Is your neighbor your friend? Scan methods for spatial social network hotspot detection

Abstract

In spatial statistical analysis, hotspot or cluster detection can find statistically significant concentrations of an event or phenomenon, such as incidences of cancer, locations of similar tree species, or clusters of restaurants across a city. Traditional point pattern analysis methods, such as Getis-Ord GI and Gi* statistics or Ripley's Kfunction, are often used to find these clusters. For example, given the locations of individuals who belong to a

A data‐driven adaptive geospatial hotspot detection approach in smart cities

“…However, this has also resulted in complex urban management challenges, including pollution, traffic congestion, disease spread, and public safety concerns. Recent advances in sensor and communication technologies enable the collection of vast amounts of urban data, facilitating deeper insights and solutions to the complexities arising from rapid urbanization (Cesario, 2023).The utilization of urban spatial big data for hotspot detection constitutes a pivotal research area in the field of smart cities (Liang et al, 2023). Study objects in urban space tend to be spatially heterogeneous, and urban hotspots can be considered as areas with a high density of point data distribution (Cesario et al, 2022).…”

“…The utilization of urban spatial big data for hotspot detection constitutes a pivotal research area in the field of smart cities (Liang et al, 2023). Study objects in urban space tend to be spatially heterogeneous, and urban hotspots can be considered as areas with a high density of point data distribution (Cesario et al, 2022).…”