Traffic forecasting has been regarded as the basis for many intelligent transportation system (ITS) applications, including but not limited to trip planning, road traffic control, and vehicle routing. Various forecasting methods have been proposed in...
The emergence and rapid advancement of large language models (LLMs), represented by OpenAI’s Generative Pre-trained Transformer (GPT), has brought up new opportunities across various industries and disciplines. These cutting-edge technologies a...
Mining spatiotemporal mobility patterns is crucial for optimizing urban planning, enhancing transportation systems, and improving public safety by providing useful insights into human movement and behavior over space and time. As an unsupervised lear...
Public urban spaces are vital settings for fostering social interaction among people. However, understanding how spatial layouts can promote positive social behaviors remains a critical and debated challenge for urban designers and planners aiming to...
Predicting house prices is a challenging task that many researchers have attempted to address. As accurate house prices allow better informing parties in the real estate market, improving housing policies and real estate appraisal, a comprehensive ov...
Large Language Models (LLMs) such as GPT, BART, and Gemini stand at the forefront of Generative Artificial Intelligence, showcasing remarkable prowess in natural language comprehension and task execution. This paper proposes a novel framework develop...
Spatial epidemiology investigates the patterns and determinants of health outcomes over both space and time. Within this field, Bayesian spatiotemporal models have gained popularity due to their capacity to incorporate spatial and temporal dependenci...
Point cloud processing is an essential task in many applications in the AEC domain, such as automated progress assessment, quality control and 3D reconstruction. As much of the procedure used to process the point clouds is shared among these applicat...
The 15-min city (FMC) is a people-oriented urban development strategy that aims to provide a higher quality of life by manifesting the people’s right to the city. This study proposes an FMC index that measures how close a specific area is to ac...
Crime is always one of the most important social problems, and it poses a great threat to public security and people. Accurate crime prediction can help the government, police, and citizens to carry out effective crime prevention measures. In this pa...
Flood is one of the most frequently occurring and devastating disasters in Nepal. Several locations in Nepal are at high risk of flood, which requires proper guidance on early warning and safe evacuation of people to emergency locations through optim...
Land use and land cover changes driven by urban sprawl has accelerated the degradation of ecosystem services in metropolitan settlements. However, most optimisation techniques do not consider the dynamic effect of urban sprawl on the spatial criteria...
Quantifying traffic congestion is a critical task for transportation planning and research. Numerous metrics have been developed, mainly focusing on changes in vehicle speeds, their extents, and travel time. In this study, new metrics are presented u...
Large language models (LLMs) have demonstrated remarkable capabilities in document processing, data analysis, and code generation. However, the generation of spatial information in a structured and unified format remains a challenge, limiting their i...
Whenever natural and human-made disasters strike, the proper response of the concerned authorities often relies on search and rescue services. Search and rescue services are complex multidisciplinary processes that involve several degrees of interdep...
The think-aloud method is a widely used method for evaluating the usability of websites and software. However, it can also be used with cartographic products, an area which has been neglected up to now. It is a method in which test participants verba...
A tropical cyclone is a significant natural phenomenon that results in substantial socio-economic and environmental damage. These catastrophes impact millions of people every year, with those who live close to coastal areas being particularly affecte...
As neighborhood walkability has gradually become an important topic in various fields, many cities around the world are promoting an eco-friendly and people-centered walking environment as a top priority in urban planning. The purpose of this study i...
The public transport system plays an important role in a city as it moves people from one place to another efficiently and economically. The public transport network must be organized in a way that will cover as many places and as much of the populat...
Recent times have witnessed wildfires causing harm to both ecological communities and urban–rural regions, underscoring the necessity to comprehend wildfire triggers and assess measures for mitigation. This research hones in on Cartagena del Ch...
In late 2023, the image-reading capability added to a Generative Pre-trained Transformer (GPT) framework provided the opportunity to potentially revolutionize the way we view and understand geographic maps, the core component of cartography, geograph...
Cadastral databases have been used for over 20 years, but most contain 2D data. The increasing presence of high-rise buildings with modern architecture complicates the process of determining property rights, restrictions, and responsibilities. It is,...
The automotive industry has experienced remarkable growth in recent decades, with a significant focus on advancements in autonomous driving technology. While still in its early stages, the field of autonomous driving has generated substantial researc...
The emergence of deep learning-based classification methods has led to considerable advancements and remarkable performance in image recognition. This study introduces the Multiscale Feature Convolutional Neural Network (MSFCNN) for the extraction of...
In the face of pressing global challenges such as climate change, socioeconomic inequalities, and rapid urbanization, ensuring sustainable development in the regions has become essential. The COVID-19 pandemic has highlighted how vulnerable cities ar...
