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Change Footprint Pattern Analysis of Crime Hotspot of Indian Districts

  • Mohd Shamsh TabarejEmail author
  • Sonajharia Minz
Conference paper
  • 60 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1141)

Abstract

体育赛事投注记录crime is the ubiquitous feature of all modern cities. different cities face a different crime rate. crime may be committed by a person who belongs to the same locality. in the crime analysis, identification of hotspot is helpful. hotspot of the crime is the region where more criminal activities occur as compared to other regions. to better understand the criminal activity, temporal analysis of hotspot is necessary. in this paper, crime done under the indian penal code (ipc) from 2001 to 2014 is used for the analysis. geo-coding is done on the crime data for spatial processing. kernel density estimation is used to find the hotspot of crime. maps were created using arcgis. to find the footprint of the hotspot, grid overlay is constructed over the study region. grid cell having point from the hotspot is considered as the footprint of the hotspot. a connected component of the hotspot is found to identify the number of hotspots. to find the temporal pattern, a number of hotspots and the footprint of the hotspot are plotted against the year. characteristic vector is defined, which identifies the direction of change. similarity index is defined based on characteristic vector which identifies similarity between two patterns.

Keywords

Special data Hotspot Footprint Crime Grid overlays Kernel density Characteristic vector Similarity Index 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2021

Authors and Affiliations

  1. 1.Jawaharlal Nehru UniversityNew DelhiIndia

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