Vulnerabilities and exposure of recent informal urban areas in Lima, Peru

Luis Moya, Marta Vilela, Javier Jaimes, Briggite Espinoza, Jose Pajuelo, Nicola Tarque, Sandra Santa-Cruz, Pablo Vega-Centeno, Fumio Yamazaki

Research output: Contribution to journalArticlepeer-review

Abstract

Urban areas are experiencing rapid growth, accompanied by significant disorder in Lima Metropolitan area and many other cities in South America. Due to decades of uncontrolled construction practices, it is imperative to identify and better understand the types of informalities prevalent in these recent urban areas. Addressing this lack of information is crucial for implementing appropriate countermeasures and developing new policies that benefit the communities residing in such areas. It is worth noting that understanding disaster risk aligns with the first priority of the Sendai Framework for Disaster Risk Reduction. In this study, we propose the use of radar satellite imagery recorded by the Sentinel-1 constellation since 2017 to identify clusters of urban growth in Lima Metropolitan area. Then, the informal urban clusters can be depicted by visual inspection of the last recorded high-resolution optical image. With good spatial and temporal resolution, we identified 25 clusters informal areas. Among our findings, we observed that several of these clusters are situated in landfills comprised of construction and other waste, increasing their vulnerability to debris flow, landslides, and earthquakes. Additionally, we noted that some new urban areas mainly consist of temporarily empty houses, highlighting the feasibility of implementing countermeasures, such as relocations, in the early stages of informal occupation. These results underscore the significant contribution of satellite radar imagery in identifying recent informal urban areas.

Original languageEnglish
Article number100345
JournalProgress in Disaster Science
Volume23
DOIs
StatePublished - Oct 2024
Externally publishedYes

Keywords

  • Informal construction
  • Landfill
  • Lima
  • SAR images
  • Sentinel-1

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