Search Results (4,167)

Economic well-being is essential for assessing sustainability of human settlement in urbanizing regions; however, the geographic factors linking settlement characteristics to residents’ well-being remain underexplored, particularly in counties in China undergoing urban–rural transformation. In this study, six representative Chinese counties (Yanshou, Wafangdian, Bazhou, Yugan, Yongsheng, and Raoping) with varying urbanization levels are investigated to establish a multidimensional evaluation framework and reveal the geographic factors underlying economic well-being. Through original household surveys conducted across these six geographically and economically diverse counties, we collected primary data from 1659 households; these data provide unique insights into residents’ lived experiences. By integrating these original survey data with objective indicators from statistical yearbooks and geographic features from multisource spatial data, key drivers were identified using Pearson correlation and random forest models. The results show the following trends: (1) significant county-level variation in subjective well-being, with Wafangdian ranking the highest and Bazhou ranking the lowest, while well-being aligned more closely with economic development levels; (2) income and happiness were the dominant determinants of subjective well-being, with work-related factors also contributing substantially, whereas nighttime light intensity, building density, and construction land area drove fusion well-being; and (3) multifactor modeling demonstrated strong explanatory power for fusion well-being (training set R² = 0.8313; validation set R² = 0.7531), indicating generalizability. The primary data collection across varied settlement settings provides strong empirical grounding. The findings reveal the spatial differentiation of economic well-being in urbanizing settlements, offering empirical support for targeted settlement planning and urban governance policies to improve sustainability and residents’ well-being in developing countries. Full article

Using accurate land cover data is essential to monitor land use and cover changes and assess the effectiveness of various environmental policies. This study evaluates the accuracy of contemporary global land cover products with 10 m spatial resolution, including Google’s Dynamic World (GDW), European Space Agency’s World Cover (ESA WC) and Esri Land Cover (ELC) in mapping forested areas in Poland, aiming to test an assumption if the combination of these products may improve forest mapping accuracy compared to any individual product. Three global datasets and their combinations were assessed with the 2022 EU Land Use/Cover Area Frame Survey (LUCAS). A land cover map of Poland (S2GLC PL) for 2021 served as an auxiliary reference data set. Forest cover classification accuracy was evaluated using precision, recall, and F1-score metrics, and spatial agreement of binary forest maps in the thematic global products was measured with the Intersection over Union (IoU) at two various scale levels (country and province). Our results showed that forest mapping accuracy of three global products varies for Poland, with F1-score equal to 72.2% for ELC, 76.9% for ESA WC, and 68.8% for GDW. IoU against S2GLC PL was equal to 82.6%, 82.3% and 75.2%, for ELC, ESA WC and GDW, respectively, and slightly exceeded 70.5% for three global products. A specific combination of binary forest maps from global products, where the output forest area consisted of forests mapped at the same time by all three products and forests mapped at the same time only by GDW and ESA WC yielded better accuracy indicators than any single product and other tested combinations (F1-score equal to 80.4%, and IoU against S2GLC PL equal to 87.1%). Full article

Extreme meteorological and climate events, such as floods and prolonged droughts, cause socio-environmental disasters in several regions of the world, including the Amazon. The Amazon Delta-Estuary, which is shaped by coastal and river environments, has constantly changing land use patterns, making it vulnerable to such events. This study aimed to evaluate rainfall regimes and flood scenarios in the tributaries of the Amazon Delta-Estuary, known as the Ottocoded River sub-basins, which are located in the municipalities of Abaetetuba and Barcarena in the Brazilian state of Pará. The Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) dataset was used to analyze rainfall dynamics. The Height Above the Nearest Drainage (HAND) model was employed for flood modeling. The geomorphological, altimetric, bathymetric, and hydrodynamic components of the water bodies were also analyzed. Flood susceptibility was zoned as follows: Very High, High, Medium, Low and Very Low. Of the surveyed buildings, 28.8% were classified as ‘Very High’, 29.1% as ‘High’, 20.2% as ‘Medium’, 13.4% as ‘Low’, and 8.5% as ‘Very Low’. Many of these buildings are located in flood-prone areas, posing a significant risk of socio-environmental disasters. This research could inform public policies aimed at managing the risks associated with environmental disasters and extreme events. Full article

