The localization of non-residential buildings over wide geographical areas is used as input within several contexts such as disaster management, regional and national planning, policy making and evaluation, among others. While the built-up environment has been continuously and globally mapped, given the efforts on producing synoptic land cover information; little attention has been given to the land

Here, a methodology to generate national-scale annual 10 m spatial resolution land use and land cover maps for Fiji (Fiji LULC) is presented. A training dataset of 13,419 points with a LULC label across three years from 2019 to 2021 was generated alongside a nationally representative test dataset of 834 points. These data were used to train a random forests model to convert an image stack of pre-processed

In remote sensing mapping studies, selecting an appropriate test set to accurately evaluate the results is critical. An imprecise accuracy assessment can be misleading and fail to validate the applicability of mapping products. Commencing with the WHU-Hi-HanChuan dataset, this paper revealed the impact of sample size ratios in test sets on accuracy metrics by generating a series of test sets with varying

Newly constructed transport infrastructure may have varying socioeconomic effects across cities and regions. This study employs a spatial equilibrium model to examine how the development of expressways and high-speed rails (HSRs) may induce changes in employed residents, housing rents, and consumer surplus within China's Yangtze River Delta region. Empirical findings indicate limited effects of transport

Before 2018, Saudi Arabia was the only country that enshrined a legal prohibition on women driving. However, little has been done to empirically investigate the associations between female commute cost and labor supply before the driving ban was lifted. This is largely due to the data scarcity on disaggregated-level female mobility patterns and travel behaviors. To fill the gap, this study deployed

This study investigates the geographic and annual variations in carbon dioxide (CO2) emissions and fuel consumption generated by private vehicles across Australia's regions over an 18-year period (2002 to 2020). We examine the influence of vehicle numbers, geography, and time on emissions and fuel consumption using spatial analysis alongside panel regression. Emissions remain relatively high in North

This article studies how airports affect regional growth in population and employment, considering heterogeneity in the circumstances of an airport’s opening. We use synthetic controls with staggered adoption and data on the whole airport system in Norway for 1950–2019. We find positive overall effects of airports on population and employment growth. Addressing heterogeneity, we find relatively strong

Impervious surfaces are important indicators of human activity, and finding ways to quantify the gain and loss of impervious surfaces is important for sustainable urban development. However, most relevant studies assume that the transformation of natural surfaces to impervious surfaces is irreversible; thus, the losses of impervious surfaces are often ignored. Here, we propose a novel framework taking

The El Niño Southern Oscillation (ENSO) significantly influences global climate patterns, with one of the strongest warm phases (El Niño) occurring in 2023, altering precipitation and temperature regimes. In this study, the spatiotemporal variability in snow cover across Canadian provinces from December 2023 to February 2024 relative to long-term averages is explored. The NOAA-OISST, NOAA-CSFV2, and

This study investigates the reconstruction of climatological patterns and vegetation dynamics in the Horn of Africa region using high temporal resolution (i.e. daily) Normalized Difference Vegetation Index (NDVI) datasets. The analysis compares a straight-forward processing approach to derive a daily vegetation index from a geostationary (SEVIRI) satellite with existing NDVI series from geostationary

Zanthoxylum rust (ZR) poses a significant threat to Zanthoxylum bungeanum Maxim.(ZBM) production, impacting both the yield and quality. The lack of current research on ZR using unmanned aerial vehicle (UAV) remote sensing poses a challenge to achieving precise management of individual ZBM plant. This study acquired six UAV hyperspectral images to create a ZR inversion dataset . This dataset, to our

With advances in data collection technology, the volume of recent remote sensing point cloud datasets has grown significantly, posing substantial challenges for point cloud deep learning, particularly in neighborhood aggregation operations. Unlike simple pooling, neighborhood aggregation incorporates spatial relationships between points into the feature aggregation process, requiring repeated relationship

Plant foliage is known to respond rapidly to environmental stressors by adjusting leaf orientation at different timescales. One of the most fascinating mechanisms is paraheliotropism, also known as light avoidance through leaf movement. The leaf orientation (zenith and azimuth angles) is a parameter often overlooked in the plant and remote sensing community due to its challenging measurement procedures

The heterogeneity and complexity of multimodal data in high-resolution remote sensing images significantly challenges existing cross-modal networks in fusing the complementary information of high-resolution optical and synthetic aperture radar (SAR) images for precise semantic segmentation. To address this issue, this paper proposes a multi-layer perceptron (MLP) dominated gate fusion network (MGFNet)

The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) mission, spanning the past five years, has collected extensive three-dimensional Earth observation data, facilitating the understanding of environmental changes on a global scale. Its key product, Land and Vegetation Height (ATL08), offers global land and vegetation height data for carbon budget and cycle modeling. Consistent measurement accuracy

Click on the article title to read more.

