Satellite Remote Sensing for Agricultural Applications[Introductory]

Key Info
Description - a brief synopsis, abstract or summary of what the learning resource is about: 
Since the launch of NASA’s first Landsat mission in 1972, satellite imagery has been used for global agricultural monitoring, providing one of the longest operational applications for the Landsat program. Although satellite observations of land began with agricultural monitoring, only in recent years has agricultural remote sensing seen reinvigoration among space agencies, national ministries of agriculture, and global initiatives. To monitor agricultural systems, NASA utilizes satellite observations to assess a wide variety of geophysical and biophysical parameters, including precipitation, temperature, evapotranspiration, soil moisture, and vegetation health.

Past ARSET webinars on land and water resources covered remote sensing-derived parameters relevant to agriculture within a broader scope. This 4-part introductory webinar will focus on data products, data access, and case-studies demonstrating how remote sensing data can be used for decision-making among the agriculture and food security communities.

This training will address how to use remote sensing data for agriculture monitoring, specifically drought and crop monitoring. The webinar will also provide end-users the ability to evaluate which regions of the world agricultural productivity are above or below long-term trends. This informs decisions pertaining to market stability and humanitarian relief.

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

  • Identify which satellites and sensors can be used for agricultural applications
  • Understand the limitations of remote sensing and modeled data for agriculture and food security
  • Acquire specific remote sensing data products that are appropriate for their work
  • Apply remote sensing techniques to crop monitoring, drought, and humanitarian relief

course Format: 

  • Four online, 1.5-hour parts with sessions offered twice a day
  • A certificate of completion will also be available to participants who attend all sessions and complete the homework assignment, which will be based on the webinar sessions. 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.

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

Part 1: Overview of Agricultural Remote Sensing
This section will cover the ARSET Program and give a general overview of remote sensing as it pertains to agriculture. This part will include the history of Earth observations (EO) for agriculture, satellites and sensors that can be used, the limitations of satellite data, an introduction of NASA HARVEST, examples of current EO applications in agriculture, and a Q&A session.

Supplementary Materials:
NASA Satellites and Sensors Relevant for Agriculture »

Fact Sheets:

  • Air Quality
  • Vegetation
  • Water Availability
  • Water Quality

Part 2: Soil Moisture for Agricultural Applications
This part of the training provides an overview of SMAP and case studies for agricultural applications and an overview of soil moisture and shallow groundwater from the Land Data Assimilation System (LDAS), as well as a Q&A session.

Part 3: Earth Observations for Agricultural Monitoring
This section will cover previous ARSET training that relates to agricultural monitoring and present case studies of EO being used for agricultural monitoring. There will also be a Q&A session.

Part 4: Evapotranspiration (ET) & Evaporative Stress Index (ESI) for Agricultural Applications
This section includes a presentation from guest speaker Dr. Christopher Hain, along with an overview and case studies of ET and ESI in agricultural applications. This section will conclude with a Q&A session.

Each part of 4 includes links to the recordings, presentation slides,  and Question & Answer Transcripts.

Authoring Person(s) Name: 
Sean McCartney
Amita Mehta
Erika Podes
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: 
Also available in - other languages in which the learning resource has been translated or made available other than the primary: 
More info about
Keywords - short phrases describing what the learning resource is about: 
Agriculture applications
Agriculture data
Crop monitoring
Data access
Drought monitoring
Environmental management
Land management
Remote sensing
Satellite imagery
Soil moisture analysis
Soils data assessment systems
Soils software and data management applications
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, April 14, 2020
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)