| HYPERSPECTRAL REMOTE SENSING OF VEGETATION AND AGRICULTURAL CROPS Prasad S Thenkabail, Murali Krishna Gumma, Pardhasaradhi Teluguntla, Irshad ... PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING 80 (8), 697-709, 2014 | 919* | 2014 |
| Automated cropland mapping of continental Africa using Google Earth Engine cloud computing J Xiong, PS Thenkabail, MK Gumma, P Teluguntla, J Poehnelt, ... ISPRS Journal of Photogrammetry and Remote Sensing 126, 225-244, 2017 | 558 | 2017 |
| 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 P Teluguntla, P Thenkabail, A Oliphant, J Xiong, MK Gumma, ... ISPRS Journal of Photogrammetry and Remote Sensing 144, 325-340, 2018 | 503 | 2018 |
| 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 J Xiong, PS Thenkabail, JC Tilton, MK Gumma, P Teluguntla, A Oliphant, ... Remote Sensing 9 (10), 1065, 2017 | 440 | 2017 |
| 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 AJ Oliphant, PS Thenkabail, P Teluguntla, J Xiong, MK Gumma, ... International Journal of Applied Earth Observation and Geoinformation 81 …, 2019 | 219 | 2019 |
| Spectral matching techniques to determine historical land-use/land-cover (LULC) and irrigated areas using time-series 0.1-degree AVHRR Pathfinder datasets P Thenkabail, P GangadharaRao, T Biggs, M Krishna, H Turral Photogrammetric Engineering & Remote Sensing 73 (10), 1029-1040, 2007 | 211 | 2007 |
| Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data MK Gumma, PS Thenkabail, P Teluguntla, MN Rao, IA Mohammed, ... International Journal of Digital Earth 9 (10), 981-1003, 2016 | 177 | 2016 |
| Irrigated area mapping in heterogeneous landscapes with MODIS time series, ground truth and census data, Krishna Basin, India TW Biggs, PS Thenkabail, MK Gumma, CA Scott, GR Pardhasaradhi, ... International Journal of Remote Sensing 27 (19), 4245-4266, 2006 | 172 | 2006 |
| 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 … MK Gumma, PS Thenkabail, PG Teluguntla, A Oliphant, J Xiong, C Giri, ... GIScience & Remote Sensing 57 (3), 302-322, 2020 | 162 | 2020 |
| Global Food Security Support Analysis Data (GFSAD) at Nominal 4 1-km (GCAD) derived from Remote Sensing in Support of Food 5 Security in the Twenty-first Century: Current … P Teluguntla, PS Thenkabail, J Xiong, MK Gumma, C Giri, C Milesi, ... | 144* | 2015 |
| Water Scarcity Effects on Equitable Water Distribution and Land Use in a Major Irrigation Project—Case Study in India A Gaur, TW Biggs, MK Gumma, G Parthasaradhi, H Turral Journal of Irrigation and Drainage Engineering 134 (1), 26-35, 2008 | 96 | 2008 |
| Closing of the Krishna Basin: irrigation, streamflow depletion and macroscale hydrology T Biggs, A Gaur, C Scott, P Thenkabail, P Gangadhara Rao, MK Gumma, ... IWMI, 2007 | 95 | 2007 |
| Global Croplands and their Importance for Water and Food Security in the Twenty-first Century: Towards an Ever Green Revolution that Combines a Second Green Revolution with a … PS Thenkabail Remote Sensing 2 (9), 2305-2312, 2010 | 83 | 2010 |
| A meta-analysis of global crop water productivity of three leading world crops (wheat, corn, and rice) in the irrigated areas over three decades DJ Foley, PS Thenkabail, IP Aneece, PG Teluguntla, AJ Oliphant International Journal of Digital Earth 13 (8), 939-975, 2020 | 82 | 2020 |
| Spectral matching techniques (SMTs) and automated cropland classification algorithms (ACCAs) for mapping croplands of Australia using MODIS 250-m time-series (2000–2015) data P Teluguntla, PS Thenkabail, J Xiong, MK Gumma, RG Congalton, ... International Journal of Digital Earth, 1-34, 2017 | 80 | 2017 |
| NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Global Food Security-support Analysis Data (GFSAD) Cropland Extent 2015 Southeast Asia 30 m V001 AJ Oliphant, PS Thenkabail, P Teluguntla, J Xiong, RG Congalton, ... NASA EOSDIS Land Processes DAAC, 2017 | 67 | 2017 |
| NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Global Food Security-support Analysis Data (GFSAD) Cropland Extent 2015 South Asia … MK Gumma, PS Thenkabail, P Teluguntla, A Oliphant, J Xiong, ... NASA EOSDIS Land Processes DAAC, 2017 | 67 | 2017 |
| Mapping cropland fallow areas in myanmar to scale up sustainable intensification of pulse crops in the farming system MK Gumma, PS Thenkabail, KC Deevi, IA Mohammed, P Teluguntla, ... GIScience & Remote Sensing 55 (6), 926-949, 2018 | 54 | 2018 |
| Multiple agricultural cropland products of South Asia developed using Landsat-8 30 m and MODIS 250 m data using machine learning on the Google Earth Engine (GEE) cloud and … MK Gumma, PS Thenkabail, P Panjala, P Teluguntla, T Yamano, ... GIScience & Remote Sensing 59 (1), 1048-1077, 2022 | 50 | 2022 |
| 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 … PS Thenkabail, PG Teluguntla, J Xiong, A Oliphant, RG Congalton, ... Professional Paper, 2021 | 50 | 2021 |
Prasad ThenkabailSenior Scientist (ST) the United States Geological Survey (USGS)Verified email at usgs.gov
