Global Food Security Analysis-Support Data at 30 Meters (GFSAD30) Project

The Overarching Goal of the GFSAD30 project is to map and produce cropland products of the world at 30 meter resolution.

 

Global Food Security

The global population has just topped the 7 billion mark – a stark reminder of the greatest threat facing humanity in the 21st Century - food security. Society faces real challenges ahead, particularly in managing water and food supplies, as well as energy, and they are all intimately connected in achieving global food security.

Mapping Cropland on a Global Scale

Part of the answer lies in understanding global croplands, both rainfed and irrigated, how they are used, their extents and how they can be better managed, particularly since they account for nearly 80% of all freshwater abstractions. Here technologies such as remote sensing will play an increasingly critical role – providing new spatial information to help manage croplands in a more productive and sustainable way.

Help the Project

While remote sensing technologies continue to improve, we need your help to help us make sense of the data and test that our products are accurate. Use the links to the right to download our app or label some images.

Global Croplands Mobile Application

Collect data on land-use with our mobile application. It is simple to use and creates the most benefit for the project. Available for IOS and Android devices.

Get the App »

 

Our Products

The GFSAD products are freely available for educational, research, or commercial applications. If you wish to cite the GFSAD products in a report or publication please cite:

Thenkabail P.S., Knox J.W., Ozdogan, M., Gumma, M.K., Congalton, R.G., Wu, Z., Milesi, C., Finkral, A., Marshall, M., Mariotto, I., You, S. Giri, C. and Nagler, P. 2012. Assessing future risks to agricultural productivity, water resources and food security: how can remote sensing help?. Photogrammetric Engineering and Remote Sensing, August 2012 Special Issue on Global Croplands: Highlight Article. 78(8): 773-782.

Teluguntla, P., Thenkabail, P.S., Xiong, J., Gumma, M.K., Giri, C., Milesi, C., Ozdogan, M., Congalton, R., Tilton, J., Sankey, T.R., Massey, R., Phalke, A., and Yadav, K. 2014. Global Cropland Area Database (GCAD) derived from Remote Sensing in Support of Food Security in the Twenty-first Century: Current Achievements and Future Possibilities. Chapter 7, Vol. II. Land Resources: Monitoring, Modelling, and Mapping, Remote Sensing Handbook edited by Prasad S. Thenkabail.

Map

LP DAAC

Download Our Data at USGS LP DAAC.

USGS LP DAAC »

Map

Earth Engine

Analyze our data on Google Earth Engine.

Go to Earth Engine »

 

Our Methods

Our map products are created with data such as Landsat and Modis imagery using remote sensing techniques by analyzing millions of image pixels. For example, we combine temporal patterns of the Normalized Vegetation Difference Index(NVDI) with our reference data to classify the world's cropland by the following measures.

  • Cropland or NonCropland
  • Irrigation or Rainfed
  • Crop Types
  • Intensity of Cropland

Note: The more reference data that we have, the more that we can refine our algorithms and test their effectiveness. You can help our project by providing us with additional reference locations.

Remotely sensed data provide the only source of information to make a complex global agricultural monitoring system feasible by being consistent, repeatable, routine, rapid, and scalable.

2012, Thenkabail, Prasad S. et al;
 

Our Publications

Read the relevant publications that have contributed to our work and the 'knowledge gateway' that we hope to provide to the the scientific community.

Thenkabail P.S., Knox J.W., Ozdogan, M., Gumma, M.K., Congalton, R.G., Wu, Z., Milesi, C., Finkral, A., Marshall, M., Mariotto, I., You, S. Giri, C. and Nagler, P. 2012. Assessing future risks to agricultural productivity, water resources and food security: how can remote sensing help?. Photogrammetric Engineering and Remote Sensing, August 2012 Special Issue on Global Croplands: Highlight Article. 78(8): 773-782.

Teluguntla, P., Thenkabail, P.S., Xiong, J., Gumma, M.K., Giri, C., Milesi, C., Ozdogan, M., Congalton, R., Tilton, J., Sankey, T.R., Massey, R., Phalke, A., and Yadav, K. 2014. Global Cropland Area Database (GCAD) derived from Remote Sensing in Support of Food Security in the Twenty-first Century: Current Achievements and Future Possibilities. Chapter 7, Vol. II. Land Resources: Monitoring, Modelling, and Mapping, Remote Sensing Handbook edited by Prasad S. Thenkabail.

 

Meet the Team

In 2013, the US Geological Survey’s (USGS) John Wesley Powell Center launched a major new initiative – an international Working Group on Global Croplands (WGGC) and their Water Use for Food Security in the Twenty-first Century, led by Dr. Prasad Thenkabail (Research Geographer) from the USGS. Prasad has assembled a group of scientists from across the world, with skills spanning the disciplines necessary to grapple with these issues – to harness and share their collective knowledge on remote sensing, crop modelling, food security, water management and geographical information management.

  • Dr. Prasad Thenkabail, PI, USGS
  • Dr. Mutlu Ozdogan, co-I, UW
  • Dr. Russ Congalton, co-I, UNH
  • Dr. Chandra Giri, co-I, USGS EROS
  • Dr. James Tilton, co-I, NASA GSFC
  • Dr. Temuulen 'Teki' Sankey, co-I, NAU
  • Dr. Terrance Slonecker co-I
  • Dr. Mahesh Rao co-I
  • Dr. Jennifer Dungan, NASA Ames
  • Dr. Tyler Erickson, Google, Inc.
  • Noel Gorelick, Google, Inc.
  • Dr. Pardhasaradhi Teluguntla, BAERI\USGS
  • Dr. Jun Xiong, Post doc, NAU\USGS
  • Dr. Murali Krishna Gumma, ICRISAT
  • Dr. Venkateswarlu Dheeravath, UN
  • Richard Massey, PhD student, NAU/USGS
  • Aparna Phalke, PhD student, UW
  • Kamini Yadav, PhD student, UNH
  • Gu Jianyu, PhD student, UNH
  • Varsha Vijay, PhD student, Duke University
  • Adam Oliphant, MS, USGS
  • Justin Poehnelt, USGS/NAU
  • Michela Marinelli, UN FAO
  • Fabio Grita, UN FAO