Spatiotemporal identification of anomalies in a wildlife preserve

Spatiotemporal identification of anomalies in a wildlife preserve

The datasets released for the VAST Challenge 2017 comprise vehicle movement data captured with RFID sensors, chemical emission data from factories captured by gas sensors, and image attributes of the wildlife plant health obtained from satellites, all pertaining to a fictional wildlife preserve. Usi...

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Bibliographic Details
Main Authors: KISHAN, Bharadwaj, ONG, Jason Guan Jie, ZHANG, Yanrong, KAM, Tin Seong
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2017
Subjects:
Spatiotemporal analysis
Geo-spatial analytics
Visual analytics
Traffic pattern detection
Raster image processing
NDVI
MITB student
Databases and Information Systems
Geographic Information Sciences
Online Access:https://ink.library.smu.edu.sg/sis_research/3831
https://ink.library.smu.edu.sg/context/sis_research/article/4833/viewcontent/Example6_VAST_Grand_Challenge_2017_Award_for_Clear_Presentation_of_Hypotheses_and_Supporting_Evidence.pdf
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Institution: Singapore Management University
Language: English

Internet

https://ink.library.smu.edu.sg/sis_research/3831
https://ink.library.smu.edu.sg/context/sis_research/article/4833/viewcontent/Example6_VAST_Grand_Challenge_2017_Award_for_Clear_Presentation_of_Hypotheses_and_Supporting_Evidence.pdf

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