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Big Earth Observation Data Processing for Disaster Damage Mapping

In: Handbook of Big Geospatial Data

Author

Listed:
  • Bruno Adriano

    (RIKEN Center for Advanced Intelligence Project)

  • Naoto Yokoya

    (RIKEN Center for Advanced Intelligence Project)

  • Junshi Xia

    (RIKEN Center for Advanced Intelligence Project)

  • Gerald Baier

    (RIKEN Center for Advanced Intelligence Project)

Abstract

Ever-growing earth observation data enable rapid recognition of damaged areas caused by large-scale disasters. Automation of data processing is the key to obtain adequate knowledge quickly from big earth observation data. In this chapter, we provide an overview of big earth observation data processing for disaster damage mapping. First, we review current earth observation systems used for disaster damage mapping. Next, we summarize recent studies of global land-cover mapping, which is essential information for disaster risk management. After that, we showcase state-of-the-art techniques for damage recognition from three different types of disaster, namely, flood mapping, landslide mapping, and building damage mapping. Finally, we summarize the remaining challenges and future directions.

Suggested Citation

  • Bruno Adriano & Naoto Yokoya & Junshi Xia & Gerald Baier, 2021. "Big Earth Observation Data Processing for Disaster Damage Mapping," Springer Books, in: Martin Werner & Yao-Yi Chiang (ed.), Handbook of Big Geospatial Data, chapter 0, pages 99-118, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-55462-0_4
    DOI: 10.1007/978-3-030-55462-0_4
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