Title
Monitoring Nutrient Concentrations In Tampa Bay With Modis Images And Machine Learning Models
Keywords
coastal bay; genetic programming; MODIS; nutrient monitoring; Remote sensing; wastewater treatment
Abstract
This paper explores the spatiotemporal nutrient patterns in Tampa Bay, Florida with the aid of Moderate Resolution Imaging Spectroradiometer (MODIS) images and Genetic Programming (GP) models that are designed to link Total Phosphorus (TP) levels and remote sensing reflectance bands in aquatic environments. In-situ data were drawn from a local database to support the calibration and validation of the GP model. The GP models show the effective capacity to demonstrating the snapshots of spatiotemporal distributions of TP across the Bay, which helps to delineate the short-term seasonality effect and the global trend of TP in the coastal bay. The model output can provide informative reference for the establishment of contingency plans in treating nutrients-rich runoff. © 2013 IEEE.
Publication Date
8-14-2013
Publication Title
2013 10th IEEE International Conference on Networking, Sensing and Control, ICNSC 2013
Number of Pages
702-707
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/ICNSC.2013.6548824
Copyright Status
Unknown
Socpus ID
84881282093 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84881282093
STARS Citation
Chang, Ni Bin and Xuan, Zhemin, "Monitoring Nutrient Concentrations In Tampa Bay With Modis Images And Machine Learning Models" (2013). Scopus Export 2010-2014. 6093.
https://stars.library.ucf.edu/scopus2010/6093