Understanding satellite imagery resolution

Satellite imagery is a powerful tool for monitoring landscapes, tracking change, and making informed decisions. One of the most important concepts to understand is “resolution”—and it’s more than just a number attached to an image.

In Lens, you can access a wide variety of public and leading commercial satellite imagery at a range of resolutions and we want to make sure you are well-equipped to choose the right data source for your monitoring. See all our available datasets and transparent pricing here and contact our team to learn more.

What does "resolution" mean?

When we talk about satellite imagery resolution, we’re referring to the size each pixel represents on the ground, specifically the width of the pixel. For example, for imagery with 10-meter resolution, a single pixel covers an area of 10-meters by 10-meters, or a total of 100 square meters. Similarly, data at a 30-meter resolution has pixels that represent an area on the ground of 30-meters by 30-meters for a total of 900 square meters. It’s easy to assume that a 10m pixel is a third the size of a 30m pixel, but in reality, it’s actually one-ninth of the area. This is important to keep in mind when comparing datasets and assessing what level of detail is available and most relevant for your use case.

Spatial vs. temporal resolution

Resolution isn’t just about pixel size. It’s also about timing. Spatial resolution dictates how much detail can be seen, while temporal resolution refers to how often new imagery is collected for a location. Typically, the finer the detail (higher spatial resolution), the less frequently the area is revisited. Understanding the balance between these two types of resolution helps tailor imagery selection to your specific needs.

For example, Sentinel-2 data in Lens has a lower spatial resolution of 10 meters, but it has a high temporal resolution with a revisit time of about every 5 days. Conversely, another publicly available data source in Lens is NAIP – this data has a spatial resolution of 1 meter, but a frequency of about once every 2 years.

Choosing the right resolution

Not all tasks require the highest possible spatial resolution. Monitoring broad areas for vegetation or water change might only need moderate resolution, while identifying new structures or specific objects calls for finer detail. Aligning the resolution to the monitoring goals ensures efficient, effective analysis without unnecessary data volume or cost.

Generally speaking, finer resolutions mean more expansive data. A 10-meter resolution image is typically sufficient for detecting broader changes such as timber harvesting, new construction, road development, or agricultural harvests. However, for specific details or smaller-scale changes such as new sheds, identifying cattle, or vehicle tracks, sub-meter resolution is recommended. While factors like haze and color correction can influence image sharpness, this serves as a general guideline.

Maximizing value from satellite data

Optimizing the mix of spatial and temporal resolution—using more frequent, lower-resolution imagery for ongoing monitoring and high-resolution data for detailed analysis when needed—can boost both coverage and precision. Thoughtful pairing helps answer a variety of questions, whether tracking daily change or investigating specific events. With satellite tasking, you can also guarantee high-resolution imagery at the time when you need it.

The right satellite imagery resolution is the one that best matches your question, not just the highest available. By understanding both spatial and temporal resolution tradeoffs, users can select the right datasets to support scalable, actionable landscape monitoring.

Want to learn more about what imagery resolution is right for your projects? Get in touch with our team, we’d be happy to help!