Random Forest Classification for Calculating the Area of Mangrove Forest in Benoa Bali Bay

I Gede Arta Wibawa; I Ketut Gede Suhartana; Anak Agung Gde Raka Dalem

doi:10.2991/978-94-6463-413-6_22

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Random Forest Classification for Calculating the Area of Mangrove Forest in Benoa Bali Bay

Authors

I Gede Arta Wibawa¹^{, *}, I Ketut Gede Suhartana¹, Anak Agung Gde Raka Dalem¹

¹Udayana University, Kampus Unud Road Bukit Jimbaran Bali, Denpasar, Indonesia

^*Corresponding author. Email: gede.arta@unud.ac.id

Corresponding Author

I Gede Arta Wibawa

Available Online 13 May 2024.

DOI: 10.2991/978-94-6463-413-6_22 How to use a DOI?
Keywords: Benoa Bay; Mangrove; Random Forest
Abstract: The Benoa Bay area in Bali is an interesting area to study because of its influence on the community’s economy and the presence of mangrove forests in overcoming the issue of climate change, especially in Bali. The extent of mangrove forests in the bay of the continent of Bali needs to always be observed considering their great influence on life. This research aims to provide information on the extent of mangrove plants found in Benoa Bay, Bali. The technique used is to classify satellite images using the random forest method so that the area of mangrove plants in Benoa Bay, Bali, can be measured. The steps taken in this research are: Image acquisition, pre-processing, pixel classification using random forest and measuring the area of mangrove plant objects in Benoa Bay, Bali. The area of mangrove forest obtained was 1,230.4 hectares. There was a decrease in area compared to previous research of around 143.1 hectares..
Copyright: © 2024 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 Applied Mathematics, Statistics, and Computing (ICAMSAC 2023)
Series: Advances in Computer Science Research
Publication Date: 13 May 2024
ISBN: 10.2991/978-94-6463-413-6_22
ISSN: 2352-538X
DOI: 10.2991/978-94-6463-413-6_22 How to use a DOI?
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

ris enw bib

TY  - CONF
AU  - I Gede Arta Wibawa
AU  - I Ketut Gede Suhartana
AU  - Anak Agung Gde Raka Dalem
PY  - 2024
DA  - 2024/05/13
TI  - Random Forest Classification for Calculating the Area of Mangrove Forest in Benoa Bali Bay
BT  - Proceedings of the First International Conference on Applied Mathematics, Statistics, and Computing (ICAMSAC 2023)
PB  - Atlantis Press
SP  - 221
EP  - 227
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-413-6_22
DO  - 10.2991/978-94-6463-413-6_22
ID  - Wibawa2024
ER  -

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