AimPlants allocate sodium (Na) to leaves and roots as an adaptation to salinity and drought, potentially modulating herbivory and ecosystem carbon cycling. However, large‐scale spatial patterns and environmental drivers of plant Na allocation remain unclear.LocationChina and the world.Time PeriodField data were collected between 2013 and 2019. Literature data were collected between 1970 and 2024.Major

Rapid urbanization and global climate change are intensifying the Urban Heat Island (UHI) effect in cities worldwide, with consequences for human health and well-being. Urban green spaces (UGSs) mitigate extreme temperatures, but their cooling potential depends on spatial configuration, size, shape, and distribution. This study fills a geographic gap by providing one of the first detailed analyses

China, despite being a leading producer of potatoes, has a potato yield below the global average, primarily due to inefficient nutrient management practices. Remote sensing provides a non-invasive and large-scale approach to monitor crop nutrient status, offering an efficient alternative to traditional plant tissue analysis. However, the generalization of foliar nutrient models is often constrained

The integration of Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) data with Optical Photogrammetric Satellite Stereo Imagery (OPSSI) for Block Adjustment (BA) has emerged as a novel approach for generating large-area, high-accuracy Digital Elevation Models (DEMs). However, owing to the discrepancies between these two data platforms and the systematic errors of their sensors, errors arise in

Satellite video, as an emerging data source for Earth observation, enables dynamic monitoring and has wide-ranging applications in diverse fields. Nevertheless, cloud occlusion hinders the ability of satellite video to provide uninterrupted monitoring of the Earth’s surface. To mitigate the interference of clouds, cloud-free areas need to be selected before application, or an optimized solution like

A common problem in healthcare logistics is maximizing coverage of a scarce resource through optimal facility location. There are important equity considerations when some areas cannot access potentially life-saving medical services. For emergency healthcare which is time-sensitive, it is necessary to consider both the quality and extent of the coverage. Most past research in this area focused on maximizing

Scientific workflow management systems (WfMS) provide a systematic way to streamline necessary processes in scientific research. The demand for FAIR (Findable, Accessible, Interoperable, and Reusable) workflows is increasing in the scientific community, particularly in GIScience, where data is not just an output but an integral part of iterative advanced processes. Traditional WfMS often lack the capability

High-resolution (≤10 m) digital elevation models (DEMs) are essential for obtaining accurate terrain information and are integral to geographic analysis. However, a majority of currently available DEMs datasets possess a relatively coarse spatial resolution (≥30 m), which limits the terrain features and details that can be accurately represented. Furthermore, due to the substantial production costs

Accurate measurement of high-resolution snow depth (SD) is crucial for regional ecohydrology and climate studies. Passive microwave remote sensing is an effective technique for SD retrieval on global or regional scales. However, its low spatial resolution limits its application in various fields. Additionally, the complex effects of multiple factors in the microwave radiation process pose a significant

Tidal flats and their associated sandbanks are dynamic environments crucial for ecological balance and biodiversity. Monitoring their evolutionary history and topographic changes is important to better understand their dynamic mechanisms and predict their future status. Accurately mapping their evolution, however, remains challenging due to highly dynamic currents, suspended sediment variability, and

In central city areas, the use of different transport modes is common and levels of people activity tend to be high. However, existing measures of street space use mainly focus on vehicle flow, with little consideration given to measuring ‘people’. Based on surveys undertaken within the central city of Melbourne, this research developed six measures of street space use, building upon established measures

The x-minute city concept emphasizes the importance of residents being able to access locations of urban functions by active transportation modes within a short travel time. However, there are inevitably areas where active transportation modes like walking are insufficient to reach certain locations. In such cases, public transit plays a vital role in providing sustainable and healthy transportation

This study employs an integrated approach, combining remote sensing and numerical modelling techniques, to characterize flood-prone regions resulting from the combined effects of extreme river water elevations and long-term sea-level rise in the Senegal River Estuary. Four different case scenarios of hydrodynamic conditions have been investigated to provide a quantitative assessment of flooding. Simultaneously

Accurate assessment of fuel conditions is a prerequisite for fire ignition and behavior prediction, and risk management. The method proposed herein leverages diverse data sources – including L8 optical imagery, S1 (C-band) Synthetic Aperture Radar (SAR) imagery, PL (L-band) SAR imagery, and terrain features – to capture comprehensive information about fuel types and distributions. An ensemble model