Traditional methods for measuring asset wealth face limitations due to data scarcity, making it challenging to apply them on a large scale and over long periods with fine granularity. Publicly available satellite images, such as nighttime light imagery, have become an important alternative data source for estimating asset wealth. This study thoroughly exploited the spatial neighborhood information

Supervised classification methods can distinguish between noise and signal in ice, cloud, and land elevation satellite-2 (ICESat-2) data across various feature perspectives and autonomously optimize parameters. Nevertheless, model generalization remains a significant limitation for practical applications. This study focuses on developing a universal denoising model for ICESat-2 using machine learning

Transportation economics studies show that the activity density, in particular, employment density, is influenced by availability and quality of transportation infrastructure and services, including public transit. These studies also show that businesses and economic activities may have unique requirements, preferences, and characteristics, which may lead to varying effect of transportation on different

Hyperspectral unmixing is of vital importance within the realm of hyperspectral analysis, which is aimed to decide the fractional proportion (abundances) of fundamental spectral signatures (endmembers) at a subpixel level. Unsupervised unmixing techniques that employ autoencoder (AE) network have gained significant attention for its exceptional feature extraction capabilities. However, traditional

The escalating water pollution in many lakes has led to more frequent occurrences of algal bloom disasters in recent decades. The severity of these disasters can be assessed through remote sensing techniques, specifically using the Normalized Difference Vegetation Index (NDVI) for measurement. However, NDVI observations using optical sensors are often affected by cloud and fog in areas with numerous

Invasive alien plant species (IPS) are one of the major threats to biodiversity and ecosystem services. As the dynamics of biological invasions by non-native plant species are expected to intensify with climate change, there is an increasing need to provide accessible information on the distribution of IPS to improve environmental management programmes. Monitoring the probability of occurrence of IPS

Highly destructive flood disasters have occurred frequently recently. Related to this, accurate mapping of flood areas is a necessary undertaking that helps to understand the temporal and spatial evolution patterns of floods. Thus, this paper proposes a novel, unsupervised multi-scale machine learning (ML) approach for urban flood mapping with SAR images from the perspective of information mining and

Quick and high-precision semantic segmentation from Mobile Laser Scanning (MLS) point clouds faces huge challenges such as large amounts of data, occlusion in complex scenes, and the high annotation cost associated with 3D point clouds. To tackle these challenges, this paper proposes a novel efficient and high-precision semantic segmentation method Mapping Considering Semantic Segmentation (MCSS) for

Economic impact estimates of the initial lockdowns due to the COVID-19 pandemic showed a significant reduction in economic activities globally. However, the succeeding impacts and their spatiotemporal distribution within countries remain unknown. Studies showed that nighttime light data (NTL) has effectively revealed the spatiotemporal dimensions of the economic effects of COVID-19. Thus, this study

In this paper we use complex network analysis to describe fossil fuel spatial flows among 132 places covering the entire United States in 2017 and in 2022. These spatial flows are for crude petroleum, gasoline, and oil fuels. The analysis shows that all three fuels have different network topology. For all six networks we find major hubs of crude petroleum and its products, gasoline and fuel oils, concentrated

Empirical studies of logistics location choice have largely focused on logistics as a single sector. This research attempts to address this research gap by analysing the heterogeneity in locational preferences of logistics across facility types and sizes. We estimate a multinomial logistic regression model to study the relative impact of various spatial drivers on logistics development in the Netherlands

During the last few decades, the gap between the most prosperous metropolitan areas and the rural areas has widened, especially since the 2008 crisis. This gap has been particularly relevant in relation to population and employment. However, the bi-directional links in terms of population and employment between rural places and the most urbanized areas have been partly overlooked by the literature

