"Satellite Estimation of Chlorophyll-a Using Moderate Resolution Imagin" by Mohd Manzar Abbas, Assefa M. Melesse et al.

Department of Earth and Environment

Title

Satellite Estimation of Chlorophyll-a Using Moderate Resolution Imaging Spectroradiometer (MODIS) Sensor in Shallow Coastal Water Bodies: Validation and Improvement

Authors

Mohd Manzar Abbas, Department of Earth and Environment, Florida International University
Assefa M. Melesse, Department of Earth and Environment, Florida International UniversityFollow
Leanord J. Scinto, Department of Earth and Environment, Florida International UniversityFollow
J S. Rehage, Department of Earth and Environment, Florida International UniversityFollow

Date of this Version

8-6-2019

Document Type

Article

Abstract

The size and distribution of Phytoplankton populations are indicators of the ecological status of a water body. The chlorophyll-a (Chl-a) concentration is estimated as a proxy for the distribution of phytoplankton biomass. Remote sensing is the only practical method for the synoptic assessment of Chl-a at large spatial and temporal scales. Long-term records of ocean color data from the MODIS Aqua Sensor have proven inadequate to assess Chl-a due to the lack of a robust ocean color algorithm. Chl-a estimation in shallow and coastal water bodies has been a challenge and existing operational algorithms are only suitable for deeper water bodies. In this study, the Ocean Color 3M (OC3M) derived Chl-a concentrations were compared with observed data to assess the performance of the OC3M algorithm. Subsequently, a regression analysis between in situ Chl-a and remote sensing reflectance was performed to obtain a green-red band algorithm for coastal (case 2) water. The OC3M algorithm yielded an accurate estimate of Chl-a for deep ocean (case 1) water (RMSE = 0.007, r² = 0.518, p < 0.001), but failed to perform well in the coastal (case 2) water of Chesapeake Bay (RMSE = 23.217, r² = 0.009, p = 0.356). The algorithm developed in this study predicted Chl-a more accurately in Chesapeake Bay (RMSE = 4.924, r² = 0.444, p < 0.001) than the OC3M algorithm. The study indicates a maximum band ratio formulation using green and red bands could improve the satellite estimation of Chl-a in coastal waters.

Comments

Originally in Water.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 License.

Recommended Citation

Abbas, Mohd Manzar; Melesse, Assefa M.; Scinto, Leanord J.; and Rehage, J S., "Satellite Estimation of Chlorophyll-a Using Moderate Resolution Imaging Spectroradiometer (MODIS) Sensor in Shallow Coastal Water Bodies: Validation and Improvement" (2019). Department of Earth and Environment. 46.
https://digitalcommons.fiu.edu/earth_environment_fac/46

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DOI

10.3390/w11081621

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