AimUnderstanding the processes that structure biodiversity on Earth is a major challenge in biology. Our work tests three key hypotheses driving taxonomic changes in bird communities globally, focusing on nestedness and turnover components: (1) contemporary climate, related to energy and water availability; (2) climate stability, reflecting shifts since the last glacial maximum; and (3) climatic heterogeneity

The construction of the Qinghai-Tibet railway (QTR) parallel to the Qinghai-Tibet highway (QTH) has been associated with concerns about its impact on local wildlife. However, to date, most related research has been conducted after the QTR was built, and there is a lack of evidence of the effect of its construction on wildlife. By comparing ungulate survey data along the QTH between 2001 and 2020, an

The spatially continuous dynamic monitoring of near-surface NO2 concentrations on sub-daily scales would serve to enhance awareness of the current state of air pollution, which is crucial to improving regional air quality. Satellites, like OMI and TROPOMI, are capable of observing atmospheric NO2 column concentrations on a global scale. However, the fixed transit times of the satellites and severe

AimBeta diversity quantifies the similarity of ecological assemblages. Its increase, known as biotic homogenisation, can be a consequence of biological invasions. However, species occurrence (presence/absence) and abundance‐based analyses can produce contradictory assessments of the magnitude and direction of changes in beta diversity. Previous work indicates these contradictions should be less frequent

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Lanuza, J.B., T.M. Knight, N. Montes-Perez, et al. 2025. “ EuPPollNet: A European Database of Plant-Pollinator Networks.” Global Ecology and Biogeography 34: e70000. https://doi.org/10.1111/geb.70000 In the originally published article, funding information for some authors was missing. The missing information is included below. JBL was funded by the Federal State of Saxony-Anhalt (MLU-BioDivFund).

AimTropical niche conservatism (TNC) and dispersal limitation (DL) are major ecological and evolutionary mechanisms in shaping taxonomic and phylogenetic β‐diversities. While these mechanisms have been studied in plants and vertebrates, their roles in freshwater taxa remain unclear. We leveraged Odonata species distribution and phylogenetic data to map geographical patterns of taxonomic and phylogenetic

AimPre‐degradation baseline conditions (references) provide crucial context for restoration actions. Here, we compare vegetation structure and its driving processes across the main pre‐agricultural references discussed for temperate Europe: the Last Interglacial and the early‐mid Holocene—before and after the arrival of Homo sapiens, respectively.LocationTemperate Europe.Time PeriodThe first ~4000–6000

Estimating deformation at the upstream dam slope from Interferometric Synthetic Aperture Radar (InSAR) is challenging due to the complete loss of coherence in seasonally inundated upstream slope. Here, we present an improved Distributed Scatterer-InSAR method that accounts for the seasonal decorrelation of upstream dam slopes and optimizes the interferogram pair selection with inter- and multi-annual

Monitoring and governing the development of cities are the major concerns of urban planners, since involve physical and social aspects, such as land use and population trends. Models for spatial growth have been developed both from the mathematical and empirical viewpoints, with the aim of forecasting and decision-making. Statistical models require regular space–time datasets that are provided by recent

Gender differences affect the urban mobility patterns and travel behaviour of users. This research investigated the impediments faced by women in the public transportation system of Lahore, Pakistan. The study explores mobility using a mixed method of interviews with transport officials, visual analysis of bus stops and a questionnaire survey. A total of 624 women aged 15–29 were inquired about the

This article investigates the relationship between child sex abuse scandals and migration aspirations. We consider individual survey data from Argentina, Brazil, Chile, and Mexico over the period 2010–15, and we exploit the region of residence and the date of the interview of respondents to estimate the effect of region-specific time-varying pedophilia scandals in the Catholic Church on migration aspirations

Land surface temperature (LST) is an indispensable factor for comprehending of surface equilibrium state on the Earth. In particular, satellites can continuously provide LST data and support the large-scale monitoring of LST with a high temporal resolution; however, satellite data may be easily contaminated by clouds. Previous satellite-based all-sky LST reconstruction approaches have inherent limitations

Information regarding the spatial arrangement and extent of past habitats is important for understanding present biodiversity, restoration potential, and fighting extinction-debt effects. European landscapes have changed profoundly over recent decades, with the trend accelerating following World War 2. We develop a proof of concept for mapping historic habitat distribution for Switzerland from black

Shared parking has shown great potential in alleviating the shortage of parking spaces, particularly within residential areas with high parking demand. However, studies on shared parking's effectiveness in meeting nighttime parking demand remain limited. This study investigates whether shared parking facilities, integrating existing resources, can effectively alleviate nighttime parking shortages in

