the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
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
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This preprint has been retracted.
-
Retraction notice
This preprint has been retracted.
-
Preprint
(618 KB)
Virginia M. Miori et al.
Interactive discussion


-
RC1: 'Review ESSD-2018-18', Anonymous Referee #1, 10 Aug 2018
-
EC1: 'Evaluation from 2nd reviewer', David Carlson, 12 Sep 2018
-
EC2: 'Options for ESSD-2018-18', David Carlson, 14 Sep 2018
Interactive discussion


-
RC1: 'Review ESSD-2018-18', Anonymous Referee #1, 10 Aug 2018
-
EC1: 'Evaluation from 2nd reviewer', David Carlson, 12 Sep 2018
-
EC2: 'Options for ESSD-2018-18', David Carlson, 14 Sep 2018
Virginia M. Miori et al.
Virginia M. Miori et al.
Viewed
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
2,363 | 332 | 70 | 2,765 | 78 | 85 |
- HTML: 2,363
- PDF: 332
- XML: 70
- Total: 2,765
- BibTeX: 78
- EndNote: 85
Viewed (geographical distribution)
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1