Remote Sensing of Coastal Ecosystems (delivered in English and Spanish)

25 August, 1 and 8 September, 2020
Training Provider(s): 

Remote sensing of coastal and marine ecosystems is particularly challenging. Up to 80% of the signal received by the sensors in orbit comes from the atmosphere. Additionally, the constituents of the water column (dissolved and suspended) attenuate most of the light either through absorption or scattering. When it comes to retrieving information from the ocean floor, even in the clearest waters, only less than 10% of the signal originates from it. Users, particularly those with little remote sensing experience, stand to benefit from this training covering some of the difficulties associated with remote sensing of coastal ecosystems, particularly beaches and benthic communities such as coral reefs and seagrass.

Relevant UN Sustainable Development Goals: 

  • Goal 14: Conserve and sustainably use the oceans, seas and marine resources for sustainable development
  • Target 14.2: By 2020, sustainably manage and protect marine and coastal ecosystems to avoid significant adverse impacts, including by strengthening their resilience, and take action for their restoration in order to achieve healthy and productive oceans

Course Dates: August 25, September 1, and 8, 2020

Times and Registration Information: 

English Session: 11:00-12:00 EDT (UTC-4):
Spanish Session: 14:00-15:00 EDT (UTC-4):

Learning Objectives: By the end of this training, attendees will be able to:

  • Identify the different water column components and how they affect the remote sensing signal of shallow-water ecosystems
  • Outline existing satellite sensors used for ocean color and shallow-water ecosystem characterization
  • Understand the interaction between water constituents, the electromagnetic spectrum, and the remote sensing signal
  • Recognize the different processes used to remove the water column attenuation from the remotely-sensed signal to characterize benthic components
  • Summarize techniques for characterizing shoreline beach environments with remotely-sensed data and field methods for beach profiling

Audience: Local, regional, state, federal, and non-governmental environmental managers, researchers, and students.

Course Format: Three, 1-hour parts