Abstract
Clandestine graves are an expression of extreme violence whose findings have increased in Mexico in recent years. In this paper we use two concepts already studied: spatial clustering and clandestine space and integrate them into a spatial model within a web application, with the aim of improving the previous model by reducing the areas with the highest probability of finding more clandestine graves in Baja California (BC), based on information from 52 grave points already located by the local attorney general’s office. The results confirm that, by incorporating the analysis of point patterns, the search area is substantially reduced (\({<}10\%\)). The model ensures that the final search areas will be within practical distances from most urban settlements, 39 min in the case of BC.
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Notes
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- 2.
Public information access requests are conducted through National Institute for Transparency, Access to Information and Protection of Personal Data (INAI-Plataforma Nacional de Transparencia https://www.plataformadetransparencia.org.mx/web/guest/inicio), which is a website from the Mexican government where citizens can request public information from federal and local authorities, according to the General Law on Transparency and Access to Public Information in Mexico. Authorities are obliged to respond to the information requests within 20 d. Information can be granted or reserved, depending on the sensitivity of the information requested or the authority’s interpretation.
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ANN was conducted using QGIS and Ripley’s K function was conducted using the R programming language.
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In the GEE App, the exponent is limited to small integer values of \(\log _2(n)\).
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Silván-Cárdenas, J.L., Alegre-Mondragón, A.J., Ruiz-Reyes, J. (2022). Geospatial Analysis of Clandestine Graves in Baja California: New Approaches for the Search of Missing Persons in Mexico. In: Tapia-McClung, R., Sánchez-Siordia, O., González-Zuccolotto, K., Carlos-Martínez, H. (eds) Advances in Geospatial Data Science. iGISc 2021. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-030-98096-2_3
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