Spectral Complexity of Hyperspectral Images: A New Approach for Mangrove Classification

Patrick Osei Darko,Margaret Kalacska,Matthew E Fagan,J Pablo Arroyo-Mora

doi:10.3390/rs13132604

Abstract

Hyperspectral remote sensing across multiple spatio-temporal scales allows for mapping and monitoring mangrove habitats to support urgent conservation efforts. The use of hyperspectral imagery for assessing mangroves is less common than for terrestrial forest ecosystems. In this study, two well-known measures in statistical physics, Mean Information Gain (MIG) and Marginal Entropy (ME), have been adapted to high spatial resolution (2.5 m) full range (Visible-Shortwave-Infrared) airborne hyperspectral imagery. These two spectral complexity metrics describe the spatial heterogeneity and the aspatial heterogeneity of the reflectance. In this study, we compare MIG and ME with surface reflectance for mapping mangrove extent and species composition in the Sierpe mangroves in Costa Rica. The highest accuracy for separating mangroves from forest was achieved with visible-near infrared (VNIR) reflectance (98.8% overall accuracy), following by shortwave infrared (SWIR) MIG and ME (98%). Our results also show that MIG and ME can discriminate dominant mangrove species with higher accuracy than surface reflectance alone (e.g., MIG–VNIR = 93.6% vs. VNIR Reflectance = 89.7%).

Highlights

The spectral similarity improved with differences < 5% across the spectral range indicating an improvement in the spectral consistency (Figure 5c,d) across the two flight lines
The present study demonstrates the utility of spectral complexity metrics (MIG and Marginal Entropy (ME)), an information theory measure, derived from full range airborne hyperspectral imagery for mangrove classification
The spectral complexity metrics produced spectral signatures that can be associated with the mangrove and terrestrial forest

Summary

Introduction

Mangroves are characterized by a unique composition of tree and shrub species capable of thriving in saline conditions [4]. They are primarily found in coastal environments in the tropical and subtropical regions of the world, forming an interface between the sea and terrestrial environment [6,7]. They serve as an important ecological and economic resource providing many ecosystem services [8,9,10]. Mangroves serve both as a barrier that protects coastlines and as significant carbon sinks (blue carbon) [11], serving as a key natural climate solution to mitigate global warming [4,12]

Methods

Results

Discussion

Conclusion