Suchergebnisse

Abstract. Remote sensing analysis is routinely used to map flooding
extent either retrospectively or in near-real time. For flood emergency
response, remote-sensing-based flood mapping is highly valuable as it can
offer continued observational information about the flood extent over large
geographical domains. Information about the floodwater depth across the
inundated domain is important for damage assessment, rescue, and
prioritizing of relief resource allocation, but cannot be readily estimated from
remote sensing analysis. The Floodwater Depth Estimation Tool (FwDET) was
developed to augment remote sensing analysis by calculating water depth
based solely on an inundation map with an associated digital elevation model
(DEM). The tool was shown to be accurate and was used in flood response
activations by the Global Flood Partnership. Here we present a new version
of the tool, FwDET v2.0, which enables water depth estimation for coastal
flooding. FwDET v2.0 features a new flood boundary identification scheme
which accounts for the lack of confinement of coastal flood domains at the
shoreline. A new algorithm is used to calculate the local floodwater
elevation for each cell, which improves the tool's runtime by a factor of 15
and alleviates inaccurate local boundary assignment across permanent water
bodies. FwDET v2.0 is evaluated against physically based hydrodynamic
simulations in both riverine and coastal case studies. The results show good
correspondence, with an average difference of 0.18 and 0.31 m for the
coastal (using a 1 m DEM) and riverine (using a 10 m DEM) case studies,
respectively. A FwDET v2.0 application of using remote-sensing-derived flood
maps is presented for three case studies. These case studies showcase FwDET v2.0 ability to efficiently provide a synoptic assessment of floodwater.
Limitations include challenges in obtaining high-resolution DEMs and
increases in uncertainty when applied for highly fragmented flood inundation
domains.

PurposeAs stated in the United Nations Global Assessment Report 2022 Concept Note, decision-makers everywhere need data and statistics that are accurate, timely, sufficiently disaggregated, relevant, accessible and easy to use. The purpose of this paper is to demonstrate scalable and replicable methods to advance and integrate the use of earth observation (EO), specifically ongoing efforts within the Group on Earth Observations (GEO) Work Programme and the Committee on Earth Observation Satellites (CEOS) Work Plan, to support risk-informed decision-making, based on documented national and subnational needs and requirements.Design/methodology/approachPromotion of open data sharing and geospatial technology solutions at national and subnational scales encourages the accelerated implementation of successful EO applications. These solutions may also be linked to specific Sendai Framework for Disaster Risk Reduction (DRR) 2015–2030 Global Targets that provide trusted answers to risk-oriented decision frameworks, as well as critical synergies between the Sendai Framework and the 2030 Agenda for Sustainable Development. This paper provides examples of these efforts in the form of platforms and knowledge hubs that leverage latest developments in analysis ready data and support evidence-based DRR measures.FindingsThe climate crisis is forcing countries to face unprecedented frequency and severity of disasters. At the same time, there are growing demands to respond to policy at the national and international level. EOs offer insights and intelligence for evidence-based policy development and decision-making to support key aspects of the Sendai Framework. The GEO DRR Working Group and CEOS Working Group Disasters are ideally placed to help national government agencies, particularly national Sendai focal points to learn more about EOs and understand their role in supporting DRR.Originality/valueThe unique perspective of EOs provide unrealized value to decision-makers addressing DRR. This paper highlights tangible methods and practices that leverage free and open source EO insights that can benefit all DRR practitioners.