Remote Sensing for Freshwater Habitats [Intermediate]

Key Info
URL - the landing page for the learning resource: 
https://appliedsciences.nasa.gov/what-we-do/capacity-building/arset?utm_campaign…
Description - a brief synopsis, abstract or summary of what the learning resource is about: 
Freshwater habitats play an important role in ecological function and biodiversity. Remote sensing of these ecosystems is primarily tied to observations of the drivers of biodiversity and ecosystem health. Remote sensing can be used to understand things like land use and land cover change in a watershed, habitat connectivity along a water body, water body location and extent, and water quality parameters. This webinar series will guide participants through using NASA Earth observations for habitat monitoring, specifically for freshwater fish and other species. The training will also provide a conceptual overview, as well as the tools and techniques for applying landscape environmental variables to genetic and habitat diversity in species. 

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


  • understand the limitations of using remote sensing for freshwater habitats

  • find data and models that can be used in their landscape genetics and habitat monitoring work

  • see how remote sensing can be used for habitat restoration, ecological assessments, and climate change assessments relating to freshwater systems

  • be able to use the Riverscape Analysis Project decision support system

  • be familiar with the Freshwater Health Index


Course Format: 


  • Three, one-hour parts that include lectures, demonstrations, and question & answer sessions

  • This training will only be broadcast in English

  • A certificate of completion will be available to participants who attend all parts and complete all homework assignments. Note: certificates of completion only indicate the attendee participated in all aspects of the training, they do not imply proficiency on the subject matter, nor should they be seen as a professional certification.


Prerequisites: Please complete ARSET's Fundamentals of Remote Sensing or have equivalent knowledge. Attendees that do not complete the prerequisite may not be prepared for the pace of the training. 

Part One: Review of Aquatic Remote Sensing & Freshwater Habitats
As a result of this part of the webinar series, attendees will be able to: 


  • identify which NASA satellites & sensors can be used for freshwater monitoring

  • understand the limitations of remote sensing of freshwater habitats

  • find data and models they can use in landscape genetics and habitat monitoring work


Part Two: Overview of the Riverscape Analysis Project (RAP)
As a result of this part of the webinar series, attendees will be able to: 


  • understand using remote sensing for habitat restoration, ecological assessments, and climate change assessments relating to freshwater systems through case studies

  • use the RAP decision-support system for accessing, downloading, and applying remote sensing data


Part Three: Overview of the Freshwater Health Index (FHI)
As a result of this part of the webinar series, attendees will be able to: 


  • understand how to evaluate freshwater ecosystem health

  • have the ability to use the FHI data and tools to assess freshwater ecosystem health

  • identify potential uses of the FHI for their work and decision-making

  • Use the FHI to identify vulnerabilities to degradation and/or climate change, as well as opportunities for improvement of infrastructure development within a basin


Each part of 3 includes links to the recordings, presentation slides, and Question & Answer Transcripts.
 

Authoring Person(s) Name: 
Amber McCullum
Juan Torres-Perez
Authoring Organization(s) Name: 
NASA Applied Remote Sensing Training Program (ARSET)
License - link to legal statement specifying the copyright status of the learning resource: 
Creative Commons Attribution 2.0 Generic - CC BY 2.0
Access Cost: 
No fee
Primary language(s) in which the learning resource was originally published or made available: 
English
More info about
Keywords - short phrases describing what the learning resource is about: 
Biodiversity data
Climate data
Conservation
Data access
Data formats
Environmental change records
Environmental management
Freshwater habitat applications
Hydrologic data
Land management
Remote sensing
Satellite imagery
Sustainable Development Goals (SDGs)
Subject Discipline - subject domain(s) toward which the learning resource is targeted: 
Education: Science and Mathematics Education
Physical Sciences and Mathematics: Earth Sciences
Physical Sciences and Mathematics: Environmental Sciences
Published / Broadcast: 
Tuesday, September 17, 2019
Publisher - organization credited with publishing or broadcasting the learning resource: 
NASA Applied Remote Sensing Training Program (ARSET)
Media Type - designation of the form in which the content of the learning resource is represented, e.g., moving image: 
Presentation - representation of the particular way in which an author shows, describes or explains one or more concepts, e.g., a set of Powerpoint slides.
Contact Person(s): 
Brock Blevins
Contact Organization(s): 
NASA Applied Remote Sensing Training Program (ARSET)
Educational Info
Purpose - primary educational reason for which the learning resource was created: 
Professional Development - increasing knowledge and capabilities related to managing the data produced, used or re-used, curated and/or archived.
Learning Resource Type - category of the learning resource from the point of view of a professional educator: 
Lesson - detailed description of an element of instruction in a course, [could be] contained in a unit of one or more lessons, and used by a teacher to guide class instruction. Example: presentation slides on a topic.
Target Audience - intended audience for which the learning resource was created: 
Citizen scientist
Data manager
Data policymaker
Early-career research scientist
Mid-career research scientist
Research scientist
Technology expert group
Intended time to complete - approximate amount of time the average student will take to complete the learning resource: 
More than 1 hour (but less than 1 day)