Understanding the spatial distribution of crime based on its related variables using geospatial discriminative patterns

Wang, Dawei; Ding, Wei; Lo, Henry Z.; Morabito, Melissa S.; Chen, Ping; Salazar, Josue; Stepinski, T. F.

doi:10.1016/j.compenvurbsys.2013.01.008

Cited by 39 publications

(18 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Other approaches support analyses that look for spatiotemporal patterns [24] or [40]. However, these kinds of approaches follow analyses based on a single LoD and, in some cases, they are developed for the detection and exploration of a particular spatiotemporal pattern in a particular application domain [10,60,62,66].…”

Section: Visual Analytics Applicationsmentioning

confidence: 99%

Visual analytics for spatiotemporal events

Silva

Pires

Datia

et al. 2019

Multimed Tools Appl

View full text Add to dashboard Cite

Crimes, forest fires, accidents, infectious diseases, or human interactions with mobile devices (e.g., tweets) are being logged as spatiotemporal events. For each event, its geographic location, time and related attributes are known with high levels of detail (LoDs). The LoD plays a crucial role when analyzing data, as it can highlight useful patterns or insights and enhance the user' perception of phenomena. For this reason, modeling phenomena at different LoDs is needed to increase the analytical value of the data, as there is no exclusive LOD at which the data can be analyzed. Current practices work mainly on a single LoD of the phenomena, driven by the analysts' perception, ignoring that identifying the suitable LoDs is a key issue for pointing relevant patterns. This article presents a Visual Analytics approach called VAST, that allows users to simultaneously inspect a phenomenon at different LoDs, helping them to see in what LoDs do interesting patterns emerge, or in what LoDs the perception of the phenomenon is different. In this way, the analysis of vast amounts of spatiotemporal events is assisted, guiding the user in this process. The use of several synthetic and real datasets supported the evaluation and validation of VAST, suggesting LoDs with different interesting spatiotemporal patterns and pointing the type of expected patterns.

show abstract

Section: Visual Analytics Applicationsmentioning

confidence: 99%

Visual analytics for spatiotemporal events

Silva

Pires

Datia

et al. 2019

Multimed Tools Appl

View full text Add to dashboard Cite

show abstract

“…Spatial clusters are generally referred to in the literature as 'hotspots'. Land price hotspots mapping is a descriptive technique that has recently drawn considerable attention from academics and practitioners alike (Wang et al, 2013). This is because the accurate identification of hotspots and the correct understanding of their relation to explanatory variables can help the decision-maker in analytical works such as planning for amenities and zoning.…”

Section: Spatial Autocorrelation and Hotspot Detectionmentioning

confidence: 99%

A spatial econometric analysis of residential land prices in Kuwait

Mostafa

2018

Regional Studies, Regional Science

View full text Add to dashboard Cite

Land price mapping has recently drawn considerable attention from academics and practitioners alike. This paper investigates the factors influencing residential land prices in a rather underrepresented part of the world. Owing to land prices' spatial association and heterogeneity, the study uses both traditional and Bayesian spatial regression techniques to test the impact of population density, the percentage of Kuwaitis among the total population, the total number of schools, traffic accidents, and air pollution as measured by the prevalence of both carbon monoxide (CO, ppm) and ground-level or tropospheric ozone level (O 3 , ppb) on residential land prices in Kuwait. The general pattern of the results shows that land prices are driven positively by density, the percentage of Kuwaitis and the existence of educational amenities, while air pollution has a negative impact on prices. The analysis also reveals that land prices in Kuwait tend to cluster in groups/hotspots. It is argued that such an accurate identification of hotspots and the correct understanding of their relation to explanatory variables can help decision-makers to make sound decisions in areas as diverse as planning for amenities and zoning.

show abstract

“…Finally we adopted KDE in this specific context because it is by far the best methods of visualizing data patterns as a smooth continuous surface. 4,6,7 KDE is easy to interpret and it gives a better visual impression. To implement our proposed approach we performed a series of experiments using violent scene detection (VSD) 2014 dataset deployed in a simulated study area.…”

Section: Introductionmentioning

confidence: 99%

Crime Hotspot Detection and Monitoring Using Video Based Event Modeling and Mapping Techniques*

Zou¹,

Mohammed²,

Zhu³

et al. 2017

IJCIS

View full text Add to dashboard Cite

This paper presents a new approach to crime hotspot detection and monitoring. The approach consists of three phases' namely: video analysis, crime prediction and crime mapping. In video analysis, crime indicator events are modelled using statistical distribution of semantic concepts. In crime prediction, a neuro-fuzzy method is used to model indicator events. In crime mapping, kernel density estimation is used to detect crime hotspots. This approach is tested in a simulated platform using violent scene detection (VSD) 2014 dataset.

show abstract

Understanding the spatial distribution of crime based on its related variables using geospatial discriminative patterns

Cited by 39 publications

References 19 publications

Visual analytics for spatiotemporal events

Visual analytics for spatiotemporal events

A spatial econometric analysis of residential land prices in Kuwait

Crime Hotspot Detection and Monitoring Using Video Based Event Modeling and Mapping Techniques*

Contact Info

Product

Resources

About