APA (7th ed.) Citation

Gumma, M. K., Thenkabail, P. S., Teluguntla, P. G., Oliphant, A., Xiong, J., Giri, C., . . . Whitbread, A. M. (2020). Agricultural cropland extent and areas of South Asia derived using Landsat satellite 30-m time-series big-data using random forest machine learning algorithms on the Google Earth Engine cloud. GIScience and remote sensing, 57(3), 302-322. https://doi.org/10.1080/15481603.2019.1690780

Chicago Style (17th ed.) Citation

Gumma, Murali Krishna, Prasad S. Thenkabail, Pardhasaradhi G. Teluguntla, Adam Oliphant, Jun Xiong, Chandra Giri, Vineetha Pyla, Sreenath Dixit, and Anthony M. Whitbread. "Agricultural Cropland Extent and Areas of South Asia Derived Using Landsat Satellite 30-m Time-series Big-data Using Random Forest Machine Learning Algorithms on the Google Earth Engine Cloud." GIScience and Remote Sensing 57, no. 3 (2020): 302-322. https://doi.org/10.1080/15481603.2019.1690780.

MLA (9th ed.) Citation

Gumma, Murali Krishna, et al. "Agricultural Cropland Extent and Areas of South Asia Derived Using Landsat Satellite 30-m Time-series Big-data Using Random Forest Machine Learning Algorithms on the Google Earth Engine Cloud." GIScience and Remote Sensing, vol. 57, no. 3, 2020, pp. 302-322, https://doi.org/10.1080/15481603.2019.1690780.