Heuristic Approach to Temporal Assignments of Spatial Grid Points for Vegetation Monitoring | IGI Global Scientific Publishing
Welcome to the InfoSci Platform
Heuristic Approach to Temporal Assignments of Spatial Grid Points for Vegetation Monitoring

Heuristic Approach to Temporal Assignments of Spatial Grid Points for Vegetation Monitoring

Virginia M. Miori (Saint Joseph's University, Philadelphia, USA), Nicolle Clements (Saint Joseph's University, Philadelphia, USA), and Brian W. Segulin (RoviSys, Aurora, USA)
Copyright: © 2019 |Volume: 10 |Issue: 3 |Pages: 19
ISSN: 1947-8569|EISSN: 1947-8577|EISBN13: 9781522565741|DOI: 10.4018/IJSDS.2019070101
Cite Article Cite Article

MLA

Miori, Virginia M., et al. "Heuristic Approach to Temporal Assignments of Spatial Grid Points for Vegetation Monitoring." IJSDS vol.10, no.3 2019: pp.1-19. https://doi.org/10.4018/IJSDS.2019070101

APA

Miori, V. M., Clements, N., & Segulin, B. W. (2019). Heuristic Approach to Temporal Assignments of Spatial Grid Points for Vegetation Monitoring. International Journal of Strategic Decision Sciences (IJSDS), 10(3), 1-19. https://doi.org/10.4018/IJSDS.2019070101

Chicago

Miori, Virginia M., Nicolle Clements, and Brian W. Segulin. "Heuristic Approach to Temporal Assignments of Spatial Grid Points for Vegetation Monitoring," International Journal of Strategic Decision Sciences (IJSDS) 10, no.3: 1-19. https://doi.org/10.4018/IJSDS.2019070101

Export Reference

Mendeley
Favorite Full-Issue Download

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 article 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.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global Scientific Publishing bookstore.