Evaluation of the Use of Hyperspectral Vegetation Indices for Estimating Mangrove Leaf Area Index in Middle Andaman Island, India

Abstract

ABSTRACTMangroves are highly productive ecosystems of the coastal environment in tropics and subtropics. The Leaf Area Index (LAI) is a key structural variable of the canopy, useful for estimating the primary productivity of vegetation including mangroves. We evaluated the sensitivity of narrowband spectral indices viz., Simple Ratio, Normalized Difference Vegetation Index, Soil-Adjusted Vegetation Index and Non-Linear Vegetation Index to mangrove LAI, and thereby propose the optimal bands and spectral indices for mangrove LAI estimation. The study was carried out using EO (Earth Observation)-1 Hyperion data in the Middle Andaman Island, situated in the Bay of Bengal, India. We constructed simple, normalized and non-linear band indices from all possible band pairs in the Hyperion image, and correlated them with mangrove LAI, and empirical relationships were validated through a k-fold cross-validation. The 2-D correlation plot analysis indicates that wavebands in Shortwave Infra-Red and Near Infra-Red regions, have a high potential for mangrove LAI estimation. The wavebands at 834 nm, 844 nm, 864 nm, 1034 nm, 1185 nm, 1276 nm, 1296 nm, 1629 nm and 1679 nm were the most sensitive to mangrove LAI. The non-linear vegetation indices performed better than linear indices in predicting LAI of mangrove. The identified indices are expected to improve quantification of spatial variability of mangrove LAI.