Evaluating the potential of sentinel-2, landsat-8, and irs satellite images in tree species classification of hyrcanian forest of iran using random forest-Reference-Cited by-同舟云学术

Evaluating the potential of sentinel-2, landsat-8, and irs satellite images in tree species classification of hyrcanian forest of iran using random forest

Published:2019-04-09 Issue:7 Volume:38 Page:615-628
ISSN:1054-9811
Container-title:Journal of Sustainable Forestry
language:en
Short-container-title:Journal of Sustainable Forestry

Author:

Soleimannejad Leila¹,Ullah Sami²³^ORCID,Abedi Roya⁴,Dees Matthias²⁵^ORCID,Koch Barbara²

Affiliation:

1. Department of Forestry, University of Guilan, Rasht, Iran

2. Chair of Remote Sensing and Landscape Information Systems, Institute of Forest Sciences, Faculty of Environment and Natural Resources, University of Freiburg, Freiburg, Germany

3. Department of Forestry, Shaheed Benazir Bhutto University, Sheringal, Dir Upper, Pakistan

4. Department of Forestry, Ahar Faculty of Agriculture and Natural Resource, University of Tabriz, Ahar, Iran

5. UNIQUE Forestry and Land Use GmbH, Freiburg, Germany

Publisher

Informa UK Limited

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Food Science,Forestry

Link

https://www.tandfonline.com/doi/pdf/10.1080/10549811.2019.1598443

Reference34 articles.

1. Prediction of Dominant Forest Tree Species Using QuickBird and Environmental Data

2. Exploiting machine learning algorithms for tree species classification in a semiarid woodland using RapidEye image

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