Landslide risk assessment combining kernel extreme learning machine and information value modeling-A case study of Jiaxian Country of loess plateau, China.

Landslide risk mapping can be an effective reference for disaster mitigation and land use planning, but the modelling process involves multidisciplinary knowledge which leads to its complexity. In this study, Jiaxian County in Shaanxi Province on the Loess Plateau of China, served as the study area, primarily characterized by Quaternary loess-covered geomorphology, with an average rainfall of about 400 mm annually. Soil erosion and human engineering activities have contributed to significant slope failures, posing threats to local residents and infrastructure.

Beta diversity subcomponents of plant species turnover and nestedness reveal drivers of community assembly in a regenerating subtropical forest.

Secondary forests represent a significant proportion of global forest cover, with over 70% of forests in East Asia classified as regenerating. While succession has been studied extensively in temperate systems, trajectories of subtropical succession remain poorly characterized in highly disturbed, urban-adjacent forests. Investigating the additive beta diversity components of turnover and nestedness may reveal community assembly mechanisms driving secondary succession.

Analysis of spatial-temporal evolution and investment model of industrial cross-regional investment network-taking the Pearl River Delta urban agglomeration as an example.

Cross-regional investment behavior plays a pivotal role in enterprise development and regional economic growth. Nonetheless, existing investment network analyses often adopt a broad perspective, most studies tend to invest in network models and focus on a particular industry, and pay less attention to investment models in different industries. Therefore, this paper will combine the dual perspectives of space and network to observe the spatial and temporal evolution characteristics of enterprise investment and its investment model.

Rural human settlement environment, non-agricultural transfer of labour and arable land abandonment in China.

The arable land abandonment caused by the large-scale non-agricultural transfer of labour has attracted substantial attention from all walks of life in China. Promoting improvement in human settlement environment can accelerate the construction of infrastructure, ameliorate grassroots organization and enhance management capacities while simultaneously decelerating agricultural production costs. High level of human settlement environment can also attract the labour force to return, stimulate the vitality of rural elements and endogenous powers.

Spatiotemporal evolution and driving factors analysis of fractional vegetation coverage in the arid region of northwest China.

The arid region of northwest China (ARNC) is the most ecologically fragile region in China, and is characterized by harsh natural conditions, severe soil erosion, and poor soil fertility. Understanding long-term vegetation changes in this region is critical for effective environmental monitoring and climate change adaptation. Fractional vegetation coverage (FVC) is a key parameter for characterizing the ecological conditions of the ARNC.

Human-earth system dynamics in China's land use pattern transformation amidst climate fluctuations and human activities.

Amid rapid environmental changes, the interplay between climate change and human activity is reshaping land use, emphasizing the significance of human-earth system dynamics. This study, rooted in human-earth system theory, explores the complex relationships between land use patterns, climate change, and human activities across China from 1996 to 2022. Using a comprehensive analytical framework that combines Geographical Detector (GeoDetector), Random Forest (RF) model, Data Envelopment Analysis (DEA), Spearman's rank correlation, and k-means clustering, we analyzed data from national land surveys, climate records, and nighttime light observations.

DRA-UNet for Coal Mining Ground Surface Crack Delineation with UAV High-Resolution Images.

Coal mining in the Loess Plateau can very easily generate ground cracks, and these cracks can immediately result in ventilation trouble under the mine shaft, runoff disturbance, and vegetation destruction. Advanced UAV (Unmanned Aerial Vehicle) high-resolution mapping and DL (Deep Learning) are introduced as the key methods to quickly delineate coal mining ground surface cracks for disaster prevention. Firstly, the dataset named the Ground Cracks of Coal Mining Area Unmanned Aerial Vehicle (GCCMA-UAV) is built, with a ground resolution of 3 cm, which is suitable to make a 1:500 thematic map of the ground crack.

An Algorithm for Generating Outdoor Floor Plans and 3D Models of Rural Houses Based on Backpack LiDAR.

As the Rural Revitalization Strategy continues to progress, there is an increasing demand for the digitization of rural houses, roads, and roadside trees. Given the characteristics of rural areas, such as narrow roads, high building density, and low-rise buildings, the precise and automated generation of outdoor floor plans and 3D models for rural areas is the core research issue of this paper. The specific research content is as follows: Using the point cloud data of the outer walls of rural houses collected by backpack LiDAR as the data source, this paper proposes an algorithm for drawing outdoor floor plans based on the topological relationship of sliced and rasterized wall point clouds.

Determinants of spatiotemporal changes of land use carbon emissions for counties in Shaanxi Province, China.

In China, urban sprawl and developed land expansion challenge the country's "carbon peak" and "carbon neutrality" goals. Counties as the basic governance units are crucial for effective carbon reduction policies. This study examines land use carbon emissions (LUCE) in Shaanxi Province at the county level, essential for China's low-carbon strategy.

Uncovering the impact and mechanisms of air pollution on eye and ear health in China.

Increasing air pollution could undermine human health, but the causal link between air pollution and eye and ear health has not been well-studied. Based on four-week-level records of eye and ear health over 1991-2015 provided by the China Health and Nutrition Survey, we estimate the causal effect of air pollution on eye and ear health. Using two-stage least squares estimation, we find that eye or ear disease possibility rises 1.

Spatiotemporal evolution of land use efficiency in 357 cities across mainland China from 2000 to 2020 based on SDG 11.3.1.

