Concepedia

Author

Adam Oliphant

United States Geological SurveyORCID

Also Known As

A. J. Oliphant, Adam J. Oliphant, Adam Oliphant, Oliphant, Adam, Prasad S. Thenkabail

38

Publications

2K

Citations

14

H-Index

45

Concepts

All Affiliations

United States Geological SurveyAstrogeology Science CenterBay Area Environmental Research InstituteInternational Crops Research Institute for the Semi-Arid TropicsWestern Geographic Science Center
AO

About

Adam Oliphant is an author at United States Geological Survey specializing in engineering, remote sensing, and earth science.

Top Concepts

#ConceptH-IndexPublicationsCitations

1

Engineering

10

10

1.5K

2

Social Sciences

4

4

1.1K

3

Public Health

2

2

174

4

Chemical Engineering

2

2

213

5

Chemistry

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1

19

Adam Oliphant

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17

Publications

1.9K

Citations

14

H-Index

YearCitations

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,

ISPRS Journal of Photogrammetry and Remote Sensing

2018

521

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,

Remote Sensing

2017

391

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,

International Journal of Applied Earth Observation and Geoinformation

2019

213

Extraction of Lignocellulose and Synthesis of Porous Silica Nanoparticles from Rice Husks: A Comprehensive Utilization of Rice Husk Biomass

Weixing Wang, Jarett C. Martin, Adam Oliphant,

ACS Sustainable Chemistry & Engineering

2012

194

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,

GIScience & Remote Sensing

2019

151

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 Teluguntla, Jun Xiong,

USGS professional paper

2021

82

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

Daniel J. Foley, Prasad S. Thenkabail, Itiya Aneece,

International Journal of Digital Earth

2019

79

Reconstructing disturbance history for an intensively mined region by time-series analysis of Landsat imagery

Jing Li, Carl E. Zipper, P Donovan,

Environmental Monitoring and Assessment

2015

60

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,

International Journal of Digital Earth

2017

60

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,

GIScience & Remote Sensing

2018

44

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