Table 1
How can geographic information enable Sendai Framework Targets?
| SF TARGET | GEO-ENABLING SF TARGETS |
|---|---|
| 1 | Disaster-related information for affected people or people in danger can be generated through the CS/VGI channels. Rescue and first responder plans and actions can be facilitated from up-to-date (i.e., post-disaster) VGI. |
| 2 | Accurate GI is needed, especially for disaster-prone areas, to enhance resilience capacity through spatial analysis. |
| 3 | Use EO and CS/VGI to plan better and resilient development expansion. Use land tenure and administration systems to quickly restore land rights and minimize economic loss. |
| 4 | Use EO and CS/VGI to map critical, health, and educational infrastructure. Use spatial analysis to enhance resilience and plan evacuation/search/rescue efforts or efficient fall-back scenarios. |
| 5 | Use CS/VGI in collaboration with authoritative (national or local) efforts to enhance spatial data infrastructures. Use CS/VGI powered with cutting edge technological developments (e.g., ML) to minimize cost for data collection, maintenance, and analysis. |
| 6 | Use CS/VGI channels to funnel crowdsourced effort to developing countries. Use technological developments (e.g,. ML) to multiply the efficiency of the crowdsourced contribution or the resilience systems developed. |
| 7 | Use CS/VGI to develop broad networks of citizen sensors that will support any authoritative early warning system and disaster risk information and assessment plan. |
[i] CS: citizen science, EO: Earth observation, ML: machine learning, Framework, VGI: volunteered geographic information.
Table 2
How can geographic information enable Sendai Framework Priorities?
| SF PRIORITY | GEO-ENABLING SF PRIORITIES |
|---|---|
| 1 | Use EO/CS/VGI to collect data to educate authorities and the public about the disaster risk assessment. Innovative methods (e.g., gamification) can bring concepts such as resilience and disaster risk management to broad audiences. |
| 2 | Include CS/VGI and innovative technologies to prepare or update policies and guidelines that will improve the overall governance of disaster management. By engaging with the crowd, a more accurate understanding of the needs and requirements of people and local communities can be acquired by the authorities. |
| 3 | Invest in expanding EO/CS/VGI proliferation to develop a resilient network of up-to-date data collection that can support resilience and disaster reduction planning and action. |
| 4 | Data from CS/VGI/ML and EO can provide a holistic framework for local, national, or regional preparedness against disasters, while securing a head start for a sustainable recovery, rehabilitation, and reconstruction process. |
[i] CS: citizen science, EO: Earth observation, ML: machine learning, Framework, VGI: volunteered geographic information.