2023
DOI: 10.1007/s11069-023-05897-z
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The relationship between multiple hazards and deprivation using open geospatial data and machine learning

Abstract: Deprived settlements, usually referred to as slums, are often located in hazardous areas. However, there have been very few studies to examine this notion. In this study, we leverage the advancements in open geospatial data, earth observation (EO), and machine learning to create a multi-hazard susceptibility index and a transferrable disaster risk approach to be adapted in low- and middle-income country (LMIC) cities, with low-cost methods. Specifically, we identify multi-hazards in Nairobi's selected case stu… Show more

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Cited by 4 publications
(1 citation statement)
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“…The SDG Target 11.1 prioritizes the importance of access to adequate, safe, and affordable housing and basic services and to upgrade slums. In Sudan, rapid urbanization combined with economic and political instabilities caused the growth of such areas, often located in hazardous locations with high poverty rates [8][9][10]. Conditions in these areas are often poorly understood and considered in urban policies due to a massive lack of data on urban poverty [11][12][13][14].…”
Section: Introductionmentioning
confidence: 99%
“…The SDG Target 11.1 prioritizes the importance of access to adequate, safe, and affordable housing and basic services and to upgrade slums. In Sudan, rapid urbanization combined with economic and political instabilities caused the growth of such areas, often located in hazardous locations with high poverty rates [8][9][10]. Conditions in these areas are often poorly understood and considered in urban policies due to a massive lack of data on urban poverty [11][12][13][14].…”
Section: Introductionmentioning
confidence: 99%