Big earth observation data processing for disaster damage mapping

Bruno Adriano; Naoto Yokoya; Junshi Xia; Gerald Baier

doi:10.1007/978-3-030-55462-0_4

Big earth observation data processing for disaster damage mapping

Bruno Adriano, Naoto Yokoya, Junshi Xia, Gerald Baier

IRIDeS - Risk Evaluation and Disaster Mitigation Research Division

RIKEN

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

4 Citations (Scopus)

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.

Original language	English
Title of host publication	Handbook of Big Geospatial Data
Publisher	Springer International Publishing
Pages	99-118
Number of pages	20
ISBN (Electronic)	9783030554620
ISBN (Print)	9783030554613
DOIs	https://doi.org/10.1007/978-3-030-55462-0_4
Publication status	Published - 2021 May 7

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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.",

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AU - Yokoya, Naoto

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Big earth observation data processing for disaster damage mapping

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