A Comparative Study of Spectral Indices for Surface Water Delineation Using Landsat 8 Images

Title

A Comparative Study of Spectral Indices for Surface Water Delineation Using Landsat 8 Images

Creator

Tv B.; Kn N.

Description

Surface water delineation is an important step in performing change detection studies on water bodies with the help of multispectral images. Commonly used techniques for surface water delineation from multispectral images are single band density slicing, spectral index based, machine learning based classification and spectral unmixing based methods. This paper presents a comparative study of commonly used spectral indices Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), Water Ratio Index (WRI), Normalized Difference Forest Index (NDFI), Enhanced water Index (EWI), Weighted Normalized Difference Water Index (WNDWI), Automated Water Extraction Index (AWEI), Tasseled Cap Water Index (TCW), Global Water Index (GWI)and Sum457 that were developed for water detection for their suitability and effectiveness when applied on Landsat 8 images. While all the above mentioned indices showed their usefulness in water detection, simpler and faster indices like GWI and Sum457 yielded comparable results to that of more complex ratios like EWI and WNDWI. 2019 IEEE.

Source

2019 International Conference on Data Science and Communication, IconDSC 2019

Date

2019-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

AWEI; EWI; GWI; MNDWI; NDFI; NDVI; NDWI; spectral index; Sum457; Surface water delineation; TCW; WNDWI; WRI

Coverage

Tv B., Dept. of Computer Science and Engineering, CHRIST, Deemed to be University, Bangalore, India; Kn N., Dept. of Civil Engineering, CHRIST, Deemed to be University, Bangalore, India

Rights

Restricted Access

Relation

ISBN: 978-153869319-3

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/IconDSC.2019.8816929

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