Online change detection: Monitoring land cover from remotely sensed data

Fang, Yi; Ganguly, Auroop R; Singh, Nagendra; Vijayaraj, Veeraraghavan; Feierabend, Robert Neal; Potere, David T

doi:10.1109/ICDMW.2006.125

Title: Online change detection: Monitoring land cover from remotely sensed data

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Abstract

We present a fast and statistically principled approach to land cover change detection. A reference statistical distribution is fitted to prior data based on off-line analysis, and an adaptive metric based on the exponentially weighted moving average (EWMA) of normal scores derived from p-values are tracked for new or streaming data, leading to alarms for large or sustained change. Methods which can track the origin of the change are also discussed. The approach is illustrated with a geographic application which involves monitoring remotely sensed data to detect changes in the normalized difference vegetation index (NDVI) in near real-time. We use Wal-Mart store openings as a nontraditional way to monitor and validate known cases of NDVI change. The proposed approach performs well on this validation dataset.

Authors:

Fang, Yi ^[1]; Ganguly, Auroop R ^[1]; Singh, Nagendra ^[1]; Vijayaraj, Veeraraghavan ^[1]; Feierabend, Robert Neal ^[1]; Potere, David T ^[1]

ORNL

Publication Date:: Sun Jan 01 00:00:00 EST 2006

Research Org.:: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Sponsoring Org.:: USDOE Laboratory Directed Research and Development (LDRD) Program

OSTI Identifier:: 931947

DOE Contract Number:: AC05-00OR22725

Resource Type:: Conference

Resource Relation:: Conference: The 2006 IEEE International Conference on Data Mining (ICDM), Hong Kong, Hong Kong, 20061218, 20061222

Country of Publication:: United States

Language:: English

Citation Formats


                    Fang, Yi, Ganguly, Auroop R, Singh, Nagendra, Vijayaraj, Veeraraghavan, Feierabend, Robert Neal, and Potere, David T. Online change detection: Monitoring land cover from remotely sensed data.  United States: N. p., 2006. 
        Web.  doi:10.1109/ICDMW.2006.125.

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                    Fang, Yi, Ganguly, Auroop R, Singh, Nagendra, Vijayaraj, Veeraraghavan, Feierabend, Robert Neal, & Potere, David T. Online change detection: Monitoring land cover from remotely sensed data.  United States.  https://doi.org/10.1109/ICDMW.2006.125

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                    Fang, Yi, Ganguly, Auroop R, Singh, Nagendra, Vijayaraj, Veeraraghavan, Feierabend, Robert Neal, and Potere, David T. 2006.  
        "Online change detection: Monitoring land cover from remotely sensed data".  United States.  https://doi.org/10.1109/ICDMW.2006.125.

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@article{osti_931947,

  title        = {Online change detection: Monitoring land cover from remotely sensed data},

  author       = {Fang, Yi and Ganguly, Auroop R and Singh, Nagendra and Vijayaraj, Veeraraghavan and Feierabend, Robert Neal and Potere, David T},

  abstractNote = {We present a fast and statistically principled approach to land cover change detection. A reference statistical distribution is fitted to prior data based on off-line analysis, and an adaptive metric based on the exponentially weighted moving average (EWMA) of normal scores derived from p-values are tracked for new or streaming data, leading to alarms for large or sustained change. Methods which can track the origin of the change are also discussed. The approach is illustrated with a geographic application which involves monitoring remotely sensed data to detect changes in the normalized difference vegetation index (NDVI) in near real-time. We use Wal-Mart store openings as a nontraditional way to monitor and validate known cases of NDVI change. The proposed approach performs well on this validation dataset.},

  doi          = {10.1109/ICDMW.2006.125},

  url          = {https://www.osti.gov/biblio/931947},
  journal      = {},
number       = ,

  volume       = ,

  place        = {United States},

  year         = {Sun Jan 01 00:00:00 EST 2006},

  month        = {Sun Jan 01 00:00:00 EST 2006}

}

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https://doi.org/10.1109/ICDMW.2006.125

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