Description

Extreme heat events are defined as prolonged periods of excessively high temperatures for multiple consecutive days. According to the World Health Organization (WHO), heat stress is the leading cause of weather-related deaths and can exacerbate accidents, underlying illnesses, and the transmission of some infectious diseases. This intermediate-level training equips participants with the foundational theory and practical skills to leverage thermal infrared (TIR) remote sensing to quantify these risks.

The course begins by establishing the physical principles of TIR, including emissivity and blackbody radiation. While these fundamentals are broadly applicable to numerous applications, this training specifically focuses on using data from NASA’s Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) to identify heat-vulnerable communities and quantify urban heat island (UHI) effects.

In the hands-on component, participants will process ECOSTRESS Land Surface Temperature (LST) data in R – including quality filtering and time-of-day subsetting – and apply the interactive ECOSTRESS LST Downscaling Tool in Google Earth Engine. This tool uses a random forest model to enhance spatial resolution from 70 m to 10 m, translating satellite observations into street-scale thermal maps suitable for urban planning, strategic greenspace placement, and extreme heat early warning systems. 

No prior programming experience is required.

Prerequisites

• Fundamentals of Remote Sensing

Objectives

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

• Identify the fundamental concepts and physical principles of thermal infrared remote sensing;
• Define the role of emissivity retrievals in ensuring the accuracy of satellite-derived land surface temperature products;
• Distinguish key differences between thermal and optical remote sensing approaches, including emission versus reflection, day/night capability, and atmospheric window considerations;
• Identify applications of thermal remote sensing data for ecosystems stewardship, agricultural management, climate adaptation, and urban planning;
• Compare the characteristics of current and upcoming thermal missions in context of their suitability to different application uses;
• Filter and visualize ECOSTRESS Land Surface Temperature (LST) data using provided R-based data processing workflows;
• Downscale native 70 m ECOSTRESS LST data to a fine 10 m spatial resolution using a Random Forest machine learning model implemented on an interactive Google Earth Engine (GEE) interface to analyze neighborhood-level urban heat patterns.

Target Audience

Urban planners, climate adaptation practitioners, and climate researchers who work with satellite data and have applied remote sensing knowledge. Participants should be comfortable with intermediate-level data analysis and have some experience with Python or the willingness to follow along with code examples.

Graduate students in environmental science, geography, or related fields; government personnel working on forest monitoring, urban heat mapping, or climate adaptation; and NGO staff involved in conservation and climate resilience projects.

Course Format

• The complete course consists of two 1.5-hour parts, with Part 1 offered on May 26 and Part 2 on June 2.
• On each day, there are two opportunities to take the course (identical offerings):
  • Session A: 11:00 a.m. to 12:30 p.m. EDT (UTC-5)
  • Session B: 2:00 p.m. to 3:30 p.m. EDT (UTC-5)
• Each part will include a 30-minute live Q&A.
• Those who attend Parts 1 & 2 and complete the homework by the due date will receive a certificate of attendance.

Sessions

Part 1: Foundational Concepts

Tuesday, May 26, 2026 

• Introduction
• Thermal Infrared Fundamentals
• Emissivity
• Current and Future Thermal Missions and Applications
• Summary
• Q&A

ARSET Instructor

Savannah Cooley (Bay Area Environmental Research Institute/NASA Ames Research Center)

Materials

• Part 1 Presentation Slides (PDF, 5.8 MB)

Part 2: Applications in Urban Heat Island Mapping

Tuesday, June 2, 2026

• Urban Heat Island Theory
• Land Surface Temperature Data Overview
• Hands-on Exercise 1: Land Surface Temperature in Los Angeles County
• Hands-on Exercise 2: ECOSTRESS LST Downscaling Tool
• Summary
• Q&A

ARSET Instructor

Savannah Cooley (Bay Area Environmental Research Institute/NASA Ames Research Center)

Guest Instructor

Glynn Hulley (NASA Jet Propulsion Laboratory)

Materials 

• Part 2 Presentation Slides (PDF, 11.0 MB)
• GEE EcoSharp Tutorial (PDF, 0.3 MB)
• QGIS ECOSTRESS Tutorial (PDF, 0.2 MB)

Homework

• Homework (Due June 16, 2026)

Resources

• Downloading from AppEEARS – ECOSTRESS Tutorials
• Downloading from Earthdata Search – Mac – ECOSTRESS Tutorials
• ECOSTRESS Tutorials Youtube Channel  

• Install QGIS
  • For assistance, please follow this ARSET tutorial. If you do not already have an account for the ARSET learning management system, you will be prompted to create a free account before you can access the tutorial. 
• Access this training's GitHub
  • If you are new to Github, it may be helpful to review this ARSET tutorial to familiarize yourself with the platform.
• Access AppEEARS
  • You will need to make a free account to access AppEEARS if you do not have one already.
• Access Google Earth Engine
  • You will need to make a free account to access GEE if you do not have one already.