APA (7th ed.) Citation

Ge, G., Shi, Z., Zhu, Y., Yang, X., & Hao, Y. (2020). Land use/cover classification in an arid desert-oasis mosaic landscape of China using remote sensed imagery: Performance assessment of four machine learning algorithms. Global ecology and conservation, 22, e00971. https://doi.org/10.1016/j.gecco.2020.e00971

Chicago Style (17th ed.) Citation

Ge, Genbatu, Zhongjie Shi, Yuanjun Zhu, Xiaohui Yang, and Yuguang Hao. "Land Use/cover Classification in an Arid Desert-oasis Mosaic Landscape of China Using Remote Sensed Imagery: Performance Assessment of Four Machine Learning Algorithms." Global Ecology and Conservation 22 (2020): e00971. https://doi.org/10.1016/j.gecco.2020.e00971.

MLA (9th ed.) Citation

Ge, Genbatu, et al. "Land Use/cover Classification in an Arid Desert-oasis Mosaic Landscape of China Using Remote Sensed Imagery: Performance Assessment of Four Machine Learning Algorithms." Global Ecology and Conservation, vol. 22, 2020, p. e00971, https://doi.org/10.1016/j.gecco.2020.e00971.