Global trends in satellite-based emergency mapping
Stefan Voigt,1 * Fabio Giulio-Tonolo,2 Josh Lyons,3 Jan Kučera,4 Brenda Jones,5 Tobias Schneiderhan,1 Gabriel Platzeck,6 Kazuya Kaku,7 Manzul Kumar Hazarika,8 Lorant Czaran,9 Suju Li,10 Wendi Pedersen,11 Godstime Kadiri James,12 Catherine Proy,13 Denis Macharia Muthike,14 Jerome Bequignon,15 Debarati Guha-Sapir16
1 German Aerospace Center, Oberpfaffenhofen, Germany. 2 Information Technology for Humanitarian Assistance, Cooperation and Action, Torino, Italy. 3 Human Rights Watch, Geneva, Switzerland. 4 European Commission - Joint Research Centre, Ispra, Italy. 5 U.S. Geological Survey, Sioux Falls, SD, USA. 6 Gulich Institute - Córdoba National University/CONAE, Córdoba, Argentina. 7 Japan Aerospace Exploration Agency, Tsukuba, Japan. 8 Asian Institute of Technology, Klong Luang, Pathumthani, Thailand. 9 United Nations Office for Outer Space Affairs, Vienna, Austria. 10National Disaster Reduction Center of China Beijing, China. 11Geneva International Centre for Humanitarian Demining, Geneva, Switzerland. 12National Space Research and Development Agency, Abuja, Nigeria. 13Centre National d'Études Spatiales, Toulouse, France. 14Regional Centre for Mapping of Resources for Development, Nairobi, Kenya. 15European Space Agency, Brussels, Belgium. 16Université catholique de Louvain (UCL), Brussels, Belgium
SCIENCE sciencemag.org - 15 JULY 2016 • VOL 353 ISSUE 6296 - pp 247- 252
Over the past 15 years, scientists and disaster responders have increasingly used satellite-based Earth observations for global rapid assessment of disaster situations. We review global trends in satellite rapid response and emergency mapping from 2000 to 2014, analyzing more than 1000 incidents in which satellite monitoring was used for assessing major disaster situations. We provide a synthesis of spatial patterns and temporal trends in global satellite emergency mapping efforts and show that satellite-based emergency mapping is most intensively deployed in Asia and Europe and follows well the geographic, physical, and temporal distributions of global natural disasters. We present an outlook on the future use of Earth observation technology for disaster response and mitigation by putting past and current developments into context and perspective.
Conclusion
The comparison between EM-DAT and SEM distributions indicates that global SEM activities are progressively evolving. However, rapid response, accuracy, and increased frequency of SEM mappings are necessary considering the growing vulnerability of global societies, technological dependencies, and projected climate change scenarios. Therefore, the scope of global SEM activities should be broadened to better include drought, extreme temperature events, global pandemics, and other slow on-set events. Nonetheless, a major challenge for EO disaster response is still the satellite tasking, reprogramming, and image collection; these require ~2 days on average to complete, as compared with the ~6 to 8 hours required for mapping after the availability of satellite imagery
Generally speaking, 30 years after the UN General Assembly resolution on remote-sensing principles and the pledge that “Remote sensing shall promote the protection of mankind from natural disasters” (39), the initial organizational and procedural hurdles for making satellite analysis available for operational disaster management have been mostly overcome. Recognizing the diversification and intense utilization of SEM at a global scale, we suggest the establishment of international guidelines on emergency mapping, quality assurance, and harmonization, tailored to specific disaster types. In addition, operational global partnerships among agencies and organizations are essential for strengthening space-based disaster relief efforts. Cooperation among the operational SEM mechanisms must be intensified, within the IWG-SEM (40), and UN-SPIDER (1), as well as through other regional and global initiatives. Improved real-time information exchange on SEM activities, mapping requirements, and locations of available SEMderived products at any given time is a key step in this process
