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Daniel J Foley

Daniel Foley is a geographer with the Western Geographic Science Center focused on remote sensing and geospatial analysis of croplands and water use to better understand crop water productivity to mitigate food and water insecurity in the 21st century. 

Global Crop Water Productivity and Savings through waterSMART (GCWP)

A Meta-Analysis of Global Crop Water Productivity

Increased food production per unit of water or increasing water productivity (or “more crop per drop”; kg/m3) is expected to lead to a “blue revolution” in agriculture making a major contribution to global food and water security in the twenty-first century. 

Global Crop Water Productivity and Savings through waterSMART (GCWP)

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

The spatial distribution of global cropland areas.

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.

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

Professional Experience

  • Daniel Foley is a geographer working for the USGS within the Western Geographic Science Center. He has a Master of Science (M.S.) in Applied Geospatial Sciences and a graduate certificate in Geographic Information Systems (GIS) from Northern Arizona University. His research interests include utilizing GIS, geospatial technology, and remote sensing to solve problems in Earth and environmental scien

Honors and Awards

  • 2021 - Best presentation award: ICWSM007 2021: XV. International Conference on Water Security and Management. Istanbul, Turkey. June, 2021.

Abstracts and Presentations

  • Foley, D., Thenkabail, P.S.., Teluguntla, P., and Oliphant, A., 2021. Cloud-Based Evapotranspiration and Crop Water Productivity Model of Leading World Crops Using Landsat and Meteorological Data Computed with Google Earth Engine: A California Central Valley, USA Case Study. ICWSM007 2021: XV. International Conference on Water Security and Management. Istanbul, Turkey. June, 2021.

  • USGS Flagstaff Science Seminar: Foley, D. How to feed the planet with less water: Mapping crop water Productivity with Remote sensing. September 1, 2021

  • WGSC Science Seminar Talk: Foley, D. A cloud-based novel Crop Water Productivity (CWP) model of leading world crops in California’s Central Valley using Landsat and meteorological data computed on Google Earth Engine (GEE) Platform. September Sept 15, 2021

  • Flagstaff Festival of Science 2021 SCI Talks: Foley, D.  How to grow more food with less water using Geographic Science.  September 24, 2021

Science and Products

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
By
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
By
Western Geographic Science Center

Crop water productivity estimation with hyperspectral remote sensing

Crop water productivity (CWP) is the ratio of accumulated crop biomass or yield (Y) to the water utilized to produce it, which is typically estimated using transpiration (ETC). CWP is an important metric to test and monitor water-saving strategies in agroecosystems across the globe. Red and near-infrared broadbands have been used to estimate CWP, because they capture biophysical constraints based
By
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...
By
Western Geographic Science Center
link

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 Spectroscopy 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:
By
Ecosystems, Land Change Science Program, Western Geographic Science Center
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Global Hyperspectral Imaging Spectroscopy 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:
Learn More
link
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 1990 to 2017.
By
Western Geographic Science Center
link

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 1990 to 2017.
Learn More

Science and Products