Rabigh Lagoon, located on the eastern coast of the Red Sea, is an ecologically rich zone in Saudi Arabia, providing habitat to Avicennia marina mangrove trees. The environmental quality of the lagoon has been decaying since the 1990s mainly from sedi...
Background: Status asthmaticus is a severe, life-threatening asthma exacerbation requiring urgent medical intervention. This study aims to examine its epidemiology in Timis County, Romania, over 11 years. Methods: A retrospective analysis was conduct...
The modeling, analysis and visualization of dynamic geospatial phenomenahas been identified as a key developmental challenge for next-generation GeographicInformation Systems (GIS). In this context, the envisaged paradigmatic extensions tocontemporar...
Dramatic changes of forests have strong influence on regional and global carbon cycles, biodiversity, and ecosystem services. Understanding dynamics of forests from local to global scale is crucial for policymaking and sustainable development. In thi...
Background: Antimicrobial resistance (AMR) is a global health challenge with significant global variation. Little is known about the prevalence on a smaller geographical scale. Objectives: This study aimed to explore the geo-temporal variation in ant...
Analysis of the spatiotemporal distribution of online public opinion topics can help understand the hotspots of public concern. The topic model is employed widely in public opinion topic clustering for social media data. In order to handle topic-clus...
Surveillance videos contain a considerable amount of data, wherein interesting information to the user is sparsely distributed. Researchers construct video synopsis that contain key information extracted from a surveillance video for efficient browsi...
Although there is extensive research demonstrating the significant loss and fragmentation of urban spaces caused by rapid urbanization, to date, no empirical research in Shanghai has investigated the spatiotemporal dynamics of urban open spaces using...
This pioneering study explores the geospatial and temporal patterns of natural and human-induced disasters from 1900 to 2024, providing essential insights into their global distribution and impacts. Significant trends and disparities in disaster occu...
14 September 2021
Disparities and their geospatial patterns exist in morbidity and mortality of COVID-19 patients. When it comes to the infection rate, there is a dearth of research with respect to the disparity structure, its geospatial characteristics, and the pre-i...
Background: As the opioid epidemic continues, understanding the geospatial, temporal, and demand patterns is important for policymakers to assign resources and interdict individual, organization, and country-level bad actors. Methods: GIS geospatial-...
In the context of water scarcity, understanding the mechanisms influencing and altering agricultural water consumption can offer valuable insights into the scientific management of limited water resources. Using Henan Province as a case study, this r...
Monitoring built-up dynamics is essential for sustainable urban and territorial planning. This study presents an innovative geospatial methodology integrating multi-temporal satellite data fusion, transfer learning, machine learning classification, a...
Reclaimed municipal wastewater is a crucial component in biofuel production, especially in regions experiencing increasing freshwater scarcity. However, accurately estimating the potential for fuel production is challenging because of the uneven dist...
Investigating soil and climate variability is critical to defining environments for field crops, understanding yield-limiting factors, and contributing to the sustainability and resilience of agro-ecosystems. Following this rationale, the aim of this...
Urban crime prevention remains a critical challenge intertwined with socioeconomic disparities. This study investigates the spatial nexus between urban deprivation and crime decline in Chicago from 2015 to 2022, addressing the question: How do change...
Urban road traffic spatio-temporal characters reflect how citizens move and how goods are transported, which is crucial for trip planning, traffic management, and urban design. Video surveillance camera plays an important role in intelligent transpor...
Metropolitan cities are facing many socio-economic problems (e.g., frequent traffic congestion, unexpected emergency events, and even human-made disasters) related to urban crowd flows, which can be described in terms of the gathering process of a fl...
Land cover change (LCC) is typically characterized by infrequent changes over space and time. Data-driven methods such as deep learning (DL) approaches have proven effective in many domains for predictive and classification tasks. When applied to geo...
When rivers impinge on the steep bluffs of valley walls, dynamic changes stem from a combination of fluvial and mass wasting processes. This study identifies the geomorphic changes, drivers, and timing of a landslide adjacent to the Apalachicola Rive...
The earth’s surface has an uneven solar energy density that is sufficient to stimulate solar photovoltaic (PV) production. This causes variations in a solar plant’s output, which are impacted by geometrical elements and atmospheric condit...
Indonesia is a country of vast geographical and cultural diversity, hosting numerous cultural festivals annually, such as Sekaten, Labuhan, and the Lembah Baliem Festival. However, as the world’s largest archipelago country, Indonesia faces geo...
Hydrological drought forecasting is essential for effective water resource management planning. Innovations in computer science and artificial intelligence (AI) have been incorporated into Earth science research domains to improve predictive performa...
Geospatial factors, because of their spatio-temporal correlations with demand-driven limited service, offer to improve urban planning decisions and expand the knowledge base in cities. Spatio-temporal analyses require an efficient and comprehensible...
Geospatial technologies have become an essential component of archaeological research, aiding in the identification, mapping, and analysis of archaeological sites. Several journals have published existing narratives on the development and impact of g...
