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YCEO Intro to Remote Sensing with Google Earth Engine In-Person

Go to Workshop Cloud-Based Geospatial Analysis using Google Earth Engine

Overview: The Yale Center for Earth Observation is offering an introductory workshop on satellite-based remote sensing.  This workshop will introduce the basic concepts of remote sensing including the electromagnetic spectrum, characteristics of selected major sensor systems, components of a satellite image, and a description of spectral, spatial and temporal resolution.

Students will use Google Earth Engine and cloud-based data to compare and contrast various types of data across time and space and will be introduced to basic image manipulation techniques. 
Participants need to sign up for a Google Earth Engine account before the workshop at https://signup.earthengine.google.com
You may bring your own laptop or use the lab PC.

Software Used: Google Earth Engine

Topics

This workshop covers basic concepts of remote sensing including:

  • the electromagnetic spectrum,
  • characteristics of selected major sensor systems,
  • components of a satellite image, and 
  • a description of spectral, spatial and temporal resolution.

Before you come

This workshop is designed for attendees who have the following:

  • Participants need to sign up for a Google Earth Engine account before the workshop at https://signup.earthengine.google.com
  • a Yale NetID to use lab machines or you may bring your own laptop or use the lab PC.

Please email natalie.schultz@yale.edu with any questions about this workshop.

            LOCATION: CSSSI Classroom (C27), Kline Biology Tower, Concourse Level -  219 Prospect St.

Related LibGuide: Geographic Information Systems at Yale by Miriam Olivares

Date:
Friday, February 28, 2020
Time:
1:00pm - 3:00pm
Time Zone:
Eastern Time - US & Canada (change)
Campus:
Science Hill
Categories:
  Marx Science and Social Science Library     Miscellaneous     GIS & Geospatial  
Registration has closed.

Event Organizer

Profile photo of Miriam Olivares
Miriam Olivares