USGS Research Geographer Dr. Prasad Thenkabail and field assistant Sam Chaiya record the location and growth stage of a large rice paddy with a tablet in Na Yai Am District, Chanthaburi Province, Thailand.
Adam J. Oliphant
(He/him)Adam Oliphant is a geographer with the USGS based in Flagstaff Arizona.
He is part of the Western Geographic Science Center and specializes in using remote sensing to map vegetation over countries and continents. Adam recently finished mapping cropland extent across all of Southeast and Northeast Asia using Landsat 7&8 as part of the Global Food Security-support Analysis Data at 30m (GFSAD30) project.
Current research focused on mapping crop type and cropland fallows in the United States and integrating NASA/USGS satellite sensors with satellite systems from ESA including Sentinel 1&2. Adam has an interest in Citizen Science and community participation in the collection, analysis, and dissemination of scientific data and projects.
Adam has an interest in surface water quality and quantity monitoring and using consumer grade electronics to collect scientifically useful information.
Professional Experience
2015 - present - Geographer with USGS Western Geographic Science Center
2013 -2015 - Graduate researcher in Forestry and Remote Sensing at Virgina Tech University.
2011 - 2013 - Undergraduate researcher in sustainable polymer science at Texas State University
2012 - Student Environmental Laboratory Intern at Round Rock, Texas Water Plant
2011 - Student Volatile Air Organic Laboratory Intern at Texas Commision for Environmental Quality
Education and Certifications
M.S. in Forestry with an emphasis in Remote Sensing from Virginia Tech, where he researched the spatial distribution of autumn olive (Elaeagnus umbellate) on reclaimed surface coal mines in Appalachia
B.S. in Chemistry with a minor in Geography from Texas State University. Undergraduate research experience in sustainable polymer science and surface water quality.
Science and Products
Global Crop Water Productivity and Savings through waterSMART (GCWP)
Global Food-and-Water Security-support Analysis Data (GFSAD)
Global Hyperspectral Imaging Spectral-library of Agricultural-Crops & Vegetation (GHISA)
DESIS and PRISMA spectral library of agricultural crops in California's Central Valley in the 2021 Growing Season
Data Supporting Automated Cropland Fallow Algorithm (ACFA) for the Northern Great Plains of USA
PlanetScope and DESIS spectral library of agricultural crops in California's Central Valley for the 2020 growing season
Download rates of the Global Food-Security-Support-Analysis Data at 30-m Resolution (GFSAD30) Cropland-Extent Products
USGS Research Geographer Dr. Prasad Thenkabail and field assistant Sam Chaiya record the location and growth stage of a large rice paddy with a tablet in Na Yai Am District, Chanthaburi Province, Thailand.
Machine learning and new-generation spaceborne hyperspectral data advance crop type mapping
Automated Cropland Fallow Algorithm (ACFA) for the Northern Great Plains of USA
Crop water productivity from cloud-Based landsat helps assess California’s water savings
New generation hyperspectral data From DESIS compared to high spatial resolution PlanetScope data for crop type classification
Global food-security-support-analysis data at 30-m resolution (GFSAD30) cropland-extent products—Download Analysis
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
Hyperspectral narrowband data propel gigantic leap in the earth remote sensing
Planetary defense preparedness: Identifying the potential for post-asteroid impact time delayed and geographically displaced hazards
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
A meta-analysis of global crop water productivity of three leading world crops (wheat, corn, and rice) in the irrigated areas over three decades
Mapping cropland extent of Southeast and Northeast Asia using multi-year time-series Landsat 30-m data using Random Forest classifier on Google Earth Engine
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
Science and Products
Global Crop Water Productivity and Savings through waterSMART (GCWP)
Global Food-and-Water Security-support Analysis Data (GFSAD)
Global Hyperspectral Imaging Spectral-library of Agricultural-Crops & Vegetation (GHISA)
DESIS and PRISMA spectral library of agricultural crops in California's Central Valley in the 2021 Growing Season
Data Supporting Automated Cropland Fallow Algorithm (ACFA) for the Northern Great Plains of USA
PlanetScope and DESIS spectral library of agricultural crops in California's Central Valley for the 2020 growing season
Download rates of the Global Food-Security-Support-Analysis Data at 30-m Resolution (GFSAD30) Cropland-Extent Products
USGS Research Geographer Dr. Prasad Thenkabail and field assistant Sam Chaiya record the location and growth stage of a large rice paddy with a tablet in Na Yai Am District, Chanthaburi Province, Thailand.
USGS Research Geographer Dr. Prasad Thenkabail and field assistant Sam Chaiya record the location and growth stage of a large rice paddy with a tablet in Na Yai Am District, Chanthaburi Province, Thailand.