Satellite Imagery Explained: 80 Years of Innovation in Space-Based Observation

This is a historic year for the satellite imagery field, and not just because of the launch of Space Aye’s Large Terrestrial Exchange platform. 2026 marks 80 years since the first ever image of earth was captured from space. In October 1946, scientists working out of the White Sands missile range successfully launched a modified V2 Rocket across the Karman line to an altitude of 105km. The few grainy black and white frames they captured from the very edge of space are the foundation for our whole industry.

Satellite imagery has come so far since those early sub-orbital flights. We have advanced from barely leaving the atmosphere and using systems that had to physically return rolls of photographic film to the Earth to be developed, to our LTx platform, a fully digital rapid tasking and delivery system.

Over the last few years that I have been in the industry, the improvements in delivery speeds from 2 days to under 2 hours have been striking, and tasking to delivery cycles measured in minutes are very much on the horizon. I truly believe that satellite imagery is right on the cusp of a revolution, similar to the internet boom around the turn of the millennium. The industry is transitioning from occupying a specialist niche to achieving true mass market adoption, with impacts in industries that no one could have foreseen.

All this enthusing about satellites raises an important question: what is satellite imagery, and why are there so many different types?

The first photo of Earth from space [left], 1946. Image via White Sands Missile Range/ Applied Physics Laboratory/ Wikimedia Commons

What actually is satellite imagery?

Simply put, it is an image taken of the Earth’s surface or atmosphere from space. However, there are various kinds of satellite imagery which have different applications.

The satellite imagery industry has developed multiple forms of satellite imagery to capture exactly what we might need of earth, but what they haven’t necessarily done is explain what these are and what they are for. This can be a barrier to entry for potential new users.

At Space Aye, we have seen many cases where there was a clear business need for satellite imagery, but identifying the most appropriate data, products and services was challenging due to the complexity of the market. With a wide range of providers, technical terminology and specifications to consider, selecting the right solution can be difficult and may also lead to costly mistakes.

A Very Quick Science Lesson: Understanding Light & Spectrums

Let’s do a quick rundown of what these satellite image types and uses are…but first, we need to do a very quick science lesson.

“Light” as we think about it, is just the section of the electromagnetic spectrum that our eyes can perceive. It is just one, relatively small section in the “middle” of the spectrum, that includes everything from radio waves and microwaves to x-rays and gamma rays.

The whole spectrum can be thought of as being broken into “bands” including the visual spectrum. You might have seen the experiment where a prism is used to break visible “white” light into its constituent “bands”, which our eyes see as different colours. This idea that light can be broken into bands that we perceive as colours it an important concept to keep in mind going forward.

The Main Types of Satellite Imagery

Optical: This is the most straightforward type of imagery as it focuses on imaging the visible spectrum.

Pan-spectral (or panchromatic) imagery produces a greyscale (black and white) image as it combines all the light bands into one. This allows for the highest possible resolution, at the expense of colour. A process called pansharpening can be used to produce a colour image by combining a panspectral image with 3 separate colour images which cover the red, green and blue bands of visible light. The 4 images are effectively overlayed on one another to produce a colour image.

Multispectral: This imagery expands on the previous idea by imaging more discrete bands of light, typically somewhere between 6 and 15, covering the visible spectrum and extending to the infrared or ultraviolet portions that our eyes can't see. These bands can be combined in different ways to produce true colour (what our eyes would see) or false colour images. These images can be used to monitor vegetation health, soil moisture, geological structures and fires. They also allow us to image at night to a greater extent than using visible light.

Hyperspectral: This imagery can be thought of, in very simple terms, as multispectral imagery but with more bands of light used (sometimes several hundred). This allows for more detailed information to be captured but at the cost of requiring more processing time and a more complex imaging system.

Thermal Imagery: This type of satellite imagery looks exclusively at the infrared bands of the spectrum to detect objects or areas that are hot and therefore are producing a lot of infrared light. This can be used to monitor cities, measure the temperature of the ocean or detect fires or volcanic activities.