Soil salinization represents one of the most severe abiotic constraints on global forest productivity. Populus, the most widely cultivated fast-growing timber tree and a premier model woody plant, exhibits striking intrageneric variation in salt tolerance—from the extremely halophytic Populus euphratica to highly salt-sensitive cultivated clones. Understanding the molecular basis of this variation has profound implications for saline–alkali land reclamation and salt-tolerant variety breeding. This review systematically synthesizes current knowledge on Populus salt-stress responses, covering three primary injury mechanisms (osmotic stress, ionic toxicity, and oxidative damage) and the corresponding physiological countermeasures. We further survey functional genes across four major categories: ion transporters, osmotic-adjustment enzymes, antioxidant-defense components, and transcription factors. Crucially, we extend beyond the herbaceous-plant paradigm by examining salt-tolerance strategies that are specific to the woody architecture of Populus: long-distance radial and axial Na⁺ transport through tall stems, salt sequestration in senescent bark and wood parenchyma, and deep-root ion exclusion strategies. Comparative insights from other woody genera are incorporated to highlight convergent and divergent mechanisms. On this basis, we propose an integrated multi-level regulatory model in which Na⁺ compartmentalization/efflux serves as the core, ROS homeostasis as the key regulatory axis, and osmotic adjustment as the auxiliary strategy. Outstanding challenges—including unresolved primary salt-signal perception, insufficient pathway integration, and limited in planta gene-function verification—are critically assessed, and future research priorities encompassing multi-omics integration, CRISPR-based gene editing, and natural-population genomics are outlined. Full article

This study examines access to Indonesia’s subsidised credit programme, Kredit Usaha Rakyat (KUR), during the COVID-19 pandemic using signalling theory. Based on logit regression of survey data from 2361 micro and small enterprises (MSEs), the study analyses how borrower characteristics were associated with loan approval across the Super Micro, Micro, and Small KUR schemes. The results show that prior credit history was the strongest observed signal of creditworthiness during the crisis. Previous receipt of KUR was associated with a 5 percentage-point higher probability of loan approval. Scheme-level estimations indicate heterogeneous signalling mechanisms. Prior credit history was positively associated with access to Micro KUR (15 p.p) and negatively associated with access to KUR Super Mikro that targeted non-bankable SMEs, whereas access to Small KUR was more strongly associated with collateral-based signals, particularly land ownership. The findings further indicate that borrowers lacking prior credit experience or formal assets were less likely to obtain KUR during the pandemic, suggesting that crisis-period lending created a “signaling trap” that stabilised liquidity while perpetuating exclusion. The study recommends reforms to KUR that incorporate hybrid risk assessment mechanisms, capacity-building, decentralised guarantees, and pathways to formalisation. Full article

Superpoint Transformers use superpoints as the basic processing units, thereby significantly reducing the number of tokens processed by Transformers. However, they have been seldom employed in point cloud roof plane instance segmentation, and existing superpoint Transformers suffer from limited performance due to the use of low-quality superpoints. To address this challenge, we establish a set of criteria that high-quality superpoints for Transformers should satisfy and introduce a corresponding two-stage superpoint generation process. The superpoints generated by our method not only have accurate boundaries, but also exhibit consistent geometric sizes and shapes, which greatly benefit the feature learning of superpoint Transformers. To compensate for the limitations of deep learning features when the training set size is limited, we incorporate multidimensional handcrafted features into the model. Additionally, we design a decoder that combines a Kolmogorov–Arnold Network with a Transformer module to improve instance prediction and mask extraction. Finally, our network’s predictions are refined using traditional algorithm-based post-processing. For evaluation, we annotated a real-world dataset and corrected annotation errors in the existing RoofN3D dataset. Experimental results show that our method achieves state-of-the-art performance on our dataset, as well as both the original and corrected RoofN3D datasets. Our model also shows significant advantages over existing methods when handling data with low point density, large density variations, or low 3D point precision. Moreover, it is not sensitive to plane boundary annotations during training, significantly reducing the annotation burden. We will release our code, trained models, and datasets. Full article

