Evaluation of ForestPA for VHR RS image classification using spectral and superpixel-guided morphological profiles-Reference-Cited by-同舟云学术

Evaluation of ForestPA for VHR RS image classification using spectral and superpixel-guided morphological profiles

Published:2019-01-01 Issue:1 Volume:52 Page:107-121
ISSN:2279-7254
Container-title:European Journal of Remote Sensing
language:en
Short-container-title:European Journal of Remote Sensing

Author:

Samat Alim¹²^ORCID,Liu Sicong³^ORCID,Persello Claudio⁴^ORCID,Li Erzhu⁵^ORCID,Miao Zelang⁶,Abuduwaili Jilili¹²

Affiliation:

1. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, CAS, Urumqi, China

2. Research Center for Ecology and Environment of Central Asia, CAS, Urumqi, China

3. College of Surveying and Geoinformatics, Tongji University, Shanghai, China

4. Department of Earth Observation Science, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, The Netherlands

5. Department of Geographical Information Science, Jiangsu Normal University, Xuzhou, China

6. School of Geosciences & Info-Physics, Central South University, China

Funder

Chinese Academy of Sciences

National Natural Science Foundation of China

Youth Innovation Promotion Association of the Chinese Academy of Sciences

Publisher

Informa UK Limited

Subject

Applied Mathematics,Atmospheric Science,Computers in Earth Sciences,General Environmental Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/22797254.2019.1565418

Reference39 articles.

1. SLIC Superpixels Compared to State-of-the-Art Superpixel Methods

2. Forest PA : Constructing a decision forest by penalizing attributes used in previous trees

3. Random forest in remote sensing: A review of applications and future directions

4. Classification of hyperspectral data from urban areas based on extended morphological profiles

5. Geographic Object-Based Image Analysis – Towards a new paradigm

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