Preprints
https://doi.org/10.5194/essd-2018-18
https://doi.org/10.5194/essd-2018-18
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Status: this preprint has been retracted.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. Miori, Nicolle Clements, and Brian W. Segulin

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This preprint has been retracted.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, Nicolle Clements, and Brian W. Segulin

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Virginia M. Miori, Nicolle Clements, and Brian W. Segulin
Virginia M. Miori, Nicolle Clements, and Brian W. Segulin

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This preprint has been retracted.

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.
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