Proceedings of the Environmental Science and Technology International Conference (ESTIC 2021)

Feature Extraction Approach in Hyperspectral Data

Authors
Munkh-Erdene Altangerel1, *, Amarsaikhan Damdinsuren1, Enkhjargal Damdinsuren1, Odontuya Gendaram2, Jargaldalai Enkhtuya1
1Institute of Geography and Geoecology, Mongolian Academy of Sciences, Ulaanbaatar, Mongolia
2Mongolian University of Pharmaceutical Sciences, Ulaanbaatar, Mongolia
*Corresponding author. Email: munkherdenea@mas.ac.mn
Corresponding Author
Munkh-Erdene Altangerel
Available Online 1 November 2021.
DOI
https://doi.org/10.2991/aer.k.211029.019How to use a DOI?
Keywords
Feature extraction; hyperspectral data; principal component; meaningful features
Abstract

In general, feature extraction deals with the problem of finding the most informative, distinctive, and reduced set of features and improve the success of data processing. The features should contain information required to distinguish between classes, be insensitive to irrelevant variability in the input, and also be limited in number, to permit, efficient computation of the applied functions and to limit the amount of data required. In many cases, it is an important step in the solutions of many tasks aiming to extract the relevant information from the available large datasets. The aim of this study is to apply a feature extraction approach to a hyperspectral image and extract different features from the dataset and reduce its dimensionality into meaningful orthogonal features. The final analysis was performed in a test site situated in central Mongolia using 242 band Hyperion data. Overall, the study indicated that the Hyperion hyperspectral data could be effectively reduced into meaningful features through a feature extraction process.

Copyright
© 2021 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article under the CC BY-NC license.

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Volume Title
Proceedings of the Environmental Science and Technology International Conference (ESTIC 2021)
Series
Advances in Engineering Research
Publication Date
1 November 2021
ISBN
978-94-6239-446-9
ISSN
2352-5401
DOI
https://doi.org/10.2991/aer.k.211029.019How to use a DOI?
Copyright
© 2021 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Munkh-Erdene Altangerel
AU  - Amarsaikhan Damdinsuren
AU  - Enkhjargal Damdinsuren
AU  - Odontuya Gendaram
AU  - Jargaldalai Enkhtuya
PY  - 2021
DA  - 2021/11/01
TI  - Feature Extraction Approach in Hyperspectral Data
BT  - Proceedings of the Environmental Science and Technology International Conference (ESTIC 2021)
PB  - Atlantis Press
SP  - 102
EP  - 108
SN  - 2352-5401
UR  - https://doi.org/10.2991/aer.k.211029.019
DO  - https://doi.org/10.2991/aer.k.211029.019
ID  - Altangerel2021
ER  -