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Extracting Land-Cover Information from Landsat Satellite Images by the Decision-Tree Model to Generate a Land-Use Map in Ba Tri District, Ben Tre Province

Received: Jul. 31, 2023    Accepted: Aug. 22, 2023    Published: Aug. 31, 2023
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Abstract

Monitoring the distribution of land-cover change plays a very important role in making decisions about land-use activities of the environmental management. Ben Tre is a new developing city in the Mekong Delta, an average topographical elevation of which is less than five meters across the province. This is one of the areas that is quite sensitive to fluctuations in mean sea level rise. In the current context, the effects of global climate change on the natural environment have become more and more obvious, especially for coastal plain areas with relatively low terrain elevation. Therefore, it is necessary to generate and update constantly land-cover or land-use maps for coastal plain areas such as Ben Tre province. Based on the land-cover or land-use maps produced over many stages, environmental managers could monitor the changing directions of the distribution of land-cover and then make sound and rational decisions about land-use activities. The main purpose of this topic is to study and build a decision tree model which can extract the real land-cover information from Landsat images in the most effective way to generate a land-cover or land-use map. Thereby, it is possible to reduce the costs of field trips during the mapping process. Research results show that the accuracy of modelling interpretation on different objects ranges from 73% to 97%. The average accuracy of the prediction results across the region reached 86.7%.

DOI 10.11648/j.rd.20230403.15
Published in Research & Development ( Volume 4, Issue 3, September 2023 )
Page(s) 102-110
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Land-Cover, Land-Use, Landsat Images, Ba Tri, Decision Tree

References
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Cite This Article
  • APA Style

    Thi To Ngan Nguyen, Tran Hoai Hieu Truong, Thi Phuong Uyen Ngo, Thi Lan Thi Nguyen, Kim Phuong Lieu. (2023). Extracting Land-Cover Information from Landsat Satellite Images by the Decision-Tree Model to Generate a Land-Use Map in Ba Tri District, Ben Tre Province. Research & Development, 4(3), 102-110. https://doi.org/10.11648/j.rd.20230403.15

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    ACS Style

    Thi To Ngan Nguyen; Tran Hoai Hieu Truong; Thi Phuong Uyen Ngo; Thi Lan Thi Nguyen; Kim Phuong Lieu. Extracting Land-Cover Information from Landsat Satellite Images by the Decision-Tree Model to Generate a Land-Use Map in Ba Tri District, Ben Tre Province. Res. Dev. 2023, 4(3), 102-110. doi: 10.11648/j.rd.20230403.15

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    AMA Style

    Thi To Ngan Nguyen, Tran Hoai Hieu Truong, Thi Phuong Uyen Ngo, Thi Lan Thi Nguyen, Kim Phuong Lieu. Extracting Land-Cover Information from Landsat Satellite Images by the Decision-Tree Model to Generate a Land-Use Map in Ba Tri District, Ben Tre Province. Res Dev. 2023;4(3):102-110. doi: 10.11648/j.rd.20230403.15

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  • @article{10.11648/j.rd.20230403.15,
      author = {Thi To Ngan Nguyen and Tran Hoai Hieu Truong and Thi Phuong Uyen Ngo and Thi Lan Thi Nguyen and Kim Phuong Lieu},
      title = {Extracting Land-Cover Information from Landsat Satellite Images by the Decision-Tree Model to Generate a Land-Use Map in Ba Tri District, Ben Tre Province},
      journal = {Research & Development},
      volume = {4},
      number = {3},
      pages = {102-110},
      doi = {10.11648/j.rd.20230403.15},
      url = {https://doi.org/10.11648/j.rd.20230403.15},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.rd.20230403.15},
      abstract = {Monitoring the distribution of land-cover change plays a very important role in making decisions about land-use activities of the environmental management. Ben Tre is a new developing city in the Mekong Delta, an average topographical elevation of which is less than five meters across the province. This is one of the areas that is quite sensitive to fluctuations in mean sea level rise. In the current context, the effects of global climate change on the natural environment have become more and more obvious, especially for coastal plain areas with relatively low terrain elevation. Therefore, it is necessary to generate and update constantly land-cover or land-use maps for coastal plain areas such as Ben Tre province. Based on the land-cover or land-use maps produced over many stages, environmental managers could monitor the changing directions of the distribution of land-cover and then make sound and rational decisions about land-use activities. The main purpose of this topic is to study and build a decision tree model which can extract the real land-cover information from Landsat images in the most effective way to generate a land-cover or land-use map. Thereby, it is possible to reduce the costs of field trips during the mapping process. Research results show that the accuracy of modelling interpretation on different objects ranges from 73% to 97%. The average accuracy of the prediction results across the region reached 86.7%.},
     year = {2023}
    }
    

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  • TY  - JOUR
    T1  - Extracting Land-Cover Information from Landsat Satellite Images by the Decision-Tree Model to Generate a Land-Use Map in Ba Tri District, Ben Tre Province
    AU  - Thi To Ngan Nguyen
    AU  - Tran Hoai Hieu Truong
    AU  - Thi Phuong Uyen Ngo
    AU  - Thi Lan Thi Nguyen
    AU  - Kim Phuong Lieu
    Y1  - 2023/08/31
    PY  - 2023
    N1  - https://doi.org/10.11648/j.rd.20230403.15
    DO  - 10.11648/j.rd.20230403.15
    T2  - Research & Development
    JF  - Research & Development
    JO  - Research & Development
    SP  - 102
    EP  - 110
    PB  - Science Publishing Group
    SN  - 2994-7057
    UR  - https://doi.org/10.11648/j.rd.20230403.15
    AB  - Monitoring the distribution of land-cover change plays a very important role in making decisions about land-use activities of the environmental management. Ben Tre is a new developing city in the Mekong Delta, an average topographical elevation of which is less than five meters across the province. This is one of the areas that is quite sensitive to fluctuations in mean sea level rise. In the current context, the effects of global climate change on the natural environment have become more and more obvious, especially for coastal plain areas with relatively low terrain elevation. Therefore, it is necessary to generate and update constantly land-cover or land-use maps for coastal plain areas such as Ben Tre province. Based on the land-cover or land-use maps produced over many stages, environmental managers could monitor the changing directions of the distribution of land-cover and then make sound and rational decisions about land-use activities. The main purpose of this topic is to study and build a decision tree model which can extract the real land-cover information from Landsat images in the most effective way to generate a land-cover or land-use map. Thereby, it is possible to reduce the costs of field trips during the mapping process. Research results show that the accuracy of modelling interpretation on different objects ranges from 73% to 97%. The average accuracy of the prediction results across the region reached 86.7%.
    VL  - 4
    IS  - 3
    ER  - 

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Author Information
  • Faculty of Geology, VNUHCM-University of Science, Ho Chi Minh City, Vietnam

  • Faculty of Geology, VNUHCM-University of Science, Ho Chi Minh City, Vietnam; M. I Foundation Solutions Co. LTD., Borey Piphop Thmey Chamkar Doung 3, Phompenh, Cambodia

  • Faculty of Geology, VNUHCM-University of Science, Ho Chi Minh City, Vietnam

  • Faculty of Biology, VNUHCM-University of Science, Ho Chi Minh City, Vietnam

  • Ho Chi Minh City Institute of Resources Geography, Tay Nguyen Institute of Scientific Research, Vietnam Academy of Science and Technology, Ho Chi Minh City, Vietnam

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