Cycling for transportation is increasingly recognised as a core strategy to combat the climate emergency, particularly in urban environments. In this frame, bike-sharing systems offer a valuable opportunity to attract new users to cycling and promote sustainable mobility. However, the rapid growth in the use of these schemes has exposed critical gaps, such as insufficient cycling infrastructure, system

This mixed-methods study examines transport poverty in Berlin and Hamburg, combining GIS-based spatial analysis of public transport (PT) service levels with qualitative interviews of 40 welfare recipients about their transport experiences. The research reveals that low-income residents do not have worse absolute access to PT, but per-capita service is poorer due to high population density. This highlights

Soil texture is an essential attribute of soil structure, which plays an important role in evaluating soil fertility and carrying out agricultural production. This study developed a novel soil texture estimation model using ZiYuan-1-02D (ZY1-02D) satellite Advanced Hyperspectral Imager (AHSI), based on the mechanism of soil spectral mixing, that enables simultaneous estimation of the three soil texture

At present, there are more than 30 satellite remote sensing Land Surface Temperature (LST) products from kilometers to hectometers resolutions. The accuracy of these products is the key issue for further application. The validation of LST products is mainly achieved through ground observations on homogeneous surfaces, but the accuracy of satellite products on heterogeneous surfaces is also an important

Existing scene classification methods allocate the same computational resources, i.e., all model parameters in the neural network, to each remote sensing image whenever from any geographic scene. However, this might be redundant for images of certain scenes that are easy to discriminate, e.g., homogeneous scenes. This observation motivates us to propose an efficient method for on-orbit scene classification

With the persistent rise in intensity and magnitude of hydrological extremes globally, timely information from operational early flood warning systems provide lead times that translate into actionable strategies to monitor and mitigate flood risk. However, the situation is often different for flood-prone regions of the global south with sparse to no ground flood monitoring systems, where flood management

Previous research concentrated in developed countries argues that individuals engaging in leisure cycling might transition from car- or motorbike-based mobilities to urban cycling. In addition to this, individuals engaging in leisure cycling could also potentially change their perceptions about the multiple risks imposed by motorised vehicles to cyclists and pedestrians, and as a consequence, re-shape

Global warming has led to the accelerated melting of the Arctic ice, making the Northern Sea Route (NSR) an emerging maritime trade route connecting Asia and Europe. Many studies actively seek to capitalize on this new opportunity for shipping to promote the maritime industry's rapid development in various countries. However, few studies have applied a strategic systems perspective to examine the critical

This study investigates the phenomenon of “crown shyness” for intercity airport shuttle services in the Yangtze River Delta Airport Cluster, China. The concept, derived from forest ecology, is applied to describe the non-overlapping nature of shuttle bus routes between airports in overlapping catchment areas, where airports may withdraw services to avoid direct competition. The research employs spatial

Cycling mitigates urban development-related traffic and environmental issues and benefits human health. However, exploring the nonlinear associations between urban environmental factors and cycling remains challenging. Moreover, the potential of crowdsourced data like Strava Heatmap for cycling research has rarely been validated. Using Melbourne as a case study, we assessed the association between

Airborne hyperspectral systems can provide high-resolution hyperspectral images (HSIs) covering large scenes, enabling fine-grained land-cover classification. However, the most popular patch-based methods are limited by low computational efficiency and broken classification results, which hinders the full utilization of this powerful technology in Earth observation applications. Therefore, in this

The p-Median Problem (PMP) is a classical discrete facility location problem with significant implications for optimizing the placement of urban public service facilities. Improved heuristics, a well-established method for solving the PMP, aim to iteratively enhance solution quality through efficient neighborhood exploration. In this study, we model the neighborhood exploration process as a Markov

Deep learning methods for classification have achieved significant advancements in processing 3D point clouds. A fundamental aspect of deep learning networks is how to best aggregate features into a global representation of the point cloud. While many existing networks rely on the traditional max-pooling for feature aggregation due to its efficiency and permutation-invariance, max-pooling has some

Port areas in densely urbanized areas are locations where the lack of development space increasingly limits growth possibilities, and competition for space between stakeholders with diverging interests and land use claims intensifies. The aim of our paper is to enrich the scientific discourse on the port-city interface by arguing for a more multi-facetted understanding of the port-city interface beyond

Telecommuting has long been indicated as a possible travel demand strategy; however, previous studies highlight the complementary effects working from home can have on household trips and vehicle miles traveled (VMT) generation. This study aims to analyze this relationship further by controlling for both socioeconomics and the built environment in pre-COVID-19 cross-sectional data with precise locations

