Land Cover Classification Using Remote Sensing and Supervised Convolutional Neural Networks-Reference-Cited by-同舟云学术

Land Cover Classification Using Remote Sensing and Supervised Convolutional Neural Networks

Published:2023-11-14 Issue: Volume: Page:13-24
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
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Author:

Perez-Guerra Jheison^ORCID,Herrera-Ruiz Veronica^ORCID,Gonzalez-Velez Juan Carlos^ORCID,Martinez-Vargas Juan David^ORCID,Torres-Madronero Maria Constanza^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-47372-2_2

Reference26 articles.

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2. Ritse, V., Basumatary, H., Kulnu, A.S., Dutta, G., Phukan, M.M., Hazarika, N.: Monitoring land use land cover changes in the Eastern Himalayan landscape of Nagaland, Northeast India. Environ. Monit. Assess. 192(11) (2020). https://doi.org/10.1007/s10661-020-08674-8

3. Talukdar, S., Pal, S.: Effects of damming on the hydrological regime of Punarbhaba river basin wetlands. Ecol. Eng. 135, 61–74 (2019). https://doi.org/10.1016/j.ecoleng.2019.05.014

4. Nguyen, K.A., Liou, Y.A.: Global mapping of eco-environmental vulnerability from human and nature disturbances. Sci. Total Environ. 664, 995–1004 (2019). https://doi.org/10.1016/j.scitotenv.2019.01.407

5. Hashem, N., Balakrishnan, P.: Change analysis of land use/land cover and modelling urban growth in Greater Doha, Qatar. Ann. GIS 21(3), 233–247 (2015). https://doi.org/10.1080/19475683.2014.992369

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