Understanding the driving mechanisms of land-use structure change is fundamental for exploring co-evolutionary dynamics of coupled human-land systems. This study focuses on traditional villages in Enshi Tujia and Miao Autonomous Prefecture, integrating spatial analysis, landscape pattern indices, and structural equation modeling (SEM) with field surveys and multi-source data. It analyzes spatial distribution, spatiotemporal evolution, and the direct and indirect pathways of topographic heterogeneity, human activities, economic development, and social level on land-use structure change. Results show: (1) Villages concentrate in mountainous junctions at 800–1200 m (52.2%), forming a multi-core, west-dense east-sparse pattern with significant spatial dependence. (2) During 1990–2020, Dong villages exhibited a development-oriented evolution, with slightly expanded cultivated and forest land, intensified fragmentation (patch density increased by up to 8.55%), increased landscape diversity, and slightly decreased grassland and water, reflecting an adaptive balance between economic development and ecological constraints. (3) SEM reveals that topographic heterogeneity exerts significant negative direct effects on human activities (−0.694) and economic development (−0.686), and indirectly constrains social level through multiple mediating pathways; human activities (0.829) and economic development (0.837) strongly drive social level, with economic development also synergistically promoting human activities. This study reveals cascading transmission mechanisms of land-use structure change, providing an empirically grounded theoretical foundation and decision-making reference for ecological protection, cultural inheritance, and sustainable development in mountainous ethnic areas. Full article

Household livelihood resilience is an important foundation for sustainable rural development, particularly in rural areas exposed to climate risks, market fluctuations, and demographic pressures. This study examines whether participation in new rural collective economic organizations (NRCEOs) is associated with household livelihood resilience and explores the mechanisms and contextual heterogeneity underlying this association. Using survey data from 837 rural households in Jiangxi Province, China, we construct a multidimensional livelihood resilience index and apply ordinary least squares, propensity score matching, and lasso Regression, together with an exploratory IV-2SLS sensitivity analysis. The results show that participation in NRCEOs is positively associated with household livelihood resilience, and this relationship remains stable across alternative estimation strategies. Mechanism analysis provides evidence consistent with two pathways: land, labor, and capital allocation support the resource-allocation pathway, while production efficiency and agricultural income support the agricultural production pathway; the sales channel estimate remains inconclusive because online sales are rare in the sample and statistical power is limited. Overall, the findings indicate that the relationship between collective economic participation and household livelihood resilience varies across mechanism dimensions and local development contexts. Full article

The Kedougou region (Senegal) is facing a resurgence of major climatic hazards (droughts, floods, forest fires, and extreme heat) that threaten its population, ecosystems, and sustainable development. This study proposes an integrated method for multi-risk assessment and mapping, combining large-scale analysis of satellite data (Landsat, MODIS, and SRTM) via Google Earth Engine (GEE) with a hierarchical multi-criteria approach (AHP). The method is supported by participatory surveys conducted with key local institutions to reflect local priorities and territorial expertise. Hazards were mapped over three periods (1995–2004, 2005–2014, and 2015–2024) using specific spectral indices: NBR for forest fires, VHI for drought, MNDWI for floods, and LST for extreme heat. Vulnerability is quantified using socio-economic (population density, cultivated areas), environmental (forests), and physical (urbanisation, topography) indicators. Individual risks, calculated as the product of normalised recurrent hazards and normalised vulnerability, were aggregated into a weighted multi-hazard map validated by a Consistency Ratio (CR) of 0.08. The results reveal that 2908.2 km² (17.2% of the Kedougou region) are exposed to multi-hazard risk, affecting approximately 33,889 people (13.5% of the population of Kedougou) and 18.9 km² of agricultural land. High-risk zones cover 76.1 km² and are concentrated in the Saraya department, where mining and population growth exacerbate exposure. Forest fires and floods are identified as the most critical risks. Publication on the MapX platform provides a proactive decision support tool aligned with SDGs 2, 11, 13, and 15. This methodology is adaptable to other semi-arid Sahelian regions facing similar challenges. Full article

