Atmospheric Correction and Vicarious Calibration of Oceansat-1 Ocean Color Monitor (OCM) Data in Coastal Case 2 Waters

Padmanava Dash,Nan Walker,Sherwin Ladner,Deepak Mishra,Eurico D’Sa

doi:10.3390/rs4061716

Abstract

The Ocean Color Monitor (OCM) provides radiance measurements in eight visible and near-infrared bands, similar to the Sea-viewing Wide Field-of-View Sensor (SeaWiFS) but with higher spatial resolution. For small- to moderate-sized coastal lakes and estuaries, where the 1 × 1 km spatial resolution of SeaWiFS is inadequate, the OCM provides a good alternative because of its higher spatial resolution (240 × 360 m) and an exact repeat coverage of every two days. This paper describes a detailed step-by-step atmospheric correction procedure for OCM data applicable to coastal Case 2 waters. This development was necessary as accurate results could not be obtained for our Case 2 water study area in coastal Louisiana with OCM data by using existing atmospheric correction software packages. In addition, since OCM-retrieved radiances were abnormally low in the blue wavelength region, a vicarious calibration procedure was developed. The results of our combined vicarious calibration and atmospheric correction procedure for OCM data were compared with the results from the SeaWiFS Data Analysis System (SeaDAS) software package outputs for SeaWiFS and OCM data. For Case 1 waters, our results matched closely with SeaDAS results. For Case 2 waters, our results demonstrated closure with in situ radiometric measurements, while SeaDAS produced negative normalized water leaving radiance (nLw) and remote sensing reflectance (Rrs). In summary, our procedure resulted in valid nLw and Rrs values for Case 2 waters using OCM data, providing a reliable method for retrieving useful nLw and Rrs values which can be used to develop ocean color algorithms for in-water substances (e.g., pigments, suspended sediments, chromophoric dissolved organic matter, etc.) at relatively high spatial resolution in regions where other software packages and sensors such as SeaWiFS and Moderate Resolution Imaging Spectrometer (MODIS) have proven unsuccessful. The method described here can be applied to other sensors such as OCM-2 or other Case 2 water areas.

Highlights

Satellite remote sensing provides a valuable tool for rapidly assessing the spatial variability of water quality parameters over synoptic scales [1]
To assess the accuracy of Lr estimation, the new code computed Lr were compared with SeaWiFS Data Analysis System (SeaDAS) provided Lr along Ocean Color Monitor (OCM) and Sea-viewing Wide Field-of-View Sensor (SeaWiFS) scan lines (Figures 4 and 5)
This paper presents a detailed methodology for the atmospheric correction of Oceansat-1 Ocean

Summary

Introduction

Satellite remote sensing provides a valuable tool for rapidly assessing the spatial variability of water quality parameters over synoptic scales [1]. Use of satellite remote sensing for monitoring small lakes and estuaries is a challenge due to the optical complexities of these Case 2 water bodies leading to atmospheric correction problems (―Case 1‖ and ―Case 2‖ defined in Morel and Prieur [2]). One such small lake is Lac des Allemands in Louisiana, USA, where high concentrations of cyanobacteria are known to occur in spring and summer [3,4,5]. Other ocean color sensors that have the required spatial resolution for studying smaller water bodies, lack frequent revisit cycles

Methods

Results

Conclusion