Getting Started

New to remote sensing? Read these pages in order. Each step builds on the one before it, and none of them needs a particular software platform.

1. Understand what an image is

1. Digital Imagery: start here; every later page assumes this picture of an image.
2. Spectral Bands: what each layer of the image records.
3. Visualization: how to look at those layers without fooling yourself.
4. Resolution: what a sensor can and cannot resolve.

2. Put images on the map

5. Raster vs Vector: how imagery meets points, lines and polygons.
6. Coordinate Systems: needed before combining any two datasets.

3. Turn pixels into answers

7. Time Series: one place, many dates.
8. Cloud Masking: remove what hides the surface before you measure it.
9. Classification Basics: labelling what the pixels show.
10. Change Detection: comparing dates with care.

4. Choose real data

11. Sentinel-2 and Landsat: the two open archives most examples use.
12. STAC Catalogs: how to find scenes from either one.

5. Run a complete workflow

13. NDVI Monitoring: the steps above, applied to one question from start to finish.

Where to go next

• Applied Workflows for other methods, and Applications for the fields that use them.
• Engineering when you need to run the analysis at scale.
• Implementation Tracks to try the ideas in a specific tool, starting with Google Earth Engine.

For how the site is organized, see What is Remote Sensing Labs?.