Against the backdrop of the growing alignment between green agricultural transformation and rural land system reform, how stable land tenure promotes farmers’ adoption of green production technologies has become an important issue in achieving high-quality agricultural development. Using 2024 survey data from 1117 farm households in Inner Mongolia under China’s second-round land contract extension policy, this study applies Poisson regression and mediation models to examine how land tenure stability affects farmers’ adoption of green production technologies. The results show that legal, factual, and perceived tenure stability, measured by second-round contract extension signing, no land disputes since the second round, and expectations of no future land adjustment, all significantly promote adoption. Tenure stability promotes adoption through higher income, better credit access, stronger benefit expectations, and greater risk-coping capacity, reflecting both economic and psychological effects. Its positive effect is stronger among small-scale farmers and those with lower-quality cultivated land. Policy efforts should not only prudently advance the second-round land contract extension, but also strengthen tenure security in practice and coordinate support for green production, rural finance, and risk protection. From a multidimensional land tenure stability perspective, this study provides new empirical evidence on how rural land reform translates into green behavioral responses. Full article

The Oriental Magpie Pica serica invaded Hokkaido, Japan, in the 1980s, but little is known about its current population status or potential for further range expansion. Here, we compile records on the distribution of magpies from 2012 to 2016 and estimate potential suitable habitats. Field surveys and citizen science reports revealed that breeding and individual birds occurred in 28 municipalities located in western Hokkaido. Although dozens or more birds have become established in three of these municipalities on the Pacific coast, populations in the other 25 appear not self-sustaining. Suitable habitats for magpies were almost exclusively limited to urban residential areas, presumably due to the availability of anthropogenic food resources. While these apparently suitable habitats occur throughout Hokkaido Island, no sightings have been recorded in eastern Hokkaido, suggesting that magpies have not crossed the forest area that runs north–south through the central part of the island. Suitable habitats, estimated based on the habitat selection by the largest population in Tomakomai, are concentrated near the centers of each municipality, separated by agricultural land, which may have slowed down the range expansion of the magpie through the Allee effect. The island-like fragmentation of suitable habitats is advantageous for comparative studies of magpie populations, food resources, predators, and competitors. Furthermore, the magpie has a distinctive black-and-white coloration and a unique, loud call, making it well-suited for citizen science surveys. Continuous monitoring of Hokkaido’s magpie population by experts and citizens will provide excellent opportunities to ask ecological questions involving bird distributions and the establishment of invasive species. Full article

Collective operating construction land marketization (COCLM) is a major institutional innovation in China’s land reform process. However, the impact of this reform on farmers’ livelihood resilience (FLR) remains underexplored. This study uses data from the 2020–2022 China Land Economic Survey (CLES) conducted in Jiangsu Province to construct an FLR index from three dimensions—buffer capacity, self-organization capacity, and learning capacity. It also incorporates the actual status of COCLM at the village level to examine the impact of COCLM on FLR and its underlying mechanisms. The results show the following: (1) COCLM significantly improves FLR, and this conclusion remains consistent after a series of robustness checks. (2) In terms of FLR dimensions, COCLM has significant positive effects on all three dimensions, but its effects on buffer capacity and learning capacity are more pronounced than those on self-organization capacity. (3) Mechanism analysis reveals that COCLM improves FLR mainly by increasing farmers’ property income and promoting household non-agricultural employment. (4) Heterogeneity analysis shows that the positive effect of COCLM is more pronounced in southern and central Jiangsu, among high-income households, and in villages with higher governance levels. This study suggests that COCLM reform should be further deepened to steadily promote the sustained improvement of FLR, enable land value-added returns and non-agricultural employment opportunities to reach farmers more effectively, and pay greater attention to regional differences, income-group disparities, and differences in grassroots governance capacity, while promoting inclusive growth through COCLM. The above conclusions have some reference value for regions similar to Jiangsu, while their applicability in other regions with substantially different development conditions still requires further examination. Full article

