Report for: Global cropland-extent product at 30-m resolution (GCEP30) derived from Landsat satellite time-series data for the year 2015 using multiple machine-learning algorithms on Google Earth Engine cloud

Title	Global cropland-extent product at 30-m resolution (GCEP30) derived from Landsat satellite time-series data for the year 2015 using multiple machine-learning algorithms on Google Earth Engine cloud
Published by	US Geological Survey, January 2021
DOI	10.3133/pp1868
Authors	Thenkabail, Prasad S., Teluguntla, Pardhasaradhi G., Xiong, Jun, Oliphant, Adam, Congalton, Russell G., Ozdogan, Mutlu, Gumma, Murali Krishna, Tilton, James C., Giri, Chandra, Milesi, Cristina, Phalke, Aparna, Massey, Richard, Yadav, Kamini, Sankey, Temuulen, Zhong, Ying, Aneece, Itiya, Foley, Daniel

X Demographics

The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.

Type	Count	As %
Members of the public	7	78%
Scientists	2	22%

Mendeley readers

The data shown below were compiled from readership statistics for 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Country	Count	As %
Unknown	73	100%

Readers by professional status	Count	As %
Student > Ph. D. Student	14	19%
Researcher	11	15%
Unspecified	5	7%
Student > Bachelor	4	5%
Student > Doctoral Student	4	5%
Other	9	12%
Unknown	26	36%

Readers by discipline	Count	As %
Environmental Science	9	12%
Agricultural and Biological Sciences	7	10%
Engineering	7	10%
Earth and Planetary Sciences	6	8%
Unspecified	5	7%
Other	9	12%
Unknown	30	41%

Global cropland-extent product at 30-m resolution (GCEP30) derived from Landsat satellite time-series data for the year 2015 using multiple machine-learning algorithms on Google Earth Engine cloud