Declining fertility and the persistent underrepresentation of women in the labour market are key concerns of our time. The fact that they overlap is not fortuitous. Traditionally, women everywhere have faced a conflict in balancing their career ambitions with family responsibilities. Yet, the pressures arising from this conflict vary enormously from one place to another. Existing research has tended

Precise forecasting of land use modifications and carbon storage (CS) alterations is essential for effective regulatory measures and ecological quality enhancement. However, there are limited studies on land use dynamics and its impact on CS in the arid regions of Northwest China. Therefore, this study explores land use and CS changes in the Tulufan-Hami Basin from 2000 to 2050. The SD-FLUS and InVEST

Cloud distribution significantly impacts global climate change, ecosystem health, urban environments, and satellite remote sensing observations. However, past research has primarily focused on the meteorological characteristics of clouds with limitations in scale and resolution, leading to an insufficient understanding of large-scale cloud distribution and its relationship with land surface cover and

Examine the effects of evapotranspiration (ET), water use efficiency (WUE), and evaporative stress index (ESI) on wildfire temperature and extent. Compare land cover type proportions in burned area with land cover type proportions in New Mexico.

A new private port and logistics complex is under construction in the city of Chancay, located north of Lima, Peru, as part of China’s Belt and Road Initiative (BRI) promising to change life in the...

Replications confront existing explanations with new evidence by retesting prior claims using new data and similar research procedures. Publishing replication studies remains uncommon in the geogra...

Despite the danger presented to communities, there is still a notable lack of knowledge on how the locations of tornadoes and tornado tracks, especially for violent tornadoes (VTs), vary on small s...

Accurate wetland extraction using remote sensing technology poses significant challenges due to the complex hydrological dynamics, diverse landscapes, and varied wetland types. Constructing a reliable sample set is a critical first step in overcoming these challenges for large-scale wetland mapping. To meet the demand for global wetland mapping, this study (1) proposes a multi-level wetland classification

Over the past two decades, the Canadian Arctic has experienced a marked reduction in sea ice extent, coinciding with a significant rise in ship traffic. This study explores the relationship between ship traffic, shipping accidents, accident rates, and diminishing sea ice from 1990 to 2022 during the shipping season. The findings reveal that ship traffic has increased substantially along major Arctic

This article addresses geographies of internationalism, feminism, pacifism, and anticolonialism, by investigating the case of pacifist and feminist activist Clementina Batalla Torres de Bassols (18...

Climate change significantly impacts vegetation gross primary productivity (GPP), yet uncertainties persist in the carbon cycle of tropical terrestrial ecosystems due to incomplete consideration of productivity drivers and lag effects. To address this, we developed a remote sensing-based process model by integrating high-resolution vegetation indices and multi-layer soil hydrological module, to simulate

Modeling incompatible spatial data, i.e., data with different spatial resolutions, is a pervasive challenge in remote sensing data analysis. Typical approaches to addressing this challenge aggregate information to a common coarse resolution, i.e., compatible resolutions, prior to modeling. Such pre-processing aggregation simplifies analysis, but potentially causes information loss and hence compromised

Accurate assessment of distribution patterns and dynamic insights into rural populations is pivotal for comprehending domestic waste generation, recycling, and transportation in rural territories. Given that the dispersion of rural inhabitants exhibits minimal variation and maintains stability, this research endeavors to establish a pragmatic model for rural domestic waste collection and routing, leveraging

Often promoted by planning and transportation authorities as one of the principal ways to reduce the impact of mobility on transportation gas emissions, carpooling practices have increased over recent decades for daily commuting as well as long-distance travel. However, mainly due to the lack of data, little is known about the geography of these trips. On the one hand, the intensity of supply and demand

The street environment correlates with perceived activity opportunities for older adults. While numerous studies have examined the transportation and social attributes of street environments, the natural attributes have been less explored. Furthermore, the nonlinear relationship between the street environment and perceived activity opportunities across different spatial scales remains under-researched

Taking London as a location with which to measure the ripple effect in the UK housing market, this study aims to explain and verify the high degree of correlation between inter-regional transportation and the regional correlation of the housing market. Based on the literature on the relationship between short-term mobility and long-term migration, this paper illustrates that the extent to which people

Weather-related road closures have the potential to cause serious impacts to society by disrupting road network function. Impacts to the population are variable based on the temporal and spatial extent of the closures, as well as the ability of the road network to absorb the impacts of closures by offering suitable alternative routes. In general, analyses of the impacts of weather-related road closures