High-efficiency land use facilitates the maximization of land utilization, lowers urban construction costs, and optimizes urban functional patterns. The Sustainable Development Goal 11.3.

The effect of air pollution on defensive expenditures: Evidence from individual commercial health insurance in China.

To mitigate the substantial losses incurred by air pollution, individuals undertake defensive behaviors in the form of health insurance expenses. Leveraging data from the 2011-2017 China Household Finance Survey (CHFS) encompassing 3033 residents, we estimate the causal impact of air pollution on defensive expenditures. Our findings are as follows: (1) Air pollution exhibits a significantly favorable effect on individual commercial health insurance expenses, with a 1% increase in PM concentration correlating to an 11.

Distribution, sources, and contamination evaluation of heavy metals in surface sediments of the Qizhou Island sea area in Hainan, China.

Coastal areas are regions of active interaction between the sea and land and are highly sensitive to changes in heavy metal contamination caused by natural and anthropogenic activities. The contents of heavy metals in 80 surface sediments in the Qizhou Island sea area in the northeast of Hainan Island were determined to assess the contamination status, spatial distribution, sources, and ecological risks. The results indicate that the main factors influencing the distribution patterns and contents of heavy metals are hydrodynamic conditions and sources of materials.

Consumer preference and willingness-to-pay for formal recycling of electric vehicle batteries: A discrete choice experiment in China.

The burgeoning electric vehicle (EV) market poses a substantial challenge to battery recycling systems, yet understanding EV battery recycling behavior from the demand side remains limited. Previous studies have analyzed perceptual or attitudinal factors, neglecting the observable attributes of EV battery recycling. To this end, we proposed a discrete choice model to investigate the differences between formal and informal recycling behaviors, identifying consumer preferences and willingness to pay.

Combining Google traffic map with deep learning model to predict street-level traffic-related air pollutants in a complex urban environment.

Background: Traffic-related air pollution (TRAP) is a major contributor to urban pollution and varies sharply at the street level, posing a challenge for air quality modeling. Traditional land use regression models combined with data from fixed monitoring stations may be unable to predict and characterize fine-scale TRAP, especially in complex urban environments influenced by various features. This study aims to estimate fine-scale (50 m) concentrations of nitrogen oxides (NO and NO₂) in Hong Kong using a deep learning (DL) structured model.

Refining soil nutrient assessment: Incorporating land use boundaries for precision agriculture.

Soil nutrient levels play a crucial role in determining crop yield. A comprehensive understanding of the spatial distribution patterns and evaluation grades of soil nutrients is of significant practical importance for informed fertilization practices, enhancing crop production, and optimizing agricultural land utilization. This study focuses on the urban area of Kashi Prefecture in Xinjiang as a case study.

The impact of rural collective property rights reform on income and poverty reduction: Evidence from China's rural regions.

The reform of rural collective property rights is pivotal in advancing agricultural modernization and comprehensive rural revitalization. This study aims to explore the impact of this reform on income growth and poverty reduction in rural areas, as well as its underlying mechanisms. Utilizing data from the China Rural Revitalization Survey (CRRS), the propensity score matching (PSM) method was employed to empirically analyze the effects of rural collective property rights reform on income growth and poverty reduction.

Responses of ecosystem service trade-offs and synergies in Guangfo Metropolitan Area to multidimensional expansion of urban space.

Understanding the responses of ecosystem service trade-offs and synergies in metropolitan areas to the multidimensional expansion of urban space is of great significance for the optimization of regional land spatial pattern and high-quality development. With the Guangfo Metropolitan Area as research region, we used land use data and natural ecological environment data from 2000 to 2020 to measure the expansion characteristics of urban space in the dimensions of scale, distribution, and morphology by using the landscape pattern indices. We further calculated four main ecosystem services: urban cooling, habitat quality, recreation, and water conservation by the InVEST model, quantified the trade-off and synergistic relationship of multiple ecosystem services by the coupling coordination degree model, and explored its response to multidimensional urban spatial expansion by using the multi-scale geographically weighted regression model.

Construction of ecological security pattern in Loess Plateau counties by integrating structural connectivity and functional enhancement: A case study of Ansai District, Yan'an City, Northwest China.

Ecological security pattern is an important spatial way to maintain ecological processes and ensure the stability of ecosystem functions. As the implementation of landscape planning and decision-making, it is critically needed to consider the consistency of differentiated methods and their spatial outputs in the construction of ecological security patterns and the matching and applicability of research objects. From the perspective of integration, we combined the regional topography and landscape characteristics, integrated the morphological spatial pattern analysis and the importance evaluation results of ecosystem services to identify the ecological source, and constructed the ecological security pattern of the Ansai District of Yan'an City, the main implementation area of the Grain-for-Green Project on the Loess Plateau.

Vegetation changes and influencing factors in different watersheds of Henan Province based on GEE and geographic detectors.

Clarifying vegetation changes and the driving factors can provide references for ecological restoration and sustainable social development. We analyzed vegetation distribution and trend changes in Henan Province and its basin zoning (Haihe River basin zoning, Yellow River basin zoning, Huaihe River basin zoning, Yangtze River basin zoning), with fractional vegetation cover data from 2000 to 2020 based on the Google Earth Engine platform, and by combining Theil-Sen Median trend analysis, Mann-Kendall test, and Hurst index. We also utilized factor detection and factor interaction to explore the individual and mutual influences of natural and anthropogenic factors on vegetation at different scales.