The ramifications for the withdrawal of nonpharmaceutical interventions (NPIs), which are widely implemented worldwide to mitigate the spread of COVID-19 in different cities, remain inadequately understood. Therefore, we quantified socioeconomic resilience following the withdrawal of the zero-COVID policy by examining the reduction and recovery of daily intracity travel intensity in 259 Chinese cities

The spatiotemporal characteristics of remote sensing data are often time-varying, leading to significant fluctuation and instability in tree species classification results across different years, especially in regions referred to as high-variance areas. To improve the stability and accuracy of the classification results, this study proposes a lightweight spatiotemporal classification framework, with

Transport plays a crucial role in access to healthcare for women with disabilities. This study explores healthcare transport access for women with disabilities in Yogyakarta, Indonesia, analysing community-supported transport and commercial transport alternatives in shifting from collective dependency to a transactional nature. However, a conversation about the role of the community remains unnoticed

This study investigates the symmetric and asymmetric relationship between road traffic casualties (RTCs) and economic development in Ghana, applying both Autoregressive Distributed Lag (ARDL) and Nonlinear ARDL (NARDL) models. Using 33 years of data (1991–2023), the research explores how key economic factors—GDP per capita, government spending, capital, and population—affect road traffic fatalities

Exploring the dynamics of urban recreational running, this study examines the spatial and temporal patterns of running activities among men and women in two major North American cities, Montréal, Canada and Washington, DC, USA. A total of 20,446 running trajectories from a geosocial fitness tracking application were analyzed, revealing significant gender differences. These gender preferences differ

Global production networks (GPNs) are a ubiquitous mode of industrial organization. This article advances the theorization of GPN formation. By focusing on the catalytic effect of seemingly unrelated crises that occur in different fields, it demonstrates the value of a conjunctural approach. Situated crises generate a mid-level thrust toward GPN formation, spurring new inter-regional and inter-firm

We propose a cross-nested logit (CNL) approach to investigate how individuals adjust their migration decisions in response to changes in the global landscape. In contrast to the widely used logit model, the CNL enables more intricate substitution patterns among destinations. Leveraging migration aspiration data from India, we demonstrate that the CNL approach outperforms competing approaches in terms

Maritime transportation plays a pivotal role in global trade, making maritime transportation safety a longstanding priority within the maritime industry. With the growing emphasis on big data and geospatial analysis in maritime safety management, this study presents a comprehensive review of 425 academic publications on the topic from 2004 to 2023. First, publication trends, influential journals, and

This mixed-methods study explores mobility – and the lack of it - in Lilongwe, Malawi, a mid-sized African capital city, based on a 600-person household travel survey, developed to capture nuances of gender and class, “mobilities of care”, and suppressed and unfulfilled travel needs, as well as over 100 semi-structured interview with city residents, transport operators, and policy makers. As well as

Electric vehicles (EVs) are recognized as a feasible solution for improving the environment, and environmental factors may also exert effects on the adoption of EVs. Previous research, primarily relying on survey methodologies, indicated that individual environmental awareness promotes the intention to adopt EVs. However, few studies explore the impact of real-world air quality on actual EV adoption

Consideration of spatial dependence in heterogeneous urban landscapes is crucial for understanding how urban landscapes shape biodiversity. However, understanding the linkage between urban landscape patterns, both vertically and horizontally, and urban-dwelling bird species at various spatial scales remains an unsolved question. Here, we investigated how patterns of vertical and horizontal urban landscape

Accurate building height information is essential for urban management and planning. However, most existing methods rely on general segmentation networks for building height estimation, often ignoring the structural characteristics of buildings. This paper proposes a novel structure-aware building height estimation (SBHE) model to address this limitation. The model is designed as a dual-branch architecture:

Forest fires significantly threaten Indonesia’s tropical forests, driven by complex interactions between human activity, environmental conditions and climate variability. This research aims to identify and analyze the factors influencing forest fires in Kalimantan, Sumatra, and Papua during the rainy, dry and all-season conditions using machine learning techniques and create vulnerability prediction

Satellite video super-resolution (SR) aims to generate high-resolution (HR) frames from multiple low-resolution (LR) frames. To exploit motion cues under complicated motion patterns, most CNN-based methods first perform motion compensation and then aggregate motion cues in aligned frames (features). However, due to the low spatial resolution of satellite videos, the moving scales are usually subtle