引用次数
引用: 1,980
H-指数: 15
I10-指数 : 16
出版物: 31
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 , Jun Xiong
ISPRS Journal of Photogrammetry and Remote Sensing 144 325 -340
300
2018
Mapping cropland fallow areas in myanmar to scale up sustainable intensification of pulse crops in the farming system
Murali Krishna Gumma , Prasad S Thenkabail , Kumara Charyulu Deevi , Irshad A Mohammed
Giscience & Remote Sensing 55 ( 6) 926 -949
14
2018
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 G Teluguntla , Adam Oliphant
Giscience & Remote Sensing 57 ( 3) 302 -322
88
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
Pardhasaradhi Teluguntla , Prasad S. Thenkabail , Jun Xiong , Murali Krishna Gumma
International Journal of Digital Earth 10 ( 9) 944 -977
40
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
Jun Xiong , Prasad S Thenkabail , James C Tilton , Murali K Gumma
Remote Sensing 9 ( 10) 1065
319
2017
New Generation Hyperspectral Data From DESIS Compared to High Spatial Resolution PlanetScope Data for Crop Type Classification
Itiya Aneece , Daniel Foley , Prasad Thenkabail , Adam Oliphant
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 15 7846 -7858
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 Google Earth Engine cloud
Prasad S Thenkabail , Pardhasaradhi G Teluguntla , Jun Xiong , Adam Oliphant
Professional Paper ( 1868)
34
2021
Hyperspectral narrowband data propel gigantic leap in the earth remote sensing
Prasad S Thenkabail , Itiya Aneece , Pardhasaradhi Teluguntla , Adam Oliphant
Photogrammetric Engineering & Remote Sensing 87 ( 7) 461 -467
5
2021
Global food-security-support-analysis data at 30-m resolution (GFSAD30) cropland-extent products—Download Analysis
Adam Oliphant , Prasad Thenkabail , Pardhasaradhi Teluguntla
Open-File Report ( 2022-1001)
4
2022
Crop Water Productivity from Cloud-Based Landsat Helps Assess California’s Water Savings
Daniel Foley , Prasad Thenkabail , Adam Oliphant , Itiya Aneece
Remote Sensing 15 ( 19) 4894 -4894
3
2023
New Generation and Old Generation Hyperspectral Remote Sensing Data and their Comparisons with Multispectral Data in the Study of Global Agriculture and Vegetation
Prasad S Thenkabail , Itiya Aneece , Pardhasaradhi Teluguntla , Adam Oliphant
IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium 5744 -5745
3
2022
Analysis of Spaceborne Hyperspectral Sensors and Tools for Classification and Characterization of Agricultural Crops
Itiya Aneece , Prasad Thenkabail , Daniel Foley , Adam Oliphant
AGU23
2023
Crop water productivity studies of leading world crops in California utilizing advanced multispectral remote sensing and modeling on the Google Earth Engine (GEE) cloud
Daniel Foley , Prasad Thenkabail , Adam Oliphant , Itiya Aneece
EGU General Assembly Conference Abstracts EGU22 -6517
2022
Character analysis of mining disturbance and reclamation trajectory in surface coal-mine area by time-series NDVI
Jing Li , Carl Zipper , Song Li , Patricia Donovan
Transactions of the Chinese Society of Agricultural Engineering 31 ( 16) 251 -257
24
2015
CropRef: Reference Datasets and techniques to improve global cropland mapping
Jun Xiong , Prasad S Thenkabail , Russell Congalton , K Yadav
2017
Mapping the agricultural croplands of the world using Petabyte-scale big-data analytics from Landsat 30m satellite sensor data, multiple machine learning algorithms, and Google Earth Engine (GEE) cloud computing
Prasad S Thenkabail , Pardhasaradhi G Teluguntla , Adam Oliphant , Itiya Aneece
Big Data VI: Learning, Analytics, and Applications 13036 130360C -130360C
2024
Analysis of Water and Nutrient loads using the Soil and Water Assessment Tool and Geographic Information Systems in Stroubles Creek Watershed
Adam Oliphant , Kevin Chu
Change 68.2302 -68.2302
2011
Mining disturbances in Virginia's southwestern coalfield, 1984-2011
Carl E. Zipper , Randolph H. Wynne , Patricia F. Donovan , Jing Li
2
2015
Synthesis and colour prediction of stable pigments from rice husk biomass
Zhaofeng Wang , Haoran Chen , Lily Xu , Susan Q. Xu
Green Materials 3 ( 1) 10 -14
17
2015
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 J. Oliphant , Prasad S. Thenkabail , Pardhasaradhi Teluguntla , Jun Xiong
International Journal of Applied Earth Observation and Geoinformation 81 110 -124
127
2019