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Xiong, J and Thenkabail, P S and Tilton, J and Gumma, M K and Teluguntla, P and Oliphant, A and Congalton, R and Yadav, K and Gorelick, N (2017) 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. Remote Sensing, 9(10) (1065). pp. 1-27. ISSN 2072-4292
Teluguntla, P and Thenkabail, P S and Xiong, J and Gumma, M K and Giri, C and Milesi, C and Ozdogan, M and Congalton, R G and Tilton, J (2015) Global Food Security Support Analysis Data (GFSAD) at Nominal 1 km (GCAD) Derived from Remote Sensing in Support of Food Security in the Twenty-First Century: Current Achievements and Future Possibilities. In: Land Resources Monitoring, Modeling, and Mapping with Remote Sensing. CRC Press, pp. 131-160. ISBN 9781482217957
Teluguntla, P and Thenkabail, P S and Xiong, J and Gumma, M K and Giri, C and Milesi, C and Ozdogan, M and Congalton, R and Tilton, J and Sankey, T T and Massey, R and Phalke, A and Yadav, K (2015) Global Cropland Area Database (GCAD) derived from Remote Sensing in Support of Food Security in the Twenty-first Century: Current Achievements and Future Possibilities. In: Land Resources Monitoring, Modeling, and Mapping with Remote Sensing (Remote Sensing Handbook). Taylor & Francis, Boca Raton, Florida, 01-45.
Teluguntla, P and Thenkabail, P S and Xiong, J and Gumma, M K and Giri, C and Milesi, C and Ozdogan, M and Congalton, R and Tilton, J and Sankey, T and Massey, R and Phalke, A and Yadav, K (2016) NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Global Food Security Support Analysis Data (GFSAD) Crop Mask 2010 Global 1 km V001. Monograph. NASA EOSDIS Land Processes DAAC, South Dakota, USA.
Xiong, J and Thenkabail, P S and Teluguntla, P and Oliphant, A and Congalton, R and Gumma, M K and Yadav, K and Massey, R and Tilton, J and Smith, C (2017) An Automated Crop Intensity Algorithm (ACIA) for global cropland intensity mapping at 30-m using multi-source time-series data and Google Earth Engine. In: 20th William T. Pecora Memorial Remote Sensing Symposium. Pecora 20 – “Observing a Changing Earth: Science for Decisions…Monitoring, Assessment, and Projection”, November 13-16, 2017, Sioux Falls, South Dakota, USA.
Teluguntla, P and Thenkabail, P S and Xiong, J and Oliphant, A and Gumma, M K and Congalton, R and Yadav, K and Massey, R and Phalke, A and Tilton, J and Smith, C (2017) Mapping cropland extent and areas of Australia at 30-m resolution using multi-year time-series Landsat data and Random Forest machine learning algorithm through Google Earth Engine (GEE) Cloud Computing. In: 20th William T. Pecora Memorial Remote Sensing Symposium. Pecora 20 – “Observing a Changing Earth: Science for Decisions…Monitoring, Assessment, and Projection”, November 14-16, 2017, Sioux Falls, South Dakota, USA.