Pardhasaradhi Teluguntla

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

Pardhasaradhi Teluguntla, Prasad S. Thenkabail, Adam Oliphant et al. · ISPRS Journal of Photogrammetry and Remote Sensing · 2018 · 540 citations · Full text

Natural Sciences, Earth Sciences, Geoinformatics +17

Automated cropland mapping of continental Africa using Google Earth Engine cloud computing

Jun Xiong, Prasad S. Thenkabail, Murali Krishna Gumma et al. · ISPRS Journal of Photogrammetry and Remote Sensing · 2017 · 489 citations · Full text

Natural Sciences, Crop Sciences, Earth Sciences +17

Nominal 30-m Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine

Jun Xiong, Prasad S. Thenkabail, James C. Tilton et al. · Remote Sensing · 2017 · 398 citations · Full text

Agriculture, Agronomy, Precision Agriculture +13

Mapping cropland extent of Southeast and Northeast Asia using multi-year time-series Landsat 30-m data using a random forest classifier on the Google Earth Engine Cloud

Adam Oliphant, Prasad S. Thenkabail, Pardhasaradhi Teluguntla et al. · International Journal of Applied Earth Observation and Geoinformation · 2019 · 217 citations · Full text

Social Sciences, Geography, Physical Geography +16

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

Murali Krishna Gumma, Prasad S. Thenkabail, Pardhasaradhi Teluguntla et al. · GIScience & Remote Sensing · 2019 · 158 citations · Full text

Natural Sciences, Geoinformatics, Land-use Planning +17