In the coming years, government, public, and commercial sectors will have greater capacity for imaging through satellite constellations, such as the European Copernicus Sentinel constellation and the many commercial systems with very-highresolution optical imaging capability that are in operation or coming up. With the higher throughput of large quantities of imagery and increasingly higher spatial resolution of satellite data, automation and image data mining as well as mass-data processing techniques will play a key role in the global SEM landscape. Single images for disaster mapping will hand over to multiscale, multitemporal nested monitoring approaches, which are relevant to identify disaster hotspots. Coarser and more frequent satellite imagery will be used to identify areas of concern and to then dynamically “zoom in” on the critical regions by using high-spatial-resolution image data. Near real-time observations and direct monitoring of dynamic natural disaster processes such as lava flows, landslides, or floods will be possible from space. In the next 5 to 10 years, substantial scientific, technological, and operational development will handle mass data from different satellite constellations and innovative space sensors. In addition, data relay satellites will be used for boosting reprogramming as well as data downlink. Moreover, automated pattern and object recognition from oblique observations of disaster scenarios is likely to come into wider use. The use of video sequences from space for disaster situation assessment and real-time processing and analysis of satellite imagery for visual analytics and fusion with crowd-sourced and social media information is also likely to play a bigger role, along with high-resolution geostationary EO systems for disaster situational awareness. Online imagery access services and geospatial big data platforms will further shape and advance the global SEM efforts in the near future. These technologies will not all develop at the same pace; nevertheless, there are substantial procedural changes and technological innovations in progress that should be used diligently in order to further advance the global SEM capacities in the years to come.
REFERENCES AND NOTES
1. United Nations, Space-based Information for Disaster Management and Emergency Response, UN-SPIDER Knowledge Portal, accessed 10 December 2015; www.un-spider.org.
2. O. M. Bello, Y. A. Aina, Procedia Soc. Behav. Sci. 120, 365–373 (2014).
3. United Nations Development Programme (UNDP), “Human Development Report” (UNDP, New York, USA, 2015).
4. Committee on Earth Observation Satellites, Satellite Earth Observations in Support of Disaster Risk Reduction, S. W. Ivan Petiteville et al., Eds. (CEOS, 2015), pp. 84.
5. A. Aitsi-Selmi et al., Int. J. Disast. Risk Sci. 7, 1–29 (2016).
6. A. Ajmar, P. Boccardo, F. Disabato, F. Giulio Tonolo, Rendiconti Lincei 26 (suppl. 1), 63 (2015). 7. S. Voigt et al., IEEE Trans. Geosci. Remote 45, 1520–1528 (2007).
8. P. Boccardo, F. Giulio Tonolo, in Engineering Geology for Society and Territory (Springer, 2015), vol. 5, chap. 17, pp. 7.
9. X. Tong et al., ISPRS J. Photogramm. Remote Sens. 68, 13–27 (2012).
10. K. Duda, B. K. Jones, Photogramm. Eng. Remote Sensing 77, 899–907 (2011).
11. S. Voigt et al., Photogramm. Eng. Remote Sensing 77, 923–931 (2011).
12. International Working Group on Satellite-Based Emergency Mapping (IWG-SEM) Webpage, accesseded 10 February 2016; http://iwg-sem.org.
13. K. Gaurav, R. Sinha, P. K. Panda, Nat. Hazards 59, 1815–1826 (2011).
14. W. Bank, Pakistan Floods 2010—Preliminary damage and needs assessment, accessed 31 May 2016 (2010); www.gfdrr. org/sites/gfdrr/files/publication/Pakistan_DNA_0.pdf.
15. K. Kaku, N. Aso, F. Takiguchi, Int. J. Disast. Risk Reduct. 12, 134–153 (2015).
16. J. L. Bessis, J. Bequignon, A. Mahmood, Acta Astronaut. 54, 183–190 (2004).
17. A. Mahmood, J. L. Bessis, J. Bequignon, L. Lauritson, K. V. Venkatachary, Int. Geosci. Remote Sens. 2, 771–773 (2002).
18. B. K. Jones, T. S. Striker, A. Mahmood, G. R. Platzeck, in TimeSensitive Remote Sensing, C. D. Lippitt et al., Eds. (Springer Verlag, 2015), pp. 79–89.
