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Species-level classification of mangrove forest using AVIRIS-NG hyperspectral imagery.

Authors :
Paramanik, Somnath
Deep, Nikhil Raj
Behera, Mukunda Dev
Bhattacharya, Bimal Kumar
Dash, Jadunandan
Source :
Remote Sensing Letters. May2023, Vol. 14 Issue 5, p522-533. 12p.
Publication Year :
2023

Abstract

Species-level classification of mangroves provides important inputs for conservation, rehabilitation and understanding of ecosystem functions. The hyperspectral sensor, Airborne Visible InfraRed Imaging Spectrometer-New Generation (AVIRIS-NG), holds promises for species-level discrimination by virtue of its coverage across a wider spectrum at very high spatial resolution. Using the continuum removal (CR) technique and absorption band depth (ABD), this study applied Random Forest (RF) model to classify the distribution of three species (Heritiera fomes, Excoecaria agallocha and Avicennia officinalis) and two of their combinations (Heritiera fomes-Excoecaria agallocha and Avicennia officinalis-Excoecaria agallocha). The classified map demonstrated good accuracy (overall accuracy = 88%; kappa coefficient = 0.84) using ABD as an independent variable. The important wavelengths (972, 1172, 1177 nm) identified for mangrove species discrimination correspond to water absorption bands. This characteristic may be replicated for species-level classification of other mangrove forests with similar species. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
2150704X
Volume :
14
Issue :
5
Database :
Academic Search Index
Journal :
Remote Sensing Letters
Publication Type :
Academic Journal
Accession number :
164084001
Full Text :
https://doi.org/10.1080/2150704X.2023.2215945