Integrated remotely sensed datasets for disaster management

Timothy McCarthy, Ronan Farrell, Andrew Curtis, Stewart Fotheringham

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Video imagery can be acquired from aerial, terrestrial and marine based platforms and has been exploited for a range of remote sensing applications over the past two decades. Examples include coastal surveys using aerial video, route-corridor infrastructures surveys using vehicle mounted video cameras, aerial surveys over forestry and agriculture, underwater habitat mapping and disaster management. Many of these video systems are based on interlaced, television standards such as North America's NTSC and European SECAM and PAL television systems that are then recorded using various video formats. This technology has recently being employed as a front-line, remote sensing technology for damage assessment post-disaster. This paper traces the development of spatial video as a remote sensing tool from the early 1980s to the present day. The background to a new spatial-video research initiative based at National University of Ireland, Maynooth, (NUIM) is described. New improvements are proposed and include; low-cost encoders, easy to use software decoders, timing issues and interoperability. These developments will enable specialists and non-specialists collect, process and integrate these datasets within minimal support. This integrated approach will enable decision makers to access relevant remotely sensed datasets quickly and so, carry out rapid damage assessment during and post-disaster.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
Volume7110
DOIs
StatePublished - 2008
Externally publishedYes
EventRemote Sensing for Environmental Monitoring, GIS Applications, and Geology VIII - Cardiff, Wales, United Kingdom
Duration: Sep 15 2008Sep 18 2008

Other

OtherRemote Sensing for Environmental Monitoring, GIS Applications, and Geology VIII
CountryUnited Kingdom
CityCardiff, Wales
Period9/15/089/18/08

Fingerprint

Disaster Management
disasters
Remote Sensing
Disasters
damage assessment
Damage Assessment
remote sensing
Remote sensing
Antennas
Disaster
Ocean habitats
Television standards
Phenylalanine Ammonia-lyase
television systems
Television systems
corridors
interoperability
Ireland
Forestry
habitats

Keywords

  • GIS
  • GPS
  • Interoperability
  • Mobile devices
  • Mobile mapping
  • Navigation
  • Remote sensing
  • Spatial video

ASJC Scopus subject areas

  • Applied Mathematics
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics

Cite this

McCarthy, T., Farrell, R., Curtis, A., & Fotheringham, S. (2008). Integrated remotely sensed datasets for disaster management. In Proceedings of SPIE - The International Society for Optical Engineering (Vol. 7110). [71100M] https://doi.org/10.1117/12.800273

Integrated remotely sensed datasets for disaster management. / McCarthy, Timothy; Farrell, Ronan; Curtis, Andrew; Fotheringham, Stewart.

Proceedings of SPIE - The International Society for Optical Engineering. Vol. 7110 2008. 71100M.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

McCarthy, T, Farrell, R, Curtis, A & Fotheringham, S 2008, Integrated remotely sensed datasets for disaster management. in Proceedings of SPIE - The International Society for Optical Engineering. vol. 7110, 71100M, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VIII, Cardiff, Wales, United Kingdom, 9/15/08. https://doi.org/10.1117/12.800273
McCarthy T, Farrell R, Curtis A, Fotheringham S. Integrated remotely sensed datasets for disaster management. In Proceedings of SPIE - The International Society for Optical Engineering. Vol. 7110. 2008. 71100M https://doi.org/10.1117/12.800273
McCarthy, Timothy ; Farrell, Ronan ; Curtis, Andrew ; Fotheringham, Stewart. / Integrated remotely sensed datasets for disaster management. Proceedings of SPIE - The International Society for Optical Engineering. Vol. 7110 2008.
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