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Salud Pública de México

versão impressa ISSN 0036-3634


GARROCHO, Carlos; CAMPOS-ALANIS, Juan  e  CHAVEZ-SOTO, Tania. Spatial analysis of buildings damaged by the S19-2017 earthquake in Mexico City. Salud pública Méx [online]. 2018, vol.60, suppl.1, pp.31-40. ISSN 0036-3634.

Our senses have an important capacity to detect spatial patterns, but their limitations are enormous, as Cognitive Psychology and Gestalt have shown for a long time. Therefore, more accurate and reliable instruments are required than our pure senses to identify patterns and act accordingly. Spatial analysis offers several alternatives to identify territorial patterns, estimating their statistical significance, minimizing the possibility of perceiving illusory patterns. This work uses cutting edge developments in conceptual, methodological and technology matters to: a) identify with spatial statistics the clusters of damaged buildings by the earthquake of 19S-2017 in Mexico City (CDMX). The strategy is based on a sequence of zooms at various geographic scales: from the global scale for the entire México City (CDMX), through delegation, neighborhood and block scales, until reaching the minimum scale: buildings; b) locate Emergency Mobile Units using location-allocation models; and c) compare the spatial patterns of collapsed and damaged buildings by the great earthquakes of 1985 and 2017. The results of this work may guide reconstruction, policy actions and research efforts towards spatially and statistically significant priority areas.

Palavras-chave : spatial analysis; spatial cluster analysis; spatial autocorrelation; location-allocation models; Mexico earthquake.

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