Earth Observation Data: Understanding Resolutions

November 23, 2022

The Two Resolutions To Focus On

Satellite imagery can be very intimidating because there’s a wide range of resolutions.

And as a new person in the industry, you might be completely overwhelmed.

At a high level there are two resolutions we think of in the satellite imagery ecosystem.

We think of Spatial Resolution which is much the same way you think of the newer iPhones having a better camera than the older iPhones.

And we think of Spectral Resolution which are the specific bands in the electromagnetic spectrum that each sensor is capturing.

So, to use the iPhone example, that captures a multispectral set of bands.

RGB that means that your human eye can see it.

But oftentimes there are bands in the electromagnetic spectrum that your human eye can’t actually see.

Higher Resolution Is Not Always Better

Now, as humans,we default to always thinking that the higher the resolution, the better.

But that’s not always the case.

On SkyWatchwe have a range of resolutions that you can access all via a single easy to use console.

We have low resolution around 10 m per pixel. Medium resolution, 1.5 to 3 m per pixel. And high resolution about 0.5 m per pixel.

To give a sense of high how high resolution that is, you can see the outlines of cards in a car parking lot at 50 centimeters.

Now while high resolution satellite imagery provides maybe a bit more detail, it also incurs a much higher cost on a per square kilometer basis.

See What You Need For Free

What we actually recommend customers to do is to come onto the EarthCache platform.

Use low resolution data, which is free, and begin experimenting to see what they can actually accomplish with low resolution data, only moving up to paid data in the medium resolution and high resolution camps once their business needs require it.

Now this is juxtaposed to many data providers who will try to make you sign a high resolution contract immediately.

We actually take the opposite approach.

We want you to come onto the platform experiment, see what works and only begin paying for data once it’s actually useful to your business use case. 

Getting Your ROI From Satellite Data

An example industry where this is most prevalent is in agriculture. Agriculture has a wide variety of needs and oftentimes they’re looking for a field by field analysis as to their specific crop health.

Now you could accomplish this via high resolution tasking data, but it will get expensive pretty quickly.

And occasionally there’s also spectral bands that high resolution multispectral sensors wouldn’t actually capture.

A perfect example of this is the red edge band which is particularly useful for vegetation management,  is not captured in high resolution multispectral tasking satellites, but it is captured at the medium resolution range.

Couple that with wider swathe widths, lower price per square kilometer and it’s a no brainer to use medium resolution data for a lot of your agriculture needs.

Scaling To Get The Right Value

At the end of the day cost and value created don’t scale on a 1 to 1 basis.

There are diminishing returns as you increase your spend on satellite imagery.

And one thing that we really want to advocate for customers to look at is to make sure that it makes sense to increase that resolution such that it matches the return on investment within their actual business.

If that equation doesn’t make sense, then the long term validity of using satellite imagery in your business won’t make sense either.

What people who are using this data to ultimately serve to an end customer need to realize is the end customer just cares about the insight. And at the end of the day, satellite data is just one data source that you’re using in a multitude of data sources to ultimately deliver insights.

By you being more cost effective and how you use satellite imagery, it will ultimately create a better experience for your customers, which will in turn make them more likely to use satellite imagery and creates a virtuous circle.

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