Terrorism perpetrated in any country by either internal or external actors jeopardizes the country’s security, economic growth, societal peace, and harmony. Hence, accurate modelling of terrorism has become a necessary component of the national...
The occurrence of flash floods in urban catchments within the Mediterranean climate zone has witnessed a substantial rise due to climate change, underscoring the urgent need for early-warning systems. This paper examines the implementation of an earl...
The past decade has witnessed an increasing frequency and intensity of disasters, from extreme weather, drought, and wildfires to hurricanes, floods, and wars. Providing timely disaster response and humanitarian aid to these events is a critical topi...
There is ongoing debate regarding the association between disorder and criminality. The literature has shown mixed, reduced, or no effects between the two phenomena, although few studies have dealt with the problem in terms of social disorder and its...
Natural hazards threaten millions of people all over the world. To address this risk, exposure and vulnerability models with high resolution data are essential. However, in many areas of the world, exposure models are rather coarse and are aggregated...
Map mosaics of the First Military Survey showing Lower Austria and Hungary (two separate zones and coordinate systems of 1:28,800 survey sections) were georeferenced. Compared to the previous fitting carried out in the framework of the publicly avail...
With recent advancements, large language models (LLMs) such as ChatGPT and Bard have shown the potential to disrupt many industries, from customer service to healthcare. Traditionally, humans interact with geospatial data through software (e.g., ArcG...
This study addresses the prevalent challenges of inefficiency and suboptimal quality in indoor 3D scene generation and rendering by proposing a parameter-tuning strategy for 3D Gaussian Splatting (3DGS). Through a systematic quantitative analysis of...
Over the past two decades, there has been increasing research on the use of artificial intelligence (AI) and geographic information technologies for monitoring and mapping varying phenomena on the Earth’s surface. At the same time, there has be...
Studying the spatiotemporal dynamics of crime is crucial for accurate crime geography research. While studies have examined crime patterns related to weekdays, seasons, and specific events, there is a noticeable gap in research on nighttime crimes. T...
Sustainable Development Goal (SDG) number 14 pertains to the preservation of sustainable marine ecosystems by establishing marine protected areas (MPAs). However, studies have reported massive damage to Indonesian marine ecosystems due to shipping po...
Predicting ship trajectories plays a vital role in ensuring navigational safety, preventing collision incidents, and enhancing vessel management efficiency. The integration of advanced machine learning technology for precise trajectory prediction is...
In the face of persistent challenges posed by urbanization and climate change, the contemporary era has witnessed a growing urgency for urban intelligence and sustainable development. Consequently, a plethora of smart city schedules and policies have...
Road traffic accidents have increased globally, which has led to significant challenges to urban safety and public health. This concerning trend is also evident in California, where major cities have seen a rise in accidents. This research conducts a...
Recent years have witnessed a revolution of artificial intelligence (AI) technologies, highlighted by the rise of generative AI and geospatial artificial intelligence (GeoAI) [...]
Nowadays, city forms are changing due to rapid urbanization and increasing population. In urban morphology studies, walkable street network is examined through the city form to create sustainable cities. This study aims to examine accessibility of st...
In the context of digital transformation, examining the differences in commercial site selection and the factors influencing these decisions holds significant practical value for understanding market adaptation strategies across varying business mode...
This study explores how combining virtual reality (VR) and augmented reality (AR) with geographic information systems (GIS) revolutionizes data visualization. It traces the historical development of these technologies and highlights key milestones th...
Physical activity (PA) plays a vital role in children’s physical and mental health. The built, natural, and socio-demographic environmental variables affect children’s PA behaviors in various ways. However, few studies focus on systematic...
The analysis of large amounts of vessel trajectory data can facilitate more complex traffic management and route planning, thereby reducing the risk of accidents. The application of deep learning methods in vessel trajectory prediction is becoming mo...
This paper is situated within the discussion of mega-urbanization, a particular urbanization process that entails a large-scale agglomeration. In this paper, our focus is on urbanization in Java, Indonesia’s most dynamic region. We add to the l...
Based on a study of the spatial distribution of coffee shops in the main urban area of Beijing, the main influencing factors were selected based on the multi-source space data. Subsequently, three regression models were compared, and the best site se...
Urbanised city transportation simulation needs a wide range of factors to reflect the influence of certain real-life events accurately. The vehicle composition and the timing of the traffic light signal scheduling play an important role in controllin...
Coastal erosion is a critical environmental challenge in the Upper Gulf of Thailand, driven by both natural processes and human activities. This study analyzes 35 years (1988–2023) of shoreline changes using geoinformatics, machine learning alg...
High-definition (HD) maps serve as crucial infrastructure for autonomous driving technology, facilitating vehicles in positioning, environmental perception, and motion planning without being affected by weather changes or sensor-visibility limitation...
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