Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)

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An Extraction and Analysis of Land Elevation and Coastal Area using Spatial Data Mining Techniques in DEMs

Authors
B. G. Kodge1, *
1School of Science, GITAM Deemed University, Hyderabad, TS, India
*Corresponding author. Email: kodgebg@gmail.com
Corresponding Author
B. G. Kodge
Available Online 10 August 2023.
DOI
10.2991/978-94-6463-196-8_37How to use a DOI?
Keywords
Elevation data; Sea coast area/cities/villages; Digital elevation model; Spatial data mining; Geographical Information System
ABSTRACT

The earth’s land surface is always changing its morphology and characteristics due to its inside and outside movements/activities like earthquakes, volcanic eruptions, tsunamis, cyclones, avalanches, asteroid hits, floods, land sliding, and so on. All these earth’s movements/activities are the natural phenomenon and not affected the earth’s atmosphere that much which is affecting more than the man made things or global warming. The main causes of increase in the earth’s temperature are the industrialization, deforestation, and pollutions which are generating more and more artificial disasters. The melting of land ice such as glaciers and ice sheets are the main reasons of increase in global sea levels and is become a big challenge to the people of cities/villages which are located on the sea coasts. Therefore an attempt is made in this paper to extract and analyse the land elevation data, elevation statistics, number of cities/villages located near the sea coasts in India within a specific distance and elevation classes using spatial data mining techniques in DEMs (Digital Elevation Models). The states wise extracted results of this paper are visualized geographically for better understanding and will be useful to plan, monitor and control the by local administrative of that concern province.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)
Series
Advances in Intelligent Systems Research
Publication Date
10 August 2023
ISBN
10.2991/978-94-6463-196-8_37
ISSN
1951-6851
DOI
10.2991/978-94-6463-196-8_37How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - B. G. Kodge
PY  - 2023
DA  - 2023/08/10
TI  - An Extraction and Analysis of Land Elevation and Coastal Area using Spatial Data Mining Techniques in DEMs
BT  - Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)
PB  - Atlantis Press
SP  - 485
EP  - 495
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-196-8_37
DO  - 10.2991/978-94-6463-196-8_37
ID  - Kodge2023
ER  -