🎯 Learning Objectives
- Calculate the Normalized Difference Vegetation Index (NDVI) to map plant health.
- Perform an Unsupervised Classification (ISO Cluster / K-Means) to group pixels into classes.
- Interpret spectral signatures to label "clusters" as real-world features (Water, Urban, Forest).
- Compare results between "dry" and "wet" years.
🧪 Interactive Tool: The Spectral Explorer
Satellites see more than our eyes. Use this tool to understand how different surfaces reflect light across the spectrum.
📂 Scenario: The Drought Impact
You are a GIS Analyst for the State Water Board. A severe drought hit Central Texas in 2011. You need to quantify the change in vegetation health compared to a normal year (2010).
lab07_remote_sensing.zip
Contains: Landsat 5 Imagery (2010 & 2011)
🛠️ Step-by-Step Instructions
Select your preferred GIS platform to view instructions:
Calculate NDVI
1. Add the 2010 and 2011 multispectral images.
2. Go to the Imagery tab > Raster Functions.
3. Search for NDVI.
4. Visible Band: Red (Band 3 for Landsat 5).
5. Infrared Band: NIR (Band 4).
6. Run for both years. Darker distinct green = healthier vegetation.
Unsupervised Classification
1. Open the Classification Wizard (Imagery Tab).
2. Choose Unsupervised (ISO Cluster).
3. Set Number of Classes to 5.
4. Run the classification. The result is a raster with values 1-5.
Label Classes
1. Compare the result to the basemap.
2. If Class 1 is "Blue" and covers the lake, rename it "Water".
3. If Class 2 is "Grey" and covers the city, rename it "Urban".
✅ Submission & Assessment
To complete this lab, you must submit:
- Map 1: NDVI Change Map (Difference between 2010 and 2011).
- Chart: A bar chart showing the % of land cover for each class (Water, Urban, Forest, etc.).
- Answer: Which land cover class changed the most during the drought?