A comparative evaluation of state-of-the-art ensemble learning algorithms for land cover classification using WorldView-2, Sentinel-2 and ROSIS imagery-Reference-Cited by-同舟云学术

A comparative evaluation of state-of-the-art ensemble learning algorithms for land cover classification using WorldView-2, Sentinel-2 and ROSIS imagery

Published:2022-05 Issue:10 Volume:15 Page:
ISSN:1866-7511
Container-title:Arabian Journal of Geosciences
language:en
Short-container-title:Arab J Geosci

Author:

Colkesen Ismail^ORCID,Ozturk Muhammed Yusuf

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences,General Environmental Science

Link

https://link.springer.com/content/pdf/10.1007/s12517-022-10243-x.pdf

Reference98 articles.

1. Abdollahi A, Pradhan B, Shukla N, Chakraborty S, Alamri A (2020a) Deep learning approaches applied to remote sensing datasets for road extraction: a state-of-the-art review. Remote Sens 12(9):1444. https://doi.org/10.3390/rs12091444

2. Abdollahi A, Pradhan B, Gite S, Alamri A (2020b) Building footprint extraction from high resolution aerial images using generative adversarial network (GAN) architecture. IEEE Access 8:209517–209527. https://doi.org/10.1109/access.2020.3038225

3. Abdollahi A, Pradhan B (2021) Integrated technique of segmentation and classification methods with connected components analysis for road extraction from orthophoto images. Expert Syst Appl 176:114908. https://doi.org/10.1016/j.eswa.2021.114908

4. Akar O (2017) Mapping land use with using rotation forest algorithm from UAV images. Eur J Remote Sens 50(1):269–279. https://doi.org/10.1080/22797254.2017.1319252

5. Akar O, Gungor O (2012) Classification of multispectral images using random forest algorithm. J Geod Geoinf 1(2):105–112. https://doi.org/10.9733/jgg.241212.1

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