications for the sustainable management and conservation of tropical forest ecosystems. Full article

Diffuse agricultural pollution is a leading contributor to surface water degradation, particularly in regions undergoing rapid land use change and agricultural intensification. In many developing countries, conventional assessment approaches fall short of capturing the spatial complexity and cumulative nature of multiple environmental drivers that influence surface water vulnerability. This study addresses this gap by introducing the Integral Index of Vulnerability to Diffuse Contamination (IIVDC), a spatially explicit, multi-criteria framework that combines the Analytical Hierarchy Process (AHP) with Geographic Information Systems (GIS). The IIVDC integrates six key indicators—slope, soil erodibility, land use, runoff potential, hydrological connectivity, and observed water quality—weighted through expert elicitation and mapped at high spatial resolution. The methodology was applied to the Guachal River watershed in Valle del Cauca, Colombia, where agricultural pressures are pronounced. Results indicate that 33.0% of the watershed exhibits high vulnerability and 4.3% very high vulnerability, with critical zones aligned with steep slopes, limited vegetation cover, and strong hydrological connectivity to cultivated areas. By accounting for both biophysical attributes and pollutant transport pathways, the IIVDC offers a replicable tool for prioritizing land management interventions. Beyond its technical application, the IIVDC contributes to sustainability by enabling evidence-based decision-making for water resource protection and land use planning. It supports integrated, spatially targeted actions that can reduce long-term contamination risks, guide sustainable agricultural practices, and improve institutional capacity for watershed governance. The approach is particularly suited for contexts where data are limited but spatial planning is essential. Future refinement should consider dynamic water quality monitoring and validation across contrasting hydro-climatic regions to enhance transferability. Full article

Understanding the impact of drought on the water use efficiency (WUE) of grasslands is essential for comprehending the mechanisms of the carbon–water cycle in the context of global warming. Nevertheless, the cumulative and lagged effects of drought on WUE across different grassland types in China remain unclear. This study investigates the cumulative and lagged effects of drought on WUE across different grassland types in China from 1982 to 2018. We employed the Sen-MK trend test and correlation analysis to identify the primary factors influencing the temporal effects of drought on WUE. The results indicated that WUE in Chinese grasslands, across various grassland types, exhibited an upward trend over time, with the most rapid increase observed in meadow. Drought had both cumulative and lagged effects on WUE, with cumulative effects lasting an average of 5.2 months and lagged effects lasting 6.1 months. Specifically, the cumulative effects of drought on WUE lasted for 5.6 months for alpine and subalpine meadow, slope, and desert grassland, whereas the lagged effects lasted 9 months for alpine and subalpine plain grassland. Furthermore, the influence of drought on WUE in grasslands varied across different grassland types and intensified with increasing altitude. The trends observed in the cumulative and lagged impacts of drought on WUE across various aridity index (AI) zones were consistent with those for grasslands as a whole. Our findings underscore that the response of WUE to drought in grasslands and their distinct types is primarily characterized by lagged effects. This research provides an important reference value for enhancing the stability of grassland ecosystems. Full article

Recent breakthrough exploration wells in the Huagang Formation in the Y-area of the central anticlinal zone of the Xihu Sag have confirmed the significant exploration potential of structure–lithology complex hydrocarbon reservoirs. However, limited understanding of the provenance system, sedimentary facies, and microfacies has hindered further progress in complex hydrocarbon exploration. Analysis of high-precision stratigraphic sequences and seismic facies data, mudstone core color, grain-size probability cumulative curves, core facies, well logging facies, lithic type, the heavy-mineral ZTR index, and conglomerate combinations in drilling sands reveals characteristics of the source sink system and provenance direction. The Huagang Formation in the Y-area represents an overall continental fluvial delta sedimentary system that evolved from a braided river delta front deposit into a meandering river channel large-scale river deposit. The results indicate that the primary provenance of the Huagang Formation in the Y-area of the Xihu Sag is the long-axis provenance of the Hupi Reef bulge in the northeast, with supplementary input from the short-axis provenance of the western reef bulge. Geochemical analysis of wells F1, F3, and G in the study area suggests that the prevailing sedimentary environment during the period under investigation was characterized by anoxic conditions in nearshore shallow waters. This confirms previous research indicating strong tectonic reversal in the northeast and a small thickness of the central sand body unrelated to the flank slope provenance system. The aforementioned findings deviate from conventional understanding and will serve as a valuable point of reference for future breakthroughs in exploration. Full article

