Implementation of Ensemble Deep Learning Coupled with Remote Sensing for the Quantitative Analysis of Changes in Arable Land Use in a Mining Area-Reference-Cited by-同舟云学术

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Implementation of Ensemble Deep Learning Coupled with Remote Sensing for the Quantitative Analysis of Changes in Arable Land Use in a Mining Area

Published:2021-09-22 Issue:11 Volume:49 Page:2875-2890
ISSN:0255-660X
Container-title:Journal of the Indian Society of Remote Sensing
language:en
Short-container-title:J Indian Soc Remote Sens

Author:

Ji Haowei^ORCID,Luo Xianqi

Funder

Key Technologies Research and Development Program

Publisher

Springer Science and Business Media LLC

Subject

Earth and Planetary Sciences (miscellaneous),Geography, Planning and Development

Link

https://link.springer.com/content/pdf/10.1007/s12524-021-01430-6.pdf

Reference35 articles.

1. Agarwal, R. (2017). Model Building To Investigate The Role Of Spatial Location In Classifying Satellite Image Using SVM, CART and mBACT: A case study. Journal of the Indian Society of Remote Sensing, 45(4), 569–578. https://doi.org/10.1007/s12524-016-0619-9

2. Araya-Lopez, R. A., Lopatin, J., Fassnacht, F. E., & Jaime Hernández, H. (2018). Monitoring Andean high altitude wetlands in central Chile with seasonal optical data: A comparison between Worldview-2 and Sentinel-2 imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 145(B), 213–224. https://doi.org/10.1016/j.isprsjprs.2018.04.001

3. Bai, X., Du, P., Guo, S., Zhang, P., Lin, C., Tang, P., & Zhang, C. (2019). Monitoring land cover change and disturbance of the mount wutai world cultural landscape heritage protected area, based on remote sensing time-series images from 1987 to 2018. Remote Sensing, 11(11), 1332. https://doi.org/10.3390/rs11111332

4. Chen, T. K., Qiu, C., Schmitt, M., Zhu, X. X., Sabel, C. E., & Prishchepov, A. V. (2020). Mapping horizontal and vertical urban densification in Denmark with Landsat time-series from 1985 to 2018: A semantic segmentation solution. Remote Sensing of Environment, 251, 2096. https://doi.org/10.1016/j.rse.2020.112096

5. Delgado-Martin, J., Juncosa-Rivera, R., et al. (2013). Four years of continuous monitoring of the Meirama end-pit lake and its impact in the definition of future uses. Environmental Science and Pollution Research, 20(11), 7520–7533. https://doi.org/10.1007/s11356-013-1618-9

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1. A comparative evaluation of deep convolutional neural network and deep neural network-based land use/land cover classifications of mining regions using fused multi-sensor satellite data;Advances in Space Research;2023-12

2. Cnns in land cover mapping with remote sensing imagery: a review and meta-analysis;International Journal of Remote Sensing;2023-09-25

3. Deep learning implementations in mining applications: a compact critical review;Artificial Intelligence Review;2023-05-11

4. Development of a deep convolutional neural network model for detection and delineation of coal mining regions;Earth Science Informatics;2023-02-09

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