Satellite Imagery AI: What you need to know
Satellite images are used to solve many business problems and data assymetry challenges. Specifically, industries such as agriculture, geological and hydrological research, forestry, environmental protection, land planning, intelligence and military purposes benefit the most.
In the past, the Earth Observation (EO) practice was majorly available only to government hired analysts, exploring the potential of getting alternative data on what is happening around the world.
There are 3 trends that will make geospatial data more valuable than before. Firstly, satellite and launch manufacturing costs are decreasing. Secondly, small payload launches are cheaper as well. Finally, bandwidth costs have gone down drastically. More SATCOM business gets re-oriented to Observation.
The increasing application of AI transformed the imagery to analytics, allowing businesses and governments to solve challenges, apply location-based services, and do predictive modeling
Where to get data? Open source imagery
The image quality directly depends on the payload and the satellite’s orbit. For example, a resolution of 10 m means that anything below that mark will get pixelated, yet still possible to be analyzed. High resolution imagery ranging from 5 m to 0.3 m become main stream for data collection.
Depending on the business case, :
High resolution with a value of 0.3, m -5 meters.
Medium resolution with a value of 5-10 meters.
Low resolution with a value of 10 meters or more.