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Adam Oliphant

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.

 

Education and Certifications

  • MS 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.

Science and Products

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Global Crop Water Productivity and Savings through waterSMART (GCWP)

The waterSMART (Sustain and Manage America’s Resources for Tomorrow) project places technical information and tools in the hands of stakeholders that allow them to answer pertinent questions regarding water availability. Two goals of waterSMART are to 1) establish water availability and its use based on an understanding of the past and present water users and to 2) project water availability and...
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Western Geographic Science Center
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Global Crop Water Productivity and Savings through waterSMART (GCWP)

The waterSMART (Sustain and Manage America’s Resources for Tomorrow) project places technical information and tools in the hands of stakeholders that allow them to answer pertinent questions regarding water availability. Two goals of waterSMART are to 1) establish water availability and its use based on an understanding of the past and present water users and to 2) project water availability and...
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Global Hyperspectral Imaging Spectral-library of Agricultural-Crops & Vegetation (GHISA)

This webpage showcases the key research advances made in hyperspectral remote sensing of agricultural crops and vegetation over the last 50 years. There are three focus areas:
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Ecosystems Mission Area, Land Change Science Program, Western Geographic Science Center
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Global Hyperspectral Imaging Spectral-library of Agricultural-Crops & Vegetation (GHISA)

This webpage showcases the key research advances made in hyperspectral remote sensing of agricultural crops and vegetation over the last 50 years. There are three focus areas:
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Global Food Security-Support

Global Food Security-Support Analysis Data at 30 m (GFSAD)

The GFSAD30 is a NASA funded project to provide high resolution global cropland data and their water use that contributes towards global food security in the twenty-first century. The GFSAD30 products are derived through multi-sensor remote sensing data (e.g., Landsat, MODIS, AVHRR), secondary data, and field-plot data and aims at documenting cropland dynamics from 2000 to 2025.
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Western Geographic Science Center
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Global Food Security-Support Analysis Data at 30 m (GFSAD)

The GFSAD30 is a NASA funded project to provide high resolution global cropland data and their water use that contributes towards global food security in the twenty-first century. The GFSAD30 products are derived through multi-sensor remote sensing data (e.g., Landsat, MODIS, AVHRR), secondary data, and field-plot data and aims at documenting cropland dynamics from 2000 to 2025.
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PlanetScope and DESIS spectral library of agricultural crops in California's Central Valley for the 2020 growing season

Here we provide information for the PlanetScope and d Deutsches Zentrum fur Luft- und Raumfahrt (DLR) Earth Sensing Imaging Spectrometer (DESIS) Derived Spectral Library of Agricultural Crops in California which was developed using PlanetScope Dove-R high spatial resolution data and DESIS hyperspectral data acquired for 2020. PlanetScope images are available through Planet Labs (2022). The DESIS i
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Western Geographic Science Center

Download rates of the Global Food-Security-Support-Analysis Data at 30-m Resolution (GFSAD30) Cropland-Extent Products

The data was collected to track the usage and downloads of the Global Food Security-support Analysis Data at 30 meters (GFSAD30) Cropland Extent Product. This data supports an Open File Report titled Global Food-Security-Support-Analysis Data at 30-m Resolution (GFSAD30) Cropland-Extent Products - Download Analysis. The GFSAD30 data is available for download on the National Aeronautics and Spate A
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Western Geographic Science Center
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New generation hyperspectral data From DESIS compared to high spatial resolution PlanetScope data for crop type classification

Thoroughly investigating the characteristics of new generation hyperspectral and high spatial resolution spaceborne sensors will advance the study of agricultural crops. Therefore, we compared the performances of hyperspectral Deutsches Zentrum fur Luftund Raumfahrt- (DLR) Earth Sensing Imaging Spectrometer (DESIS) and high spatial resolution PlanetScope in classifying eight crop types in Californ
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Western Geographic Science Center

Global food-security-support-analysis data at 30-m resolution (GFSAD30) cropland-extent products—Download Analysis

IntroductionThe global food-security-support-analysis data at 30-meter resolution (GFSAD30) cropland-extent product is a project to provide high-resolution global cropland-extent data relating to water use. It is the first global-land-cover map focusing exclusively on agriculture with a 30-meter spatial resolution. The overarching goal of the GFSAD30 project is to produce consistent and unbiased e
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Western Geographic Science Center