Synthetic Aperture Radar (SAR): This imagery is something totally different. Where the previous types we have looked at absorb light coming from the Earth, SAR actively bounces (harmless) microwave pulses off the Earth and measures the reflections. This allows SAR to produce high resolution grey scale images of the Earth’s surface even in total darkness or through cloud cover. It is widely used to monitor infrastructure, agriculture and maritime activities.

What is resolution and why does it matter?

The word “resolution” has been mentioned a few times while discussing the various types of imagery, so it’s worth quickly clarifying what that is and why it is important.

Simply put, resolution is how many pixels are used to generate the image you are looking at.

If you are reading this article on an HD monitor, your screen resolution is probably something like 1920x1080. This means that your screen has 1920 pixels along the top and 1080 pixels down the side combining for a total of 2073600 pixels making up your screen. But what is a pixel? Simply put it’s a little square that is a particular colour. All these little squares combine to produce an image. If you look at a low-resolution image on a high-resolution screen, these individual pixels become very obvious.

Satellite imagery works the same way, but we usually measure resolutions in terms of Ground Sample Distance (GSD), which is basically how much ground area each pixel in the image represents. For example, if we have resolution of 1 metre, each pixel will represent a 1m x 1m square on the ground as a single colour value.

If we then increase the resolution to 0.50m each square meter on the ground is now represented by 4 pixels, each with their own colour values. So a 1000x1000 pixel image at 0.5m resolution will cover an area of 500m x 500m.

Higher Resolution Doesn’t Always Mean Better

It is easy to assume that the highest-resolution image is always the best option. In reality, the most suitable imagery depends on the task at hand.

Generally speaking:

Higher Resolution = Higher Cost

However, ultra-high resolution imagery isn’t required in every use case. In many situations, lower-cost imagery can deliver the information needed, particularly when combined with other data sources.

For example:

• Tracking activity within a defined area of interest – lower-resolution imagery may be adequate when combined with geofencing and location data. For example, while a vehicle may not be individually visible in 10-metre resolution imagery, data from GPS or electronic tracking device (IoT data) can confirm its presence within a known area of interest. This allows the imagery to provide valuable contextual information at a lower cost.

• Monitoring global crop health – medium resolution is often sufficient enough to identify vegetation trends and changes over large areas.

• Classifying or counting vehicles or infrastructure – high resolution imagery is typically required to distinguish individual objects and extract detailed information.

• Disaster response – speed and frequency of data may matter more than ultra-high detail, making lower-resolution imagery a practical choice in time-critical situations.

Space Aye: Simplifying Access to Satellite Imagery

With our Large Terrestrial Exchange (LTx) platform, we give all types of enterprises the ability to access their required and most appropriate satellite imagery for their use as simply as possible. We have brought together a range of satellite imagery providers, with a range of capabilities, and aim to present all those options in a way that allows users to make rapid decisions about what they need and get access to the imagery as quickly as possible – whether its archive imagery or specifically tasked satellite imagery for a future date.

Turning Imagery Into Actionable Intelligence

We have also recognised that getting a satellite image isn’t always the end of the journey and that by combining satellite imagery with other sources of data, real ground-truth value can be unlocked. To that end, we can use our patented Internet of Things (IoT) integration technology to identify assets or locations within the scope of the image.

For example, tracking firefighters within a natural disaster situation, supporting shipping and logistics tracking or being able to get a better understanding of agricultural situations through biometrics.

Satellite Imagery Is Only Just Beginning

Satellite imagery has come a long way in 80 years, from a grainy snapshot of New Mexico to a fully integrated data tool. It has diversified and has become a wide and deep toolset capable of serving a huge variety of functions, and one that the wider world is only beginning to explore.

In many ways, the industry feels similar to the internet just before its boom into mainstream adoption. Powerful technology that has existed for years but is now becoming faster, more accessible and easier to integrate into everyday operations thanks to developments such as Space Aye’s LTx.

Real growth in the industry is only going to come from combining those tools with the global IoT market, allowing space to add additional context to that constant stream of data…only with Space Aye.