Laterite is the predominant zonal soil in China’s southernmost tropical rainforest and monsoon forest regions, where typhoons are the primary source of precipitation. These storms pose significant risks of land and soil degradation due to heavy rainfall. In recent years, a substantial area of sloping land has been converted to agricultural use in these regions, predominantly for the cultivation of crops grown in laterite soil. These activities contribute to soil erosion, exacerbate environmental challenges, and hinder the pursuit of sustainable development. There is a paucity of research reports on the processes and mechanisms of runoff and sediment on sugarcane-cropped slopes in regions with laterite soil under heavy rainfall conditions. In this study, four different heavy rainfall scenarios of 75, 100, 125, and 150 mm/h were designed to assess the impact on sugarcane growth at four key stages and to measure the resulting effects on initial runoff time, surface runoff, and sediment yield from laterite soil slopes under controlled laboratory conditions. The results showed that the Horton model explained much of the variation in infiltration rate on the sugarcane-cropped laterite slopes. The cumulative sediment yield on the sugarcane-cropped laterite slopes followed a second-degree polynomial function. The initial runoff time, infiltration intensity, runoff intensity, and sediment yield were all linearly related to the leaf area index (LAI) and rainfall intensity on the sugarcane-cropped slope surface. The leaf area index exerted a greater influence on the initial runoff time and infiltration intensity than rainfall intensity. However, rainfall intensity exerted a greater influence on the runoff intensity and sediment yield than the leaf area index. Compared with the bare sloping land, the average sediment yield was reduced by 12.2, 33.1, 58.2, and 64.9% with the sugarcane growth stages of seedling, tillering, elongation, and maturity, respectively. Full article

As an important drinking water source for Beijing, the capital of China, the water inflow of Miyun Reservoir has been decreasing year by year, which has affected the urban water supply security. To understand the variation trend of the inflow and analyze the main factors influencing the runoff change, this research focused on the watershed of Miyun Reservoir as the target. Based on the runoff data from 1984 to 2020 at the outlet of the basin, as well as the precipitation, potential evaporation intensity, NDVI (normalized difference vegetation index), population, and GDP (Gross Domestic Product) data, combined with correlation analysis methods, empirical statistical methods, the SCRCQ (Slope Change Ratio of Cumulative Quantity) method, and the GIS, the interannual variation characteristics of various elements in the basin were analyzed, the correlation between runoff and other factors was studied, and the influencing degrees of precipitation, water surface evaporation intensity, human activities, and other factors on the runoff change in the basin were quantitatively separated. The research results showed that the runoff exhibited a distinct decreasing trend, and there were two mutation points in the basin runoff from 1984 to 2020, which were 1995 and 2014, respectively. The runoff change was divided into three stages: 1984–1995 (upward trend in T1), 1995–2014 (downward trend in T2), and 2014–2020 (stable trend in T3). Runoff was significantly correlated with four indicators: the summer leaf area index of the Chaohe River and Baihe River, the regional GDP and population, among which the correlation of the summer leaf area index was the largest. Compared with the period T1, the contribution rates of climate change to the runoff reduction in T2 and T3 were 6.38% and 5.73%, and the contribution rates of human activities to the runoff reduction were 93.62% and 94.27%, respectively. Therefore, the change in annual runoff in the Miyun Reservoir watershed is mainly affected by human activities, and the contribution of climate change to the runoff attenuation is weak. This study is significant in the maintenance and enhancement of runoff in typical watershed. Full article

