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Preprints
https://doi.org/10.5194/essd-2018-18
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2018-18
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  24 Apr 2018

24 Apr 2018

Status
This preprint has been retracted.

Heuristic Approach to Multidimensional Temporal Assignment of Spatial Grid Points for Effective Vegetation Monitoring and Land Use in East Africa

Virginia M. Miori1, Nicolle Clements1, and Brian W. Segulin2 Virginia M. Miori et al.
  • 1Department of Decision and System Sciences, Saint Joseph's University, Philadelphia, PA 19131, USA
  • 2The Rovisys Company, Aurora, Ohio 44202, USA

Abstract. In this research, vegetation trends are studied to give valuable information toward effective land use in the East African region, based on the Normalized Difference Vegetation Index (NDVI). Previously, testing procedures controlling the rate of false discoveries were used to detect areas with significant changes based on square regions of land. This paper improves the assignment of grid points (pixels) to regions by formulating the spatial problem as a multidimensional temporal assignment problem. Lagrangian relaxation is applied to the problem allowing reformulation as a dynamic programming problem. A recursive heuristic approach with a penalty/reward function for pixel reassignment is proposed. This combined methodology not only controls an overall measure of combined directional false discoveries and nondirectional false discoveries, but make them as powerful as possible by adequately capturing spatial dependency present in the data. A larger number of regions are detected, while maintaining control of the mdFDR under certain assumptions. Data Link: https://figshare.com/s/ed0ba3a1b24c3cb31ebf DOI: https://figshare.com/articles/NDVI_and_Statistical_Data_for_Generating_Homogeneous_Land_Use_Recommendations/5897581

This preprint has been retracted.

Virginia M. Miori et al.

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Virginia M. Miori et al.

Virginia M. Miori et al.

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Short summary
Vegetation trends are studied for effective land use in the East African region, based on the Normalized Difference Vegetation Index (NDVI). This paper improves upon an original random block assignment of grid points (pixels) to regions by formulating the spatial problem as a multidimensional temporal assignment problem. This methodology controls an overall measure of false discoveries, but make them as powerful as possible by capturing spatial dependency present in the data.
Vegetation trends are studied for effective land use in the East African region, based on the...
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