Prasad S. Thenkabail

According to our database1, Prasad S. Thenkabail authored at least 28 papers between 2009 and 2020.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.



In proceedings 
PhD thesis 





Remote Sensing Open Access Journal of MDPI: Current Progress and Future Vision.
Remote. Sens., 2020

A meta-analysis of global crop water productivity of three leading world crops (wheat, corn, and rice) in the irrigated areas over three decades.
Int. J. Digit. Earth, 2020

A Bibliometric Profile of the <i>Remote Sensing Open Access Journal</i> Published by MDPI between 2009 and 2018.
Remote. Sens., 2019

<i>Remote Sensing</i> 10th Anniversary Best Paper Award.
Remote. Sens., 2019

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.
Int. J. Appl. Earth Obs. Geoinformation, 2019

Accuracies Achieved in Classifying Five Leading World Crop Types and their Growth Stages Using Optimal Earth Observing-1 Hyperion Hyperspectral Narrowbands on Google Earth Engine.
Remote. Sens., 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.
Remote. Sens., 2017

Spectral matching techniques (SMTs) and automated cropland classification algorithms (ACCAs) for mapping croplands of Australia using MODIS 250-m time-series (2000-2015) data.
Int. J. Digit. Earth, 2017

Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data.
Int. J. Digit. Earth, 2016

A Unified Cropland Layer at 250 m for Global Agriculture Monitoring.
Data, 2016

<i>Remote Sensing</i> Best Paper Award for the Year 2015.
Remote. Sens., 2015

Developing<i> in situ</i> Non-Destructive Estimates of Crop Biomass to Address Issues of Scale in Remote Sensing.
Remote. Sens., 2015

A support vector machine to identify irrigated crop types using time-series Landsat NDVI data.
Int. J. Appl. Earth Obs. Geoinformation, 2015

<i>Remote Sensing</i> Open Access Journal: Increasing Impact through Quality Publications.
Remote. Sens., 2014

<i>Remote Sensing</i> Best Paper Award for the Year 2014.
Remote. Sens., 2014

Global Land Cover Mapping: A Review and Uncertainty Analysis.
Remote. Sens., 2014

Selection of Hyperspectral Narrowbands (HNBs) and Composition of Hyperspectral Twoband Vegetation Indices (HVIs) for Biophysical Characterization and Discrimination of Crop Types Using Field Reflectance and Hyperion/EO-1 Data.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2013

<i>Remote Sensing</i> Best Paper Award 2013.
Remote. Sens., 2013

An Automated Cropland Classification Algorithm (ACCA) for Tajikistan by Combining Landsat, MODIS, and Secondary Data.
Remote. Sens., 2012

<i>Remote Sensing</i> Open Access Journal: Leading a New Paradigm in Publishing.
Remote. Sens., 2011

Mapping Irrigated Areas of Ghana Using Fusion of 30 m and 250 m Resolution Remote-Sensing Data.
Remote. Sens., 2011

Improving Water Productivity for Agriculture - Predicting and Preventing Crisis in Irrigated Water Use in a Changing Climate.
Proceedings of the IEEE Global Humanitarian Technology Conference, 2011

Earth Observing Data and Methods for Advancing Water Harvesting Technologies in the Semi-arid Rain-Fed Environments of India.
Proceedings of the IEEE Global Humanitarian Technology Conference, 2011

A Holistic View of Global Croplands and Their Water Use for Ensuring Global Food Security in the 21st Century through Advanced Remote Sensing and Non-remote Sensing Approaches.
Remote. Sens., 2010

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 Blue Revolution.
Remote. Sens., 2010

Decadal Variations in NDVI and Food Production in India.
Remote. Sens., 2010

Irrigated Area Maps and Statistics of India Using Remote Sensing and National Statistics.
Remote. Sens., 2009

A global map of rainfed cropland areas (GMRCA) at the end of last millennium using remote sensing.
Int. J. Appl. Earth Obs. Geoinformation, 2009