Blog / November 12, 2020
The Group on Earth Observations (GEO) Disaster Risk Reduction Working Group (DRR WG) is developing and implementing a coherent and crosscutting approach within GEO to advance the use of Earth observations (EO) in support of national and local disaster risk reduction and resilience efforts. Space-based and in situ Earth observations already play critical roles in a wide variety of DRR activities, but the DRR WG will focus on providing tangible solutions and use cases that bring together the EO sector, civil protection organizations and other stakeholders critical to increasing and improving DRR strategies at national and local scales.
Here are three examples illustrating how earth are actively supporting risk reduction activities.
Guided by the 2019 National Plan for Civil Earth Observations and informed by the UN-GGIM WG-Disasters Strategic Framework on Geospatial Information and Services for Disasters, the NASA Disasters Program promotes the use of Earth observations to inform disaster risk reduction activities on a global scale. The Program’s Disasters Mapping Portal recently added geospatially enabled data from the NASA Soil Moisture Active Passive (SMAP) satellite mission. The SMAP data is especially relevant for use in floods and fires. For example, decision makers can use the data to identify dry areas in a region experiencing fires and determine where the fires are likely to travel to next. These data can also be used to predict which local regions may experience flooding in the path of an impending tropical cyclone.
Not only do these data offer a predictive value, they also allow for the incorporation of other datasets by end users into their existing decision workflows, adding a customizable element to the tool. Civil protection organizations preparing for a tropical cyclone could identify (with the SMAP data) where flooding is more likely, while also adding in statistical data to display local concentrations of elderly citizens. This combination allows end users in such a situation to estimate where evacuation may require more time and effort, addressing critical vulnerability and exposure concerns. With Earth observation-derived information, national and local decision makers are better informed and prepared in the face of disasters and natural hazards.
Using advanced methods on data processing for wildfire detection and monitoring, numerical weather prediction models, and remote sensing, the Global Wildfire Information System (GWIS) enables enhanced wildfire prevention, preparedness and effectiveness in wildfire management. GWIS provides the first global database of wildfire events for a continuous time frame (between 2001-2019) enabling the analysis of wildfire regimes worldwide and providing the basis for the assessment of potential effects of climate change.
Over the 2019-2020 summer, bushfires heavily impacted various regions in Australia and caused widespread harm to people and animals and damage to the economy. Multiple states of emergency were declared across New South Wales, Victoria, and the Australian Capital Territory. During the most critical phase between December 2019 and January 2020, the European Commission established contact with the Australian government to offer support in terms of physical means and analysis of the situation, drawing on the GWIS data.
At the global level, GWIS is set to be a unique resource supporting developing countries that may not have access to national-level information on wildfires. Unfortunately, those being most affected by disasters more often include middle and low-income and developing countries according to the UN Development Programme (2018). This global open data portal is providing necessary information to those countries that need it most.
Fiji’s location, on the boundary between the tectonic Australian Plate and the Pacific Plate, makes it vulnerable to many natural hazards, especially tsunamis. Understanding the need for a nationwide tsunami warning mass notification system, Tonkin + Taylor International (T+TI) stepped up to design a Tsunami Early Warning System (TEWS). This system applies a mixed methodology approach, using a combination of hydrodynamic models, probabilistic approaches, satellite and remote sensing, geographic information systems and quantitative analysis to determine maximum tsunami heights and exposure to tsunami hazard.
According to Dr. Bapon Fakhruddin, Senior Natural Hazards and DRR specialist at T+TI, the results of this study provide valuable information for the Government of Fiji, specifically the National Disaster Management Office, Mineral Resources Department, the National Tsunami Warning Centre and at-risk communities. This will increase tsunami risk knowledge, will encourage decisive warning times and allow emergency management to make informative decisions about emergency preparedness and response planning. The Mineral Resources Department (MRD) uses the TEWS to send warning messages within two minutes. Multiple channels can then share the warning within another minute, making the entire warning process no more than three minutes.
These examples demonstrate how earth observations support disaster risk reduction and how they could inform national DRR strategies. The UN Office for Disaster Risk Reduction (UNDRR) is conducting a survey to learn the main challenges and best practices for integrating climate change considerations in national and local disaster risk reduction strategies.
Survey responses will contribute to the development of guidance and related training products on how to better foster coherence between climate change adaptation and disaster risk reduction through national and local DRR strategies in the broader context of sustainable development. The target group for this guidance includes government authorities, practitioners, technical experts, policy makers and others. These are all areas where Earth observations already play an important role.
You can access David Borges post here: originally posted on PreventionWeb.
Thank you for your subscription to the GEO Week 2019 mailing list.
Follow us on: