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Updated: Dec 29, 2025

Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information
Published on: June 13, 2020
Evaluating sensitivity of hyperspectral indices for estimating mangrove chlorophyll in Middle Andaman Island, India
Rajee George1, Hitendra Padalia2, S K Sinha2
1Department of Environment and Forests, Port Blair, Andaman and Nicobar Islands 744102, India. george_rajee@yahoo.co.in.
Abstract:
Mangroves are the highly productive and extensive ecosystem in the tropical coasts. Chlorophyll is the key foliar determinant of mangrove productivity. Optical characteristics of mangrove markedly differ from land vegetation; hence, defining narrowband spectral indices most sensitive to mangrove chlorophyll is crucial, in view of their importance to the coastal environment and mounting biotic pressures. We assessed the sensitivity of a set of satellite hyperspectral remote sensing indices to mangrove canopy chlorophyll in Middle Andaman Island, India, and propose most robust spectral indices for mangrove chlorophyll estimation. We generated simple, modified simple, normalized difference vegetation, and non-linear indices from all possible two band combinations of EO-1 Hyperion bands in the 500-900 nm spectral range. The strength of correlation between each pair of spectral indices to mangrove chlorophyll was analyzed in 2D correlograms and validated using k-fold cross-validation technique. Results show that 549 nm, 559 nm (green) and 702 nm, 722 nm, 742 nm, and 763 nm (red-edge) wavelengths are the most sensitive to mangrove chlorophyll. We report performance of traditional chlorophyll indices and new indices with higher predictive capability for mangrove chlorophyll prediction. Simple ratio (559 nm/885 nm) offered the strongest correlation with mangrove chlorophyll (R2-0.75, RMSE-0.60, p < 0.05). Study findings will help researchers in deciding suitable chlorophyll indices for mangrove productivity and stress assessment. The best calibrated index was used to prepare mangrove chlorophyll spatial variability map of the study area.

