Satellites

A satellite is an object orbiting another body. The Moon is a natural satellite; the machines people launch are artificial satellites. Their motion follows Orbital mechanics. Being in orbit does not mean being stationary or beyond the reach of gravity.^[1]

An artificial satellite is a spacecraft in a bound orbit about a primary body. Its state includes position and velocity, while orbital elements provide a useful alternative description. Mission terminology often reserves “probe” for other exploration trajectories, although a spacecraft can change classification as it enters or leaves an orbit.^[1]

The payload does the mission’s main job, such as taking pictures or relaying signals. The bus supports it with electricity, communications, temperature control, and orientation. A small CubeSat still needs those services, even if each component is much smaller than on a large spacecraft.^[2]

Bus functions commonly include structure, power conditioning and storage, command and data handling, communications, attitude control, and thermal management. The payload-to-bus boundary is an architectural choice rather than a physical law. Instrument needs flow into pointing, electromagnetic compatibility, thermal stability, and downlink requirements.^[2]

A satellite’s orbit determines what it can see and when. Some watch broad regions from far away; others pass closer to Earth and build up coverage over many orbits. Weather observation, communications, and navigation therefore use different arrangements rather than one universal “satellite orbit.”^[1][3]

Altitude and inclination influence footprint, access time, revisit, latency, and spatial resolution. A geostationary platform supports persistent regional viewing but with geometry unlike a low-orbit imager. Constellations can improve temporal coverage, but their performance depends on orbital distribution, payload capabilities, and ground infrastructure, not simply the number of spacecraft.^[1][3]

Earth-observing satellites measure light or other signals that must be interpreted. A colourful map may represent temperature, reflected sunlight, or radar measurements. Understanding what was measured, at what resolution, and under which conditions matters as much as the appearance of the finished image.^[3]

Remote-sensing products depend on sensor calibration, spectral response, geometric processing, and retrieval algorithms. Spatial, spectral, radiometric, and temporal resolution are distinct. Comparing two datasets requires compatible definitions and uncertainty treatment. Instrument measurements become application products through a processing chain that can introduce its own assumptions and limitations.^[3]