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July 12, 2017 - July 19, 2017

Prolonged drought can result in economic, environmental, and health-related impacts. In this webinar, participants will learn how to monitor drought conditions and assess impacts on the ecosystem using precipitation, soil moisture, and vegetation data. The training will provide an overview of drought classification, as well as an introduction to web-based tools for drought monitoring and visualization. Lectures will be followed by hands-on demonstrations of data access and visualization.

Agenda Cite This Training


By the end of the training, participants will be able to:

  • Understand how remote sensing can be used for drought monitoring
  • Acquire remotely-sensed imagery and products for drought
  • Analyze drought data and calculate anomalies within a geospatial software

Regional, state, federal, and international organizations interested in using remote sensing to monitor drought. Professional organizations in the public and private sectors engaged in environmental management and monitoring will be given preference over organizations focused primarily on research.

Course Format
  • Two 2-hour sessions
Remote Sensing-Based Drought Monitoring

This session will include an overview of drought classification, an introduction to web-based drought monitoring tools, a demonstration of drought data visualization tools, and end with an exercise for attendees to practice downloading data.


Materiales en Español:

Drought Monitoring Analysis and Application

This session will include a demonstration of soil moisture, groundwater, NDVI, and evapotranspiration (ET) data access and visualization, and will use a case study (California) exercise to demonstrate how participants can analyze drought conditions. Background will also be provided for a case study (northern Africa) to be used by participants to independently conduct their own analysis.


Materiales en Español:


Attendees that do not complete prerequisites may not be properly prepared for the pace and exercises during the training.