Improved mapping of highland bamboo forests using Sentinel-2 time series and machine learning in Google Earth Engine-Reference-Cited by-同舟云学术

Improved mapping of highland bamboo forests using Sentinel-2 time series and machine learning in Google Earth Engine

Published:2024-01 Issue:1 Volume:39 Page:
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Yebeyen Dagnew¹,Hailu Binyam Tesfaw²³,Zewdie Worku⁴,Abera Temesgen³⁵,Sileshi Gudeta W.⁶,Getachew Melaku⁷,Nemomissa Sileshi⁶

Affiliation:

1. International Bamboo and Rattan Organization, East Africa Regional Office, Addis Ababa, Ethiopia

2. School of Earth Science, Addis Ababa University, Addis Ababa, Ethiopia

3. Department of Geosciences and Geography, University of Helsinki, Helsinki, Finland

4. Department of Remote Sensing, Space Science and Geospatial Institute, Addis Ababa, Ethiopia

5. Department of Environmental Informatics, Faculty of Geography, Philipps-Universität Marburg, Marburg, Germany

6. Department of Plant Biology and Biodiversity Management, Addis Ababa University, Addis Ababa, Ethiopia

7. Biometry, GIS and Database Directorate, Ethiopian Environment and Forest Research Institute, Addis Ababa, Ethiopia

Funder

Ethiopian Environment and Forest Research Institute

Addis Ababa University

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2024.2364680

Reference67 articles.

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3. Pro Machine Learning Algorithms

4. A review of vegetation indices

5. Bedru S. 2007. Land-use/land-cover changes in Andracha and Masha Woredas of Sheka zone, SNNP regional state. In: Maseresha F, editor. Forests of Sheka: ecological, social, legal and economic dimensions of recent land-use/land-cover changes, overview and synthesis. Multidisciplinary case studies on impact of land-use/land-cover changes, South West Ethiopia. Addis Ababa: Melca Mahiber, p. 21–56.