Spatial-temporal event detection in climate parameter imagery.

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Description

Previously developed techniques that comprise statistical parametric mapping, with applications focused on human brain imaging, are examined and tested here for new applications in anomaly detection within remotely-sensed imagery. Two approaches to analysis are developed: online, regression-based anomaly detection and conditional differences. These approaches are applied to two example spatial-temporal data sets: data simulated with a Gaussian field deformation approach and weekly NDVI images derived from global satellite coverage. Results indicate that anomalies can be identified in spatial temporal data with the regression-based approach. Additionally, la Nina and el Nino climatic conditions are used as different stimuli applied to the ... continued below

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42 p.

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McKenna, Sean Andrew & Gutierrez, Karen A. October 1, 2011.

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Description

Previously developed techniques that comprise statistical parametric mapping, with applications focused on human brain imaging, are examined and tested here for new applications in anomaly detection within remotely-sensed imagery. Two approaches to analysis are developed: online, regression-based anomaly detection and conditional differences. These approaches are applied to two example spatial-temporal data sets: data simulated with a Gaussian field deformation approach and weekly NDVI images derived from global satellite coverage. Results indicate that anomalies can be identified in spatial temporal data with the regression-based approach. Additionally, la Nina and el Nino climatic conditions are used as different stimuli applied to the earth and this comparison shows that el Nino conditions lead to significant decreases in NDVI in both the Amazon Basin and in Southern India.

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42 p.

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  • Report No.: SAND2011-6876
  • Grant Number: AC04-94AL85000
  • DOI: 10.2172/1029771 | External Link
  • Office of Scientific & Technical Information Report Number: 1029771
  • Archival Resource Key: ark:/67531/metadc847185

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

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  • October 1, 2011

Added to The UNT Digital Library

  • May 19, 2016, 3:16 p.m.

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  • Dec. 7, 2016, 9:33 p.m.

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McKenna, Sean Andrew & Gutierrez, Karen A. Spatial-temporal event detection in climate parameter imagery., report, October 1, 2011; United States. (digital.library.unt.edu/ark:/67531/metadc847185/: accessed November 17, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.