APA (7th ed.) Citation

Teluguntla, P., Thenkabail, P. S., Oliphant, A., Xiong, J., Gumma, M. K., Congalton, R. G., . . . Huete, A. (2018). A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform. ISPRS journal of photogrammetry and remote sensing, 144, 325-340. https://doi.org/10.1016/j.isprsjprs.2018.07.017

Chicago Style (17th ed.) Citation

Teluguntla, Pardhasaradhi, Prasad S. Thenkabail, Adam Oliphant, Jun Xiong, Murali Krishna Gumma, Russell G. Congalton, Kamini Yadav, and Alfredo Huete. "A 30-m Landsat-derived Cropland Extent Product of Australia and China Using Random Forest Machine Learning Algorithm on Google Earth Engine Cloud Computing Platform." ISPRS Journal of Photogrammetry and Remote Sensing 144 (2018): 325-340. https://doi.org/10.1016/j.isprsjprs.2018.07.017.

MLA (9th ed.) Citation

Teluguntla, Pardhasaradhi, et al. "A 30-m Landsat-derived Cropland Extent Product of Australia and China Using Random Forest Machine Learning Algorithm on Google Earth Engine Cloud Computing Platform." ISPRS Journal of Photogrammetry and Remote Sensing, vol. 144, 2018, pp. 325-340, https://doi.org/10.1016/j.isprsjprs.2018.07.017.