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The orbit of a remote sensing satellite determines when, where, and how often it observes any point on Earth. Two orbit families dominate: sun-synchronous orbits (SSO) cross every latitude at the same local solar time, providing consistent illumination for comparative studies, with typical altitudes of 600-900 km and revisit periods of days to weeks. Geostationary orbits (GEO) sit at ~35,786 km above the equator, rotating with Earth to continuously monitor the same hemisphere at coarser spatial resolution. Orbit parameters directly control spatial resolution, swath width, temporal revisit, and illumination geometry.
Building on your understanding of sensor types, the next question is how the platform carrying the sensor determines what you can observe. A satellite's orbit dictates its altitude (controlling spatial resolution and swath width), its ground track pattern (determining geographic coverage), and its revisit period (how often you get a new image of the same location).
Sun-synchronous orbits are the workhorse of land remote sensing. Satellites like Landsat, Sentinel-2, and SPOT fly at 600-900 km altitude in near-polar orbits inclined at about 98 degrees. This inclination exploits Earth's equatorial bulge (J2 perturbation) to make the orbital plane precess eastward at exactly the rate Earth orbits the Sun. The satellite crosses every latitude at the same local solar time on every pass, chosen to balance adequate illumination with minimal cloud buildup.
Geostationary orbits serve a fundamentally different purpose. At 35,786 km altitude, the orbital period matches Earth's rotation, so the satellite appears stationary above a fixed equatorial point. GOES, Meteosat, and Himawari provide continuous hemispheric weather imagery at 10-15 minute intervals. The penalty is spatial resolution: each pixel covers 0.5-4 km on the ground.
The choice between orbit families is the first design decision in any remote sensing mission. It determines what science questions the satellite can answer, what applications it enables, and what complementary data sources are needed to fill its gaps.