Constructing an ecological security pattern in ecologically fragile areas is crucial for maintaining regional ecological stability. This study focuses on the Kunlun Mountain region, identifying ecological sources based on habitat suitability assessments and ecosystem services. An ecological resistance evaluation index system is constructed, considering topography, land use, and habitat quality. The minimum cumulative resistance model is then applied to identify ecological corridors, with areas exhibiting higher ecological currents designated as ecological nodes. By integrating the spatial characteristics of ecosystem services, an ecological security pattern is established. The results are as follows: (1) The ecological source area covers approximately 11.30% of the study area. (2) The cumulative length of ecological corridors is 21,111 km, mainly distributed along valleys, gentle slopes, and oasis areas. (3) The areas of ecological nodes and ecological barriers are 126.75 km² and 46.75 km², respectively. Ecological nodes are mainly distributed on both sides of the Kunlun Mountains, while ecological barriers are primarily located in the central mountainous area of the Kunlun Mountains. (4) The findings recommend establishing an ecological security pattern consisting of “2 horizontal and 4 vertical corridors and 5 zones” to ensure the ecological security of the Kunlun Mountains. The integration of ecological corridors and ecosystem services in constructing a regional ecological security pattern provides valuable decision-making tools for protecting ecosystems and species in fragile areas. Full article

Global warming has increased the occurrence of extreme weather events, causing significant economic losses and casualties from rainfall-induced landslides. China, being highly prone to landslides, requires comprehensive predictions of future rainfall-induced landslide risks. By developing a landslide-prediction model integrated with the CMIP6 GCMs ensemble, we predict the spatiotemporal distribution of future rainfall-induced landslides in China, incorporating antecedent soil-wetness factors. In this study, antecedent soil wetness is represented by the antecedent effective rainfall index (ARI), which accounts for cumulative rainfall, evaporation, and runoff losses. Firstly, we calculated landslide susceptibility using seven geographic factors, such as slope and geology. Then, we constructed landslide threshold models with two antecedent soil-wetness indicators. Compared to the traditional recent cumulative rainfall thresholds, the landslide threshold model based on ARI demonstrated higher hit rates and lower false alarm rates. Ensemble predictions indicate that in the early 21st century, the risk of landslides decreases in the Qinghai–Tibet Plateau, Southwest, and Southeast regions but increases in other regions. Mid-century projections show a 10% to 40% increase in landslide risk across most regions. By the end of the century, the risk is expected to rise by more than 15% nationwide, displaying a spatial distribution pattern that intensifies from east to west. Full article

Precisely assessing the vulnerability of landslides is essential for effective risk assessment. The findings from such assessments will undoubtedly be in high demand, providing a solid scientific foundation for a range of critical initiatives aimed at disaster prevention and control. In the research, authors set the ancient core district of Sichuan Moxi Ancient Town as the research object; they conduct and give the final result of the geological survey. Fault influences are commonly utilized as key markers for delineating strata in the field of stratigraphy, and the slope distance, slope angle, slope aspect, elevation, terrain undulation, plane curvature, profile curvature, mean curvature, relative elevation, land use type, surface roughness, water influence, distance of the catchment, cumulative water volume, and the Normalized Vegetation Index (NDVI) are used along roads to calculate annual rainfall. With the purpose of the establishment of the evaluation system, there are 17 factors selected in total. Through the landslide-susceptibility assessment by the coupled models of DNN-I-SVM and DNN-I-LR nine factors had been selected; it was found that the Area Under the Curve (AUC) value of the Receiver Operating Characteristic Curve (ROC) was high, and the accuracy of the model is relatively high. The coupler, DNN-I-LR, gives 0.875 of an evaluation accuracy of AUC, higher than DNN-I-SVM, which yielded 0.860. It is necessary to note that, in this region, compared to the DNN-I-SVM model, the DNN-I-LR coupling model has better fitting and prediction abilities. Full article