19. Regulation (EU) No 377/2014 of the European Parliament and of the Council of the 3 April 2014 establishing the Copernicus Programme and repealing Regulation (EU) No 911/2010 (2014); http://copernicus.eu/ sites/default/files/library/Regulation_377_2014_Copernicus_ 3April2014.pdf.
20. K. Kaku, A. Held, Int. J. Disast. Risk Reduct. 6, 1–17 (2013).
21. D. Guha-Sapir, P. Hoyois, R. Below, “Annual Disaster Statistical Review 2014—The Numbers and Trends,” [Center for Research on the Epidemiology of Disasters (CRED), 2015].
22. World Bank, Country Income Groups, accessed January 15, 2016; http://data.worldbank.org/news/ new-country-classifications-2015.
23. Materials and methods are available as supplementary materials on Science Online.
24. Oak Ridge National Laboratory, LandScan Population Data 2010, accessed 5 December 2015; http://web.ornl. gov/sci/landscan.
25. J. E. Dobson, E. A. Bright, P. R. Coleman, B. L. Bhaduri, in Remotely Sensed Cities, V. Mesev, Ed. (Taylor & Francis, London, Great Britain, 2003), pp. 267–281.
26. I. Ayala et al., “The Value of Geoinformation for Disaster and Risk Management (VALID),” (Joint Board of Geospatial Information Societies, 2013).
27. Organisation for Economic Co-operation and Development, OECD Handbook on Measuring the Space Economy (OECD Publishing, 2012).
28. M. Rodell, I. Velicogna, J. S. Famiglietti, Nature 460, 999–1002 (2009).
29. J. S. Famiglietti et al., Science 349, 2 (2015).
30. A. AghaKouchak et al., Rev. Geophys. 53, 452–480 (2015).
31. A. A. Borsa, D. C. Agnew, D. R. Cayan, Science 345, 1587–1590 (2014). 3
2. F. Checchi, B. T. Stewart, J. J. Palmer, C. Grundy, Int. J. Health Geogr. 12, 4–12 (2013).
33. F. Rembold, C. Atzberger, I. Savin, O. Rojas, Remote Sens. 5, 1704 (2013).
34. C. Yang, J. H. Everitt, J. M. Bradford, Precis. Agric. 10, 292–303 (2009).
35. R. Bailey, Managing famine risk—Linking early warning to early action, accessed 5 June 2016 (2013); www. chathamhouse.org/sites/files/chathamhouse/public/ Research/Energy,%20Environment%20and%20Development/ 0413r_earlywarnings.pdf.
36. United Nations Office for the Coordination of Humanitarian Affairs, ReliefWeb—West Africa: Ebola Outbreak—Mar 2014, accessed 5 June 2016 (2014); http://reliefweb.int/disaster/ ep-2014-000041-gin.
37. I. C. S. M. Disasters, Ebola Epidemic in West Africa, accessed 15 March 2016; www.disasterscharter.org/web/guest/ activations/-/article/other-in-sierra-leone.
38. J. S. Kargel et al., Science 351, aac8353 (2016).
39. United Nations, 41/65 Resolution Relating to Remote Sensing of the Earth from Space, accessed 10 February 2016; www.un.org/documents/ga/res/41/a41r065.htm.
40. International Working Group on Satellite-Based Emergency Mapping, Emergency Mapping Guidelines (2014); www.un-spider.org/sites/default/files/IWG_SEM_ EmergencyMappingGuidelines_v1_Final.pdf.
41. A. S. Belward, J. O. Skøien, ISPRS J. Photogramm. Remote Sens. 103, 115–128 (2015).
42. University of Twente, ITC’s Database of Satellites and Sensors, accessed 15 January 2016; www.itc.nl/research/products/ sensordb/AllSatellites.aspx.
43. European Space Agency, Earth Observation Portal, accessed 1 December 2015; https://directory.eoportal.org/web/ eoportal/satellite-missions.
44. Committee on Earth Observation Satellites, The CEOS Database, accessed 20 December 2015; http://database. eohandbook.com/timeline/timeline.aspx.
Full Text
Or
ليست هناك تعليقات:
إرسال تعليق