Geospatial monitoring is crucial for landslide research and hazard mitigation. This paper provides a comprehensive overview of contemporary landslide monitoring methods and lays the groundwork for a unified monitoring framework. An in-depth bibliomet...
28 February 2023
Remote sensing (RS), satellite imaging (SI), and geospatial analysis have established themselves as extremely useful and very diverse domains for research associated with space, spatio-temporal components, and geography. We evaluated in this review t...
Urban mobility systems generate large volumes of heterogeneous geospatial data that differ in temporal resolution, spatial coverage, update frequency, and semantic structure, making integrated near-real-time analysis difficult. This paper presents a...
The present survey examines the role of big data analytics in advancing remote sensing and geospatial analysis. The increasing volume and complexity of geospatial data are driving the adoption of machine learning (ML) and artificial intelligence (AI)...
Currently, the best practice to support land planning calls for the development of Spatial Data Infrastructures (SDI) capable of integrating both geospatial datasets and time series information from multiple sources, e.g., multitemporal satellite dat...
With the widespread deployment of ground, air and space sensor sources (internet of things or IoT, social networks, sensor networks), the integrated applications of real-time geospatial data from ubiquitous sensors, especially in public security and...
Visual analysis provides a powerful approach for exploring multidimensional spatiotemporal data, yet it faces significant challenges in simultaneously representing temporal and spatial attributes. A key limitation is the difficulty of visually encodi...
Alpine glaciers are a vital resource for mountain regions. They provide water reserves, support energy production and tourism, and promote biodiversity. However, they are highly susceptible to climate change. In fact, they are recognised as being amo...
Geospatial three-dimensional (3D) raster data have been widely used for simple representations and analysis, such as geological models, spatio-temporal satellite data, hyperspectral images, and climate data. With the increasing requirements of resolu...
Recurrent Neural Networks (RNNs), including Long Short-Term Memory (LSTM) architectures, have obtained successful outcomes in timeseries analysis tasks. While RNNs demonstrated favourable performance for Land Cover (LC) change analyses, few studies h...
Traffic crashes remain a critical public safety issue and are among the leading causes of mortality worldwide. Understanding, analyzing, and forecasting crash trends are essential for implementing effective countermeasures and reducing injury severit...
This paper discusses a methodology where geo-spatial analysis tools are used to quantify risk derived from anthropic activities on habitats and species. The method has been developed with a focus on simplification and the quality of standard procedur...
Respiratory infections caused by Ornithobacterium rhinotrachealis (ORT) and Pasteurella multocida (PM) bacteria are significant threats to the poultry industry by causing economic losses and welfare issues. Due to characterization difficulties and un...
The use of in situ references in Earth observation monitoring is a fundamental need. LUCAS (Land Use and Coverage Area frame Survey) is an activity that has performed repeated in situ surveys over Europe every three years since 2006. The dataset is u...
Contrary to what is represented in geospatial databases, places are dynamic and shaped by events. Point clustering analysis commonly assumes events occur in an empty space and therefore ignores geospatial features where events take place. This resear...
In Taiwan, earthquakes have long been recognized as a major cause oflandslides that are wide spread by floods brought by typhoons followed. Distinguishingbetween landslide spatial patterns in different disturbance regimes is fundamental fordisaster m...
19 August 2021
Physical activity (PA), associated with all-cause mortality, morbidity, and healthcare costs, improves vitamin D absorption, immune response, and stress when completed outdoors. Rural communities, which experience PA inequities, rely on trails to mee...
Open-source disaster intelligence (OSDI) is crucial for improving situational awareness, disaster preparedness, and real-time decision-making. Traditional OSDI frameworks often rely on social media data, which are susceptible to misinformation and cr...
High-resolution GPS trajectories pose a geospatial processing challenge: transforming temporally ordered observations into structured spatial representations that retain intra-trip state transitions at metropolitan scale. This study develops and vali...
Climate change poses an imminent physical risk to cultural heritage sites and their surrounding landscape through intensifying environmental processes such as damaging wetting and drying cycles that disrupt archaeological preservation conditions, and...
The proliferation of geospatial data from diverse sources, such as Earth observation satellites, social media, and unmanned aerial vehicles (UAVs), has created a pressing demand for cross-platform data integration, interoperation, and intelligent dat...
Cities are complex systems composed of numerous interacting components that evolve over multiple spatio-temporal scales. Consequently, no single data source is sufficient to satisfy the information needs required to map, monitor, model, and ultimatel...
Urban built-up areas are the main space carrier of population and urban activities. It is of great significance to accurately identify urban built-up area for monitoring urbanization dynamics and their impact on Sustainable Development Goals. Using o...
In the last decade, real-time access to data and the use of high-resolution spatial information have provided scientists and engineers with valuable information to help them understand risk. At the same time, there has been a rapid growth of novel an...
Crowdsourced geospatial platforms constitute complex socio-technical systems in which data quality and reliability emerge from collective user behavior rather than centralized control. This study proposes a system-oriented, unsupervised machine learn...
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