What You'll Learn
- Load a specific Landsat image by its ID
- Apply scale factors to Landsat Collection 2 data
- Create natural color (true color) composites
- Create false color composites using NIR
- Compare and interpret different band combinations
- Identify environmental events from satellite imagery
Building On Previous Learning
This lab challenges you to apply skills from multiple previous labs:
Why This Matters
The ability to quickly create and interpret different band combinations is essential for:
- Disaster response: Rapidly assess fire damage, floods, or storms
- Environmental monitoring: Track vegetation health, water bodies, urban expansion
- Verification: Confirm what you see in true color with NIR/SWIR bands
This lab simulates real-world scenarios where you need to work independently with unfamiliar imagery.
Before You Start
- Prerequisites: Complete Labs 1-4 and gather your notes on study area selection from the earlier challenges.
- Estimated time: 75 minutes
- Materials: Earth Engine login, any saved scripts from prior labs, and supporting references for your chosen region.
Key Terms
- Natural Color Composite
- RGB image using Red, Green, Blue bands to show features as they appear to the human eye.
- False Color Composite
- RGB image using non-visible bands (like NIR) to reveal information not visible to the eye.
- Scale Factor
- A multiplier applied to raw satellite data to convert Digital Numbers to physical values (like reflectance).
- Path/Row
- Landsat's grid system for identifying scene locations (e.g., Path 22, Row 39).
Introduction
This challenge lab gives you the opportunity to practice the skills you've learned in the previous labs. You'll work with a specific Landsat image to create both natural color and near-infrared false color composites, then analyze what each reveals about an environmental event.
Challenge Task
Create a new script to make two composites - natural color and near-infrared false color for this image:
Image ID:
'LANDSAT/LT05/C02/T1_L2/LT05_022039_20050907'
Hint: Look at the date in the ID - September 7, 2005. What was happening in the southeastern US at that time?
In your script, make comments with the following information:
- Where is this image?
- What environmental event do you think the images show?
- Compare and contrast the natural and false-color composites.
- What do the false-color composite help you see that is more difficult to decipher in the natural color composite?
Landsat 5 Band Reference
| Band Name | Wavelength | Description |
|---|---|---|
SR_B1 |
0.45-0.52 μm | Blue |
SR_B2 |
0.52-0.60 μm | Green |
SR_B3 |
0.63-0.69 μm | Red |
SR_B4 |
0.76-0.90 μm | Near Infrared (NIR) |
SR_B5 |
1.55-1.75 μm | Shortwave Infrared 1 (SWIR1) |
SR_B7 |
2.08-2.35 μm | Shortwave Infrared 2 (SWIR2) |
Composite Quick Reference
| Composite Type | RGB Bands | What It Shows |
|---|---|---|
| Natural Color | SR_B3, SR_B2, SR_B1 | As the eye would see it |
| NIR False Color | SR_B4, SR_B3, SR_B2 | Vegetation appears red/pink, water appears dark |
| SWIR False Color | SR_B7, SR_B4, SR_B3 | Good for urban areas and fire scars |
Hints
Technical Tips
- Landsat 5 uses Collection 2 Level 2 data
- Natural color composite: Use bands SR_B3 (Red), SR_B2 (Green), SR_B1 (Blue)
- False color (NIR) composite: Use bands SR_B4 (NIR), SR_B3 (Red), SR_B2 (Green)
- You may need to adjust min/max values for optimal visualization
- Use
Map.centerObject()to center on the image - Scale factors for Landsat Collection 2 Level 2: multiply by 0.0000275 and add -0.2
Sample Code Structure
// Load the image
var image = ee.Image('LANDSAT/LT05/C02/T1_L2/LT05_022039_20050907');
// Apply scaling factors
function applyScaleFactors(image) {
var opticalBands = image.select('SR_B.').multiply(0.0000275).add(-0.2);
return image.addBands(opticalBands, null, true);
}
var scaledImage = applyScaleFactors(image);
// Center the map
Map.centerObject(image, 8);
// Create natural color composite
Map.addLayer(scaledImage, {
bands: ['SR_B3', 'SR_B2', 'SR_B1'],
min: 0,
max: 0.3
}, 'Natural Color');
// Create false color composite
Map.addLayer(scaledImage, {
bands: ['SR_B4', 'SR_B3', 'SR_B2'],
min: 0,
max: 0.4
}, 'NIR False Color');
Analysis Questions
After creating your composites, explore the image and answer these questions in your script comments:
- Location: Where is this image located? (Hint: Look at the path/row and use geographic features)
- Environmental Event: What type of environmental event or phenomenon do you observe? Look for clues in both the natural and false color composites.
- Comparison: How do the natural color and false color composites differ in what they reveal? Which features are more prominent in each?
- False Color Advantage: What specific information does the false color composite reveal that is harder to see in the natural color composite?
Check Your Understanding
- Why do we need to apply scale factors to Landsat Collection 2 data?
- In a NIR false color composite, what color would healthy vegetation appear? What about water?
- How can you determine the location of a Landsat image from its ID?
- Why might a false color composite be better than natural color for assessing vegetation damage?
Troubleshooting
Solution: Your min/max values are wrong. For scaled reflectance data, try min: 0, max: 0.3. Use the Inspector to check actual pixel values.
Solution: Check that you copied the ID exactly, including the single quotes. The path is case-sensitive: use 'LANDSAT' not 'Landsat'.
Solution: For Landsat 5 Collection 2 Level 2, bands are named SR_B1, SR_B2, etc. (not just B1, B2).
📋 Lab Submission
Subject: Lab 5 - Challenge Refreshers - [Your Name]
Submit:
A shareable URL to your Google Earth Engine script that includes:
- Code to create both natural color and false color composites
- Comments answering all four questions above
- Proper visualization parameters for both layers
- Descriptive layer names
Total: 50 Points