Utility of Field Spectroradiometer Data in Chlorophyll-α Estimation

Abstract

Abstract:We present here results supporting the use of Medium Resolution Imaging Spectrometer (MERIS)-based Near Infrared-Red algorithms for estimating chlorophyll-a (chl-a) concentration in complex coastal waters. The objective of the study was to test the potential of universal applicability of NIR-Red algorithms, calibrated with (a) radiometric measurements and in situ data from inland waters in Nebraska, (b) MERIS data, acquired over Azov Sea in Russia, and (c) data synthetically generated using a radiative transfer model, to estimate chl-a concentration in the Hudson/Raritan Estuary of New York/New Jersey. We used a set of in situ reflectance and water samples collected in the Hudson/Raritan Estuary of New York/New Jersey for this validation. The NIR-Red algorithms produced consistently accurate estimates of chl-a concentration, ranging from 3.9 mg m -3 to 26.3 mg m 3 , with the root mean square error (RMSE) below 2 mg m -3 . The algorithms do not need re-parameterization and it presents a strong case for the use of NIR-Red algorithms for real-time quantitative monitoring of Hudson/Raritan Estuary, and potentially other inland and coastal waters.

Estimation of chlorophyll-a concentrations in diverse water bodies using ratio-based NIR/Red indices

“…Moreover, Moses et al (2012a) investigated the performance of NIR-Red indices when applied to multi-temporal Airborne Imaging Spectrometer for Applications (AISA) data, and found that the spatial distribution of chlorophyll-a can be captured using NIR-Red indices even without atmospheric correction. Bagheri et al (2012) concluded that two-band NIR-Red algorithms had proven highly reliable for estimating chlorophyll-a concentration in turbid productive waters when applied to MERIS data in different geographic locations. Tao et al (2013) noticed that the ratio index NIR (708 nm)/Red (665 nm) estimated chlorophyll-a concentrations better than three or four band indices.…”

Long-Term Agroecosystem Research in the Central Mississippi River Basin: Hyperspectral Remote Sensing of Reservoir Water Quality

“…Additional model comparison research by Gurlin et al (2011) found that the accuracy of the three‐band and ratio models was very similar across a range of Chl‐ a contents from 4 to 100 μg L −1 . Bagheri et al (2012) established that these two models could be applied to water bodies other than those from which calibrations were derived without the need for reparameterization.…”