Exercise: Earth Observation

Earth observation satellites, operated by organizations like NOAA and EUMETSAT, provide vital data for weather forecasting and environmental monitoring. NOAA manages polar orbiting satellites that deliver real-time weather data, while EUMETSAT operates satellites that support Europe and other regions with climate data.
In this exercise, you’ll track a weather satellite, capture its signal, decode the data into an image, and identify features such as mountains, cities, lakes, and weather fronts.
Objective
With the ground station (GS-SBIC-1M2), your task is to capture a signal from a Polar-orbiting satellite of your choosing and identify the signal you have received.
Here are your key tasks:
- Track a Weather Satellite: Use a ground station to track a NOAA or EUMETSAT weather satellite in real time.
- Capture a Direct Readout Signal: Receive and record the satellite’s live data stream using the ground station.
- Decode Raw Satellite Data: Process the captured signal to decode it into a weather image.
- Analyze the Image: Identify geographical features such as mountains, cities, lakes, and weather fronts in the decoded image.
Guidelines
1. Select a target satellite:
- Objective: Target a polar orbit satellite in view of the ground station.
- Hints: See suggested satellites in datasheets section, recommend NOAA-19.
2. Determine Azimuth/Elevation (Azi/Ele) values:
- Objective: Find the target satellite position in the sky (Azi/Ele) relative to the ground station.
- Tools: Use the Dashboard for accurate estimates.
3. Schedule the satellite pass:
- Objective: Plan the motion of the ground station’s dish by defining waypoints.
- Tools: See the ground station datasheet describing rotor performance and book via Dashboard.
- Considerations: Ensure to stay within ground station performance limitations for rotor speed and maximum recording duration (4 mins) when defining waypoint times.
4. Post-processing:
- Objective: Decode raw data into a usable image
- Tools: Install and use SatDump to decode the data.
