Geospatial analytics is an important field in many communities, including crime science,
transportation science, epidemiology, ecology, and urban planning. However, with the rapid …

This study explores the clusters of closed restaurants in Seoul in response to the COVID-19
pandemic using the relative risk surface (RRS). The RRS developed based on kernel …

Kernel Density Visualization (KDV) has been extensively used in a wide range of
applications, including traffic accident hotspot detection, crime hotspot detection, disease …

Kernel density visualization (KDV) has been widely used in many geospatial analysis tasks,
including traffic accident hotspot detection, crime hotspot detection, and disease outbreak …

Kernel density visualization (KDV) has been the de facto method in many spatial analysis
tasks, including ecological modeling, crime hotspot detection, traffic accident hotspot …

The use of Kernel Density Visualization (KDV) has become widespread in a number of
disciplines, including geography, crime science, transportation science, and ecology, for …

Network K-function has been the de facto operation for analyzing point patterns in spatial
networks, which is widely used in many communities, including geography, ecology …

The widespread of geotagged data combined with modern map services allows for the
accurate attachment of data to spatial networks. Applying statistical analysis, such as hotspot …

Kernel density estimation (KDE) has become a popular method for visual analysis in various
fields, such as financial risk forecasting, crime clustering, and traffic monitoring. KDE can …

Network Kernel Density Visualization (NKDV) has often been used in a wide range of
applications, eg, criminology, transportation science, and urban planning. However, NKDV …