The increasing frequency of floods and the severity of their consequences for public safety, infrastructure, and the economy demand improved methods for flood hazard identification. Flood studies that include flood hazard mapping are critical tools for informing emergency response and flood recovery, as well as for land use and mitigation planning. The methodology for such flood studies has evolved, and access to more powerful computational resources and high-resolution base data has contributed to the increased use of two-dimensional hydraulic modelling, where one-dimensional modelling previously was the default. However, local-scale flood studies face real-world constraints, including sparse data, challenging hydrologic conditions, and budget limitations, which can hinder the application of advanced techniques. This study addresses these challenges through innovative, practice-driven solutions in two case studies in Alberta, Canada: a small, partly channelized prairie stream network (Wolf Creek, Lacombe) and a laterally dynamic river on a distributary delta (Swan River, Kinuso). Three core components of flood hazard studies are described: field survey data collection, regional hydrology assessment, and hydraulic modelling. Key findings include demonstrating that LiDAR-derived terrain models alone cannot capture channel conveyance, the importance of low-flow calibration in the absence of high-water marks, the selection of a modelling methodology based on bathymetric and topographic features within a study area, and the development of inflow hydrographs for unsteady-state simulation in flat floodplains. Full article

Rapid urbanization, uncoordinated land-use growth, and insufficient integration of public transport have led to severe traffic congestion and declining mobility in Peshawar, Pakistan, even after the implementation of a Bus Rapid Transit (BRT) system. The core research problem addressed in this study is the mismatch between growing travel demand and the limited capacity, coverage, and operational efficiency of the existing urban transport network. This research aims to evaluate the current performance of Peshawar’s transport system and to identify integrated, evidence-based strategies to alleviate congestion and enhance urban mobility. Specifically, the objectives are to assess roadway level of service on major corridors, examine public transport user satisfaction with the BRT system, and propose targeted infrastructure and operational improvements. A mixed-methods approach was employed, combining traffic volume and level-of-service (LOS) analysis, public transport user surveys, and field observations at critical intersections. The findings indicate that several key arterial roads operate at LOS E–F during peak hours, and future traffic projections indicate widespread capacity failures under existing road geometries. Survey results reveal significant dissatisfaction with the BRT system, particularly due to limited spatial coverage, inadequate feeder routes, overcrowding, and excessive travel times. Based on these results, the study proposes integrated interventions, including road widening and auxiliary lanes, geometric and signalized junction improvements, expansion of BRT feeder services, development of new arterial and ring roads, and enhanced pedestrian and parking infrastructure. This study links quantitative traffic performance measures with user-perceived service deficiencies. It provides practical, data-driven guidance for policymakers and planners to support a more efficient, accessible, and sustainable urban transport system in Peshawar. Full article

Overexploitation of groundwater resources poses a critical challenge in major agricultural regions worldwide, yet how confined and unconfined aquifers respond differentially to governance interventions remains poorly understood. This study presents a comparative assessment of hydrochemical evolution and nitrate contamination dynamics in the Weishan Irrigation District, Shandong Province, China, contrasting pre-governance conditions (2011) with post-governance status (2022–2023) following comprehensive overexploitation control. By integrating hydrochemical characterization with stable isotope tracers (δ¹⁸O, δD, δ¹⁵N-NO₃⁻, δ¹⁸O-NO₃⁻) and Bayesian mixing models (MixSIAR), we reveal fundamentally contrasting aquifer responses to regulation. The unconfined aquifer exhibited continued degradation under persistent agricultural influence, characterized by elevated sodium, nitrate, and bicarbonate concentrations. In sharp contrast, the confined aquifer demonstrated substantial recovery, with major ion concentrations declining markedly, hydrochemical facies restored toward a pristine state, and overall water quality improving significantly to achieve full compliance with the highest-quality standards by 2023. These divergent trajectories indicate that regulatory interventions effectively restored aquitard barrier integrity, thereby shielding the confined aquifer from surface contamination, whereas the unconfined aquifer remained vulnerable to agricultural pollution. Isotope-constrained Bayesian modeling identified soil organic nitrogen, chemical fertilizers, manure/sewage, and industrial wastewater as dominant nitrate sources, with isotopic evidence confirming that the unconfined aquifer receives mixed recharge from Yellow River water and precipitation under contemporary contamination, while the confined aquifer maintains independent, pollution-free recharge. These findings demonstrate that overexploitation control can effectively rehabilitate confined aquifer systems by reestablishing natural hydrogeological barriers, but unconfined aquifers require targeted agricultural pollution mitigation. The contrasting responses highlight the necessity of aquifer-specific management strategies in irrigation-dependent regions, advancing theoretical understanding of how regulatory measures differentially affect multi-layered groundwater systems and providing a scientific basis for precision groundwater governance. Full article