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

Executive SummaryGlobal food and water security analysis and management require precise and accurate global cropland-extent maps. Existing maps have limitations, in that they are (1) mapped using coarse-resolution remote-sensing data, resulting in the lack of precise mapping location of croplands and their accuracies; (2) derived by collecting and collating national statistical data that are often
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Western Geographic Science Center, International Programs

Hyperspectral narrowband data propel gigantic leap in the earth remote sensing

Hyperspectral narrowbands (HNBs) capture data as nearly continuous “spectral signatures” rather than a “few spectral data points” along the electromagnetic spectrum as with multispectral broadbands (MBBs). Almost all of satellite remote sensing of the Earth in the twentieth century was conducted using MBB data from sensors such as the Landsat-series, Advanced Very High-Resolution Radiometer (AVHRR
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Western Geographic Science Center

Planetary defense preparedness: Identifying the potential for post-asteroid impact time delayed and geographically displaced hazards

A considerable amount of effort has been done to quantify impact effects from the impact of an asteroid. The effects usually considered are: blast, overpressure shock, thermal radiation, cratering, seismic shaking, ejecta, and tsunami (e.g. Hills & Goda, 1993; Collins et al., 2005, Rumpf et al., 2017). These first-order effects typically are localized in time and diminish with increased distance
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Natural Hazards Mission Area, Astrogeology Science Center

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

The South Asia (India, Pakistan, Bangladesh, Nepal, Sri Lanka and Bhutan) has a staggering 900 million people (~43% of the population) who face food insecurity or severe food insecurity as per United Nations, Food and Agriculture Organization’s (FAO) the Food Insecurity Experience Scale (FIES). The existing coarse-resolution (>250-m) cropland maps lack precision in geo-location of individual farms
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Western Geographic Science Center

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

The overarching goal of this study was to perform a comprehensive meta-analysis of irrigated agricultural Crop Water Productivity (CWP) of the world’s three leading crops: wheat, corn, and rice based on three decades of remote sensing and non-remote sensing-based studies. Overall, CWP data from 148 crop growing study sites (60 wheat, 43 corn, and 45 rice) spread across the world were gathered from
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Western Geographic Science Center

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

Cropland extent maps are useful components for assessing food security. Ideally, such products are a useful addition to countrywide agricultural statistics since they are not politically biased and can be used to calculate cropland area for any spatial unit from an individual farm to various administrative unites (e.g., state, county, district) within and across nations, which in turn can be used
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Western Geographic Science Center

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

Mapping high resolution (30-m or better) cropland extent over very large areas such as continents or large countries or regions accurately, precisely, repeatedly, and rapidly is of great importance for addressing the global food and water security challenges. Such cropland extent products capture individual farm fields, small or large, and are crucial for developing accurate higher-level cropland
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Western Geographic Science Center

Mapping cropland fallow areas in myanmar to scale up sustainable intensification of pulse crops in the farming system

Cropland fallows are the next best-bet for intensification and extensification, leading to increased food production and adding to the nutritional basket. The agronomical suitability of these lands can decide the extent of usage of these lands. Myanmar’s agricultural land (over 13.8 Mha) has the potential to expand by another 50% into additional fallow areas. These areas may be used to grow short-
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Western Geographic Science Center

Fog water collection effectiveness: Mesh intercomparisons

To explore fog water harvesting potential in California, we conducted long-term measurements involving three types of mesh using standard fog collectors (SFC). Volumetric fog water measurements from SFCs and wind data were collected and recorded in 15-minute intervals over three summertime fog seasons (2014–2016) at four California sites. SFCs were deployed with: standard 1.00 m2 double-layer 35%
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Western Geographic Science Center

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

A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must for food and water security analysis. Precise and accurate global cropland extent maps, indicating cropland and non-cropland areas, are starting points to develop higher-level products such as crop watering methods (irrigated or rainfed), cropping intensities (e.g., single, double, or continuous cropping)
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Western Geographic Science Center
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The GFSAD30 project accomplished their goal!

The global croplands mapping project has succesfully mapped croplands across the entire planet in order to understand the security of food world wide...

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Scientists field verifying rice field in Thailand
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