Remote sensing applications are garnering much attention as a promising solution for detection, tracking and monitoring of floating marine litter (FML). With an increasing number of studies portraying the technical feasibility of FML detection, we attempt here to experimentally observe a minimum detectable abundance fraction of floating plastic (white HDPE sheets), in a Sentinel-2 and PlanetScope SuperDove

Very high-resolution (VHR) optical satellite imagery offers significant potential for detailed land cover mapping. However, terrain shadows, which appear dark and lack texture and detail, are especially acute at low solar elevations. These shadows hinder the creation of spatially complete and accurate land cover maps, particularly in rugged mountainous environments. While many methods have been proposed

Unoccupied aerial vehicles (UAVs) equipped with thermal cameras show great promise for precision agriculture, but challenges persist in analyzing land surface temperature (LST). This study explores the influence of ambient environmental conditions and intrinsic characteristics of uncooled thermal cameras on the accuracy of temperature measurements obtained through UAV-based thermal cameras. The research

With rapid advancements in automated driving technologies, there is a growing emphasis on enhancing physical and digital infrastructure to ensure safe and efficient integration of Automated Vehicles (AVs) into road networks. This study conducts the first exploratory analysis of the impact of heterogeneity in road infrastructure readiness on the usefulness of AVs for urban commuting, with a focus on

Long historical records and free accessibility have made Landsat data valuable for time-series analysis. However, Landsat time-series analysis is restricted for coastal areas due to the lack of suf...

The U.S. National Park System began at Yellowstone in 1872 and the National Park Service (NPS) took over its management in 1916. That system has evolved through nine processes to 429 units in every...

Accurate urban traffic forecasting is essential for intelligent transportation systems (ITS). However, the majority of existing forecasting methodologies predominantly concentrate on point-based forecasts (e.g., traffic detector forecasts). A limited number of them pay attention to the urban bidirectional road segments and the complex road network topology. To advance accurate traffic forecasting in

The paper introduces an original method for effective spatial data processing, particularly important for land administration and real estate governance. This approach integrates Unmanned Aerial Vehicle (UAV) data acquisition and processing with Artificial Intelligence (AI) and Geometric Transformation algorithms. The results reveal that: (1) while the separate applications of YOLO and Hough Transform

Climate-change-induced shifts in the timing of leaf emergence during spring have been widely documented and have important ecological consequences. However, mechanistic knowledge regarding what controls the timing of spring leaf emergence is incomplete. Field-based studies under natural conditions suggest that climate-warming-induced decreases in cold temperature accumulation (chilling) have expanded

This paper proposes a new enhanced propensity to fly model based on multilinear regression analysis, which is used to analyse the air transport market potential in four central European countries. Eurostat database data from 31 European states in years 2009–2019 were used with an emphasis on data homogeneity and robustness. To evaluate the quality of the regression model, the influence of seven variables

Intra-destination travel behavior of tourists is underexplored, particularly regarding the determinants of their preference for tourism spots in and around a prominent tourism destination. This study aims to investigate the tourist groups' preferences for visiting micro-destinations around the pilgrimage city of Puri, India, by utilizing the socio-demographic profile and travel/stay characteristics

Several countries have implemented designated school zones and installed traffic calming measures to enhance the safety of vulnerable pedestrians near schools. While macro-level built environment attributes (e.g., land use) have been widely acknowledged in relation to the role they play in urban traffic safety, the effects of micro-level streetscape characteristics on crash frequency have not been

Changes in landscape configuration significantly impact ecosystems and the services they provide, including disease regulation for both humans and wildlife. Land use conversion usually favors disturbed-adapted species, which are often known reservoirs of zoonotic parasites, thereby potentially escalating spillover events (i.e., the transmission of parasites to new hosts, including humans). Here we

Protected areas are a primary instrument for biodiversity conservation, and area-based targets have become a hallmark of global efforts with the 2022 Kunming-Montreal Global Biological Framework re...

Sustainable management of coastal aquaculture ponds could achieve win-win between food and economic benefits and ecological conservation including waterbird. In this study, 5790 Harmonized Landsat and Sentinel-2 images from July 2021 to June 2022 and 498 Sentinel-1 images from July 2021, August 2021, and June 2022 as supplementary data were collected to calculate multiple water indices. Based on Otsu