Land Surface Temperature (LST) products obtained by thermal infrared (TIR) remote sensing contain considerable blank areas due to the frequent occurrence of cloud coverage. The studies on the all-time reconstruction of the cloud-covered LST of geostationary meteorological satellite LST products are relatively few. To accurately fill the blank area, a hybrid method for reconstructing hourly FY-4A AGRI LST under cloud-covered conditions was proposed using a random forest (RF) regression algorithm and Savitzky-Golay (S-G) filtering. The ERA5-Land surface cumulative net radiation flux (SNR) reanalysis data was first introduced to represent the change in surface energy arising from cloud coverage. The RF regression method was used to estimate the LST correlation model based on clear-sky LST and the corresponding predictor variables, including the normalized difference vegetation index (NDVI), the normalized difference water index (NDWI), surface elevation and slope. The fitted model was then applied to reconstruct the cloud-covered LST. The S–G filtering method was used to smooth the outliers of reconstructed LST in the temporal dimension. The accuracy evaluation was performed using the measured LST of the representative meteorological stations after scale correction. The coefficients of determination derived with the reference LST were all above 0.73 on the three examined days, with a bias of −1.13–0.39 K, mean absolute errors (MAE) of 1.46–2.4 K, and root mean square errors (RMSE) of 1.77–3.2 K. These results indicate that the proposed method has strong potential for accurately restoring the spatial and temporal continuity of LST and can provide a solution for the production and research of gap-free LST products with high temporal resolution. Full article

Forest roads provide access to remote wooded areas, serving as key transportation routes and contributing to human impact on the local environment. However, large animals, such as bears (Ursus sp.), moose (Alces alces), and caribou (Rangifer tarandus caribou), are affected by their presence. Many publicly available road layers are outdated or inaccurate, making the assessment of landscape objectives difficult. To address these gaps in road location data, we employ CubeSat Imagery from the Planet constellation to predict the occurrence of road probabilities using a SegNet Convolutional Neural Network. Our research examines the potential of a pre-trained neural network (VGG-16 trained on ImageNet) transferred to the remote sensing domain. The classification is refined through post-processing, which considers spatial misalignment and road width variability. On a withheld test subset, we achieve an overall accuracy of 99.1%, a precision of 76.1%, and a recall of 91.2% (F1-Score: 83.0%) after considering these effects. We investigate the performance with respect to canopy coverage using a spectral greenness index, topography (slope and aspect), and land cover metrics. Results found that predictions are best in flat areas, with low to medium canopy coverage, and in the forest (coniferous and deciduous) land cover classes. The results are vectorized into a drivable road network, allowing for vector-based routing and coverage analyses. Our approach digitized 14,359 km of roads in a 23,500 km² area in British Columbia, Canada. Compared to a governmental dataset, our method missed 10,869 km but detected an additional 5774 km of roads connected to the network. Finally, we use the detected road locations to investigate road age by accessing an archive of Landsat data, allowing spatiotemporal modelling of road access to remote areas. This provides important information on the development of the road network over time and the calculation of impacts, such as cumulative effects on wildlife. Full article

Climate change has intensified the risk of extreme precipitation, while mountainous areas are constrained by complex disaster mechanisms and difficulties in data acquisition, making it challenging for existing critical rainfall threshold accuracy to meet practical needs. Therefore, this study focuses on Yunnan Province as the research area. Based on historical flash flood events, and combining remote sensing data and measured data, 12 causative factors are selected from four aspects: terrain and landforms, land use, meteorology and hydrology, and population and economy. A combined qualitative and quantitative method is employed to analyze the relationship between flash floods and triggering factors, and to calibrate the parameters of the RTI (Rainfall Threshold Index) model. Meanwhile, machine learning is introduced to quantify the contribution of different causative factors and identify key causative factors of flash floods. Based on this, a parameter η coupling the causative mechanism is proposed to optimize the RTI method, and develop a framework for calculating county-level critical rainfall thresholds. The results show that: (1) Extreme rainfall, elevation, slope, and other factors are direct triggers of flash floods, and the high-risk areas for flash floods are mainly concentrated in the northeast and southeast of Yunnan Province. (2) The intraday rainfall has the highest correlation with the accumulated rainfall of the previous ten days; the critical cumulative rainfall ranges from 50 mm to 400 mm. (3) The county-level critical rainfall threshold for Yunnan Province is relatively accurate. These findings will provide theoretical references for improving flash flood early warning methods. Full article