Geoinformatics'2024 - 35 articles
The 31st International Conference on Geoinformatics
Toronto, ON, Canada | 14–16 August 2024
Volume Editors:
Dongmei Chen, Queens University, Canada
Yuhong He, University of Toronto Mississauga, Canada
Songnian Li, Toronto Metropolitan University, Canada
Governments are encouraging public transportation and bicycle-sharing systems to promote sustainable development and reduce greenhouse gas emissions. Despite the expansion of Taipei’s YouBike program, many stations frequently run out of bikes o...
The International Conference on Geoinformatics is an official conference of the International Association of Chinese Professionals in Geographic Information Sciences (CPGIS) and has attracted not only CPGIS community members but also researchers, pro...
In submitting conference proceedings to Proceedings, the volume editors of the proceedings certify to the publisher that all papers published in this volume have been subjected to peer review administered by the volume editors [...]
Natural disasters often occur unexpectedly, catching people off guard, such as the Hualien earthquake on 3 April 2024. Many of the evacuation-monitoring systems currently in place lack real-time updates of shelter capacities, which raises the risk of...
Land desertification management in the Mu Us Desert has received widespread attention. Assessing land desertification sensitivity is crucial for desertification monitoring and management. This study constructed a comprehensive evaluation index system...
Monitoring river ice is crucial for planning safe navigation routes, with ice–water classification being one of the most important tasks in ice mapping. While high-resolutions satellite imagery, such as synthetic aperture radar (SAR), is well-s...
Methane (CH4), the second-largest greenhouse gas contributing to global warming, has a high warming potential despite its short atmospheric lifespan. Inner Mongolia, due to its high carbon and energy consumption industries, faces significant methane...
This paper conducts a systematic literature review on visibility analysis, aiming to develop a comprehensive classification framework. Visibility analysis is categorized into 2D, 2.5D, and 3D analyses, summarizing its extensive application fields and...
Timely identification of problems in electrical distribution networks is crucial to preventing major failures, reducing costs, and ensuring a reliable power supply. This paper presents a monitoring, inspection, and early warning system designed speci...
In recent years, the digital creative industry has manifested a vigorous growth trend along with the continuous upgrading of the Internet and the leap of the national economy. This research identifies the spatial distribution characteristics of digit...
Districting is essential in establishing efficient, fair, and equitable boundaries across various domains such as trade and service provision, land-use development, school attendance, and political representation. This paper introduces a robust spati...
Urban road collapse is a common disaster in modern cities, posing a severe threat to the safety of life and property of urban residents. Effective risk assessment is crucial for preventing collapses. This study proposes a novel method for assessing t...
Ground collapse is one of the common geological hazards in modern cities. With the development of urbanization, the risk of ground collapse increases, which has a great impact on urban public safety. Ground collapse accidents typically occur due to t...
Landslides are one of the most widespread and hazardous geologic hazards in the world. Landslide susceptibility mapping (LSM) is an effective way to identify landslide-prone areas to prevent and reduce landslide hazards. However, the accuracy of LSM...
Road surface information, encompassing aspects like road surface damages and facility distributions, is vital for maintaining and updating roads in smart cities. The proposed mobile sensing framework uses multi-modal sensors, including a GPS, gyrosco...
Three-dimensional building extraction is crucial for urban planning, environmental analysis, and autonomous navigation. One method for data collection involves using unmanned aerial vehicles (UAVs), which allow for flexible and rapid data acquisition...
Locating facilities such as directional sensors and lights represents a challenging problem given their anisotropic coverage. This paper proposes a spatial optimization model to locate and orient facilities simultaneously. A finite dominating set app...
Flood disasters are among the most severe natural calamities worldwide and typically occur in densely populated areas with abundant lakes and high rainfall. These disasters cause significant damage to the environment and human settlements. Therefore,...
The flow of water in plain river network areas is significantly influenced by various factors, including human activities, upstream water influx, downstream tidal forces, and local rainfall. This leads to a complex situation where poor drainage and f...
Resource-exhausted cities are cities where the ratio of exploited reserves to recoverable reserves exceeds 70%. Long-term energy extraction and consumption lead to weak economic growth, idle industrial land, and ecological imbalances. It is imperativ...
Subtropical tree species identification is a crucial aspect of forest resource monitoring, and the advancement of deep learning has introduced new opportunities for subtropical tree species identification. But, its performance often relies heavily on...
The comfort level of air temperature in a region is one of the influencing factors that affect tourists’ choice of tourism purpose. As a national red cultural mecca, the study of air temperature in Jiangxi Province can provide an important scie...
Timely and precise acquisition of urban functional zone (UFZ) information is crucial for effective urban planning, management, and resource allocation. However, current UFZ mapping approaches primarily focus on individual functional units’ visu...
Revealing the spatial distribution patterns and driving factors of cultivated land fragmentation is of great significance for optimizing the utilization and management of cultivated land resources and promoting moderate-scale agricultural operations....
The color of a cityscape plays a significant role in its atmosphere; however, the traditional city color analysis methods cover a wide range but are not precise enough, requiring field sampling, a lot of manual comparisons, and lacking quantitative a...
Background: China’s rural revitalisation policy has promoted the transformation of rural industries, which always neglect the “dual-carbon” goal in rural. Rural industrial upgrading in Europe can inspire sustainable rural developmen...
Built-up areas are the main gathering place for human activities. The widespread availability of various satellite sensors provides a rich data source for mapping built-up areas. Deep learning can automatically learn multi-level features of targets f...
The three-dimensional model of geographic elements serves as the primary medium for digital visualization. However, the original point cloud model is often vast and includes considerable redundant data, resulting in inefficiencies during the three-di...
For point cloud data compiled over larger spatial domains, the rasterization of features is effectively streamlined by means of structured query language (SQL). This comprises enhanced control with filtering data and implementing specific metrics for...
The Yangtze River Economic Belt (YREB), spanning nine provinces and cities in eastern, central, and western China, is a key region for China’s urbanization. This study utilizes the Google Earth Engine (GEE) platform to integrate four land cover...
Surface soil moisture (SSM) is crucial for understanding terrestrial hydrological processes. Despite its widespread use since 2015, the Soil Moisture Active and Passive (SMAP) SSM dataset faces challenges due to its inherent low spatial resolution an...
This study investigates the potential of gradient-weighted class activation mapping (Grad-CAM++) in enhancing land cover and land use (LCLU) classification using deep learning models. A U-Net and an Attention U-Net model were trained on Sentinel-2 im...
Ecosystem services, including climate regulation and biodiversity maintenance, are vital for human well-being and sustainable development. The ecological quality evaluation system, based on the three dimensions of ecological function, ecological stab...
Land use change and energy consumption caused by human activities is the primary source of carbon emissions and a driver of climate change. The study focused on the Yangtze River Delta (YRD), using the China Land Cover Dataset (CLCD) to calculate the...
Unmanned aerial vehicle (UAV) navigation in indoor environments is challenging due to varying light conditions, the dynamic clutter typical of indoor spaces, and the absence of GNSS signals. In response to these complexities, emerging sensors, such a...
