Ankita Wadhwa
ABSTRACT
For a given set of geospatial locations (like, crime activities, terrorist activities, bomb blast locations, etc.), identification of such circular zones where accumulation of points inside the circle is very much greater than outside is important. Such zones are known as hotspots and their detection is known as circular hotspot detection (CHD). Timely detection of circular hotspots is crucial in many societal applications like epidemiology, terrorism, criminology etc. The state-of-the-art method for circular hotspot detection viz. SaTScan is computationally expensive due to enumeration of all possible circles called candidate circular hotspots. Due to its high cost SaTScan is not suitable for applications like terrorist activity hotspot identification, where well-timed identification of hotspots is crucial to prioritize the security efforts put by government and security agencies. Therefore, in this paper, we present an efficient and effective Grey Wolf Optimizer based approach called GWO-CHD for terrorism hotspot detection. The results of GWO-CHD are compared with SaTScan in terms of time required to detect the hotspot and its quality (measured using relative error). All the experiments are performed using terrorist activity data of Indian subcontinent from 2016-2021. Results indicate that hotspots identified by GWO-CHD and SaTScan are almost at par in terms of quality; however, GWO-CHD proved to be much more efficient than SaTScan in terms of computational time.
- J.-G. Lee and M. Kang, “Geospatial Big Data: Challenges and Opportunities,” Big Data Res., vol. 2, no. 2, pp. 74–81, 2015, doi: https://doi.org/10.1016/j.bdr.2015.01.003.Google Scholar
Digital Library
- M. Reibel, “Geographic Information Systems and Spatial Data Processing in Demography: a Review,” Popul. Res. Policy Rev., vol. 26, no. 5, pp. 601–618, 2007, doi: 10.1007/s11113-007-9046-5.Google ScholarCross Ref
- M. Ester, H.-P. Kriegel, and J. Sander, “Spatial data mining: A database approach,” in Advances in Spatial Databases, 1997, pp. 47–66.Google ScholarCross Ref
- A. Kessler , “Spatial and temporal village-level prevalence of Plasmodium infection and associated risk factors in two districts of Meghalaya, India.,” Malar. J., vol. 20, no. 1, p. 70, Feb. 2021, doi: 10.1186/s12936-021-03600-w.Google ScholarCross Ref
- M. Solomon, L. Furuya-Kanamori, and K. Wangdi, “Spatial Analysis of HIV Infection and Associated Risk Factors in Botswana.,” Int. J. Environ. Res. Public Health, vol. 18, no. 7, Mar. 2021, doi: 10.3390/ijerph18073424.Google ScholarCross Ref
- B. Kiani , “Spatio-temporal epidemiology of the tuberculosis incidence rate in Iran 2008 to 2018.,” BMC Public Health, vol. 21, no. 1, p. 1093, Jun. 2021, doi: 10.1186/s12889-021-11157-1.Google ScholarCross Ref
- X. Wu and T. H. Grubesic, “Identifying irregularly shaped crime hot-spots using a multiobjective evolutionary algorithm,” J. Geogr. Syst., vol. 12, no. 4, pp. 409–433, 2010, doi: 10.1007/s10109-010-0107-7.Google ScholarCross Ref
- I. K. Moise and A. R. Piquero, “Geographic disparities in violent crime during the COVID-19 lockdown in Miami-Dade County, Florida, 2018–2020,” J. Exp. Criminol., 2021, doi: 10.1007/s11292-021-09474-x.Google Scholar
- S. Mondal, D. Singh, and R. Kumar, “Crime hotspot detection using statistical and geospatial methods: a case study of Pune City, Maharashtra, India,” GeoJournal, 2022, doi: 10.1007/s10708-022-10573-z.Google Scholar
