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

Application of Hyperspectral Data for Land Cover Classification

Authors
Amarsaikhan Damdinsuren1, Byambadolgor Batdorj1, *, Jargaldalai Enkhtuya1, Enkhjargal Damdinsuren1, Tsogzol Gurjav1
1Institute of Geography and Geoecology, Mongolian Academy of Sciences, Ulaanbaatar, Mongolia
*Corresponding author. Email: byambadolgorb@mas.ac.mn
Corresponding Author
Byambadolgor Batdorj
Available Online 1 November 2021.
DOI
10.2991/aer.k.211029.016How to use a DOI?
Keywords
Hyperspectral image; advanced classification; land cover
Abstract

At present, hyperspectral imaging techniques are widely used for a variety of different thematic applications, because they record a detailed spectrum of incoming radiation for every pixel and provide an invaluable source of information related to the physical nature of the Earth’s surface features. Generating accurate land cover maps using remote sensing (RS) datasets is one of the most important applications of digital image processing. For the generation of accurate maps, diverse supervised, unsupervised and hybrid classification methods can be applied. As hyperspectral images contain abundant spectral information, it makes them possible to distinguish various objects that would not be distinguishable by multispectral sensors. The aim of this study is to discriminate the land cover types in northern Mongolia using some advanced hyperspectral image classification techniques. As data sources, a Hyperion image of 2014 and some other ground truth information have been used. Overall, the research indicated that modern advanced hyperspectral data analysis methods could be successfully used for the land cover classification.

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
10.2991/aer.k.211029.016
ISSN
2352-5401
DOI
10.2991/aer.k.211029.016How 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  - Amarsaikhan Damdinsuren
AU  - Byambadolgor Batdorj
AU  - Jargaldalai Enkhtuya
AU  - Enkhjargal Damdinsuren
AU  - Tsogzol Gurjav
PY  - 2021
DA  - 2021/11/01
TI  - Application of Hyperspectral Data for Land Cover Classification
BT  - Proceedings of the Environmental Science and Technology International Conference (ESTIC 2021)
PB  - Atlantis Press
SP  - 86
EP  - 90
SN  - 2352-5401
UR  - https://doi.org/10.2991/aer.k.211029.016
DO  - 10.2991/aer.k.211029.016
ID  - Damdinsuren2021
ER  -