"Unique attributes of radar and optical data as related to forest mapping and how they can be complementary."

Review of the unique attributes of radar and optical data as related to forest mapping and how they can be complementary. The session also highlights the classification algorithms and improvements with optical imagery. You will complete an Exercise on Land Cover Classification with Radar and Optical using Google Earth Engine (GEE). 

Each training will include a theoretical portion describing the use of SAR for landcover mapping followed by a demonstration on how to access, download, and analyze SAR data for forest mapping and monitoring. These demonstrations will use freely available, open-source data and software.

By the end of this presentation, you will be able to:

• Identify the unique attributes of radar and optical data
• Explain the benefits and limitations to radar and optical data for forest mapping
• Understand the basics of land cover classification using both radar and optical data
• Conduct a land cover classification using Landsat and Sentinel-1 data in Google Earth Engine

Attendees who have not completed the Fundamentals of Remote Sensing may not be prepared for the pace of the training.

This training was created by NASA's Applied Remote Sensing Training Program (ARSET). ARSET is a part of NASA's Applied Science's Capacity Building Program. Learn more about ARSET HERE. In case of any questions regarding the session, please feel free to reach out to Ana I. Prados, Ph.D., Research Associate Professor, Joint Center for Earth Systems Technology (JCET), University of Maryland Baltimore County at aprados@umbc.edu.