- [A. Braithwaite and Q. Li, “Transnational terrorism hot spots: Identification and impact evaluation,” Confl. Manag. Peace Sci., vol. 24, no. 4, pp. 281–296, 2007, doi: 10.1080/07388940701643623.Google ScholarCross Ref
- P. Gao, D. Guo, K. Liao, J. J. Webb, and S. L. Cutter, “Early detection of terrorism outbreaks using prospective space-time scan statistics,” Prof. Geogr., vol. 65, no. 4, pp. 676–691, 2013, doi: 10.1080/00330124.2012.724348.Google ScholarCross Ref
- R. Costa, M. Pereira, L. Caramelo, C. Vega Orozco, and M. Kanevski, “Assessing SaTScan ability to detect space-time clusters in wildfires,” in EGU General Assembly Conference Abstracts, 2013, p. 14055.Google Scholar
- T. Purwaningsih and A. Cintami, “Analysis of factors affecting the area of forest and land fires in Indonesia uses spatial regression Geoda and SaTScan,” J. Inform., vol. 12, no. 2, p. 58, 2019, doi: 10.26555/jifo.v12i2.a12340.Google Scholar
- M. Azage, A. Kumie, A. Worku, A. C. Bagtzoglou, and E. Anagnostou, “Effect of climatic variability on childhood diarrhea and its high risk periods in northwestern parts of Ethiopia,” PLoS One, vol. 12, no. 10, pp. 1–18, 2017, doi: 10.1371/journal.pone.0186933.Google ScholarCross Ref
- QGIS Development Team, “QGIS Geographic Information System,” Open Source Geospatial Foundation Project., 2002. http://qgis.osgeo.org.Google Scholar
- M. Kulldorff, “SatScan user guide 2006,” p. 8, 2018, [Online]. Available: //www.satscan.org/.Google Scholar
- A. L. F. F. Cançado, A. R. Duarte, L. H. Duczmal, S. J. Ferreira, C. M. Fonseca, and E. C. D. M. D. M. Gontijo, “Penalized likelihood and multi-objective spatial scans for the detection and inference of irregular clusters,” Int. J. Health Geogr., vol. 9, no. 1, p. 55, Oct. 2010, doi: 10.1186/1476-072X-9-55.Google ScholarCross Ref
- M. Verdiana and Y. Widyaningsih, “Hotspot detection using space-time scan statistics on children under five years of age in Depok,” AIP Conf. Proc., vol. 1827, 2017, doi: 10.1063/1.4979434.Google ScholarCross Ref
- E. Eftelioglu, “A generic dual grid pruning approach for significant hotspot detection,” pp. 1–4, 2016, doi: 10.1145/3003819.3003821.Google ScholarDigital Library
- M. Kulldorff, “A spatial scan statistic,” Commun. Stat. - Theory Methods, vol. 26, no. 6, pp. 1481–1496, Jan. 1997, doi: 10.1080/03610929708831995.Google ScholarCross Ref
- M. Kulldorff, L. Huang, L. Pickle, and L. Duczmal, “An elliptic spatial scan statistic,” Stat. Med., vol. 25, no. 22, pp. 3929–3943, 2006, doi: 10.1002/sim.2490.Google ScholarCross Ref
- E. Eftelioglu, X. Tang, and S. Shekhar, “Geographically Robust Hotspot Detection: A Summary of Results,” Proc. - 15th IEEE Int. Conf. Data Min. Work. ICDMW 2015, pp. 1447–1456, 2016, doi: 10.1109/ICDMW.2015.159.Google ScholarDigital Library
- X. Tang, J. Gupta, and S. Shekhar, “Linear Hotspot Discovery on All Simple Paths: A Summary of Results,” in Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2019, pp. 476–479, doi: 10.1145/3347146.3359100.Google ScholarDigital Library
- E. Eftelioglu, S. Shekhar, J. M. Kang, and C. C. Farah, “Ring-Shaped Hotspot Detection,” IEEE Trans. Knowl. Data Eng., vol. 28, no. 12, pp. 3367–3381, 2016, doi: 10.1109/TKDE.2016.2607202.Google ScholarDigital Library
- S. Mirjalili, S. M. Mirjalili, and A. Lewis, “Grey Wolf Optimizer,” Adv. Eng. Softw., vol. 69, pp. 46–61, Mar. 2014, doi: 10.1016/j.advengsoft.2013.12.007.Google ScholarDigital Library
- “The Armed Conflict Location & Event Data Project.” https://acleddata.com/#/dashboard (accessed Aug. 07, 2021).Google Scholar
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