Improving the accuracy of mangrove forest mapping using sentinel image and developed classification algorithm based on machine learning-Reference-Cited by-同舟云学术

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Improving the accuracy of mangrove forest mapping using sentinel image and developed classification algorithm based on machine learning

Published:2024-04-08 Issue: Volume: Page:1-27
ISSN:1449-8596
Container-title:Journal of Spatial Science
language:en
Short-container-title:Journal of Spatial Science

Author:

Purwanto Anang Dwi¹²^ORCID,Wikantika Ketut¹^ORCID,Deliar Albertus¹^ORCID,Darmawan Soni¹³^ORCID,Harto Agung Budi¹^ORCID,Khomarudin Muhammad Rokhis²^ORCID,Ardli Erwin Riyanto⁴^ORCID

Affiliation:

1. Geodesy and Geomatics Engineering, Faculty of Earth Science and Technology, Bandung Institute of Technology, Bandung, Indonesia

2. National Research and Innovation Agency (BRIN), Jakarta, Indonesia

3. Geodesy Engineering, Faculty of Civil Engineering and Planning, Institut Teknologi Nasional Bandung, Bandung, Indonesia

4. Faculty of Biology, Universitas Jenderal Soedirman, Purwokerto, Indonesia

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/14498596.2024.2337747

Reference92 articles.

1. A COMPARATIVE ASSESSMENT OF REMOTE SENSING IMAGING TECHNIQUES: OPTICAL, SAR AND LIDAR

2. Process Variable Importance Analysis by Use of Random Forests in a Shapley Regression Framework

3. Mangrove Damage Evaluation using Two Species of Acanthus as a Biomonitoring Agent, Case Study: Segara Anakan Cilacap, Indonesia

4. Land Cover Changes and Impacts of Massive Siltation on the Mangrove Segara Anakan Lagoon System, Cilacap Indonesia

5. MODELLING ABOVE GROUND BIOMASS OF MANGROVE FOREST USING SENTINEL-1 IMAGERY

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