Publication: Combining human computing and machine learning to make sense of big (aerial) data for disaster response
Date
Date
Date
2016
Journal Article
Published version
Abstract
Abstract
Abstract
Aerial imagery captured via unmanned aerial vehicles (UAVs) is playing an increasingly important role in disaster response. Unlike satellite imagery, aerial imagery can be captured and processed within hours rather than days. In addition, the spatial resolution of aerial imagery is an order of magnitude higher than the imagery produced by the most sophisticated commercial satellites today. Both the United States Federal Emergency Management Agency (FEMA) and the European Commission's Joint Research Center (JRC) have noted that aerial
Metrics
Views
194 since deposited on 2017-01-23
Acq. date: 2025-11-12
Additional indexing
Creators (Authors)
- Ofli, Ferda
- Meier, Patrick
- Imran, Muhammad
- Castillo, Carlos
- Tuia, Devis
- Rey, Nicolas
- Briant, Julien
- Millet, Pauline
- Reinhard, Friedrich
- Parkan, Matthew
- Joost, Stéphane
Volume
Volume
Volume
4
Number
Number
Number
1
Page range/Item number
Page range/Item number
Page range/Item number
47
Page end
Page end
Page end
59
Item Type
Item Type
Item Type
Journal Article
In collections
Dewey Decimal Classifikation
Dewey Decimal Classifikation
Dewey Decimal Classifikation
Keywords
Information Systems and Management, Information Systems, Computer Science Applications
Language
Language
Language
English
Publication date
Publication date
Publication date
2016
Date available
Date available
Date available
2017-01-23
ISSN or e-ISSN
ISSN or e-ISSN
ISSN or e-ISSN
2167-6461
OA Status
OA Status
OA Status
Closed
Publisher DOI
Metrics
Views
194 since deposited on 2017-01-23
Acq. date: 2025-11-12
Closed
Loading...
No files available