
I am fortunate to be part of two publications that are great examples of cutting-edge work using remote sensing in archaeology. To celebrate these publications, this post provides a succinct overview of a foundational concept in remote sensing while providing archaeological examples. Read on to learn more about the 4 resolutions of remote sensing from an archaeological perspective.
Background
Remote sensing is a term used to describe acquiring data from a distance. In archaeology, we use a variety of remote sensing methods. For example, ground-penetrating radar and magnetometry are two methods used to detect underground archaeological features (e.g., buried buildings or even entire settlements).
Airborne platforms like satellites are also a popular remote sensing method in archaeology. They are especially useful for obtaining information on a regional scale. Different satellites offer different types of data and data quality. Remotely sensed images are generated based on four different types of resolutions:
- Spectral
- Spatial
- Temporal
- Radiometric
The next section details the 4 resolutions of remote sensing.

4 Resolutions of Remote Sensing
Spectral Resolution
Spectral resolution is the number and size of bands in the electromagnetic spectrum that a remote sensing platform can capture. For example, the first two Landsat satellites use a multi-spectral scanner (MSS) and captured images using four spectral bands (green, red, and two near-infrared bands). On the other hand, h
In a recent paper spearheaded by my colleague Alexander Sivitskis, we used hyperspectral imagery to detect natural occurrences of

You might remember an earlier blog post detailing the discovery and publication of the archaeological site of Aqir al-Shamoos in Oman. This find was important because it was the first known site in Arabia that demonstrated soft-stone production, but we did not know the raw material source location(s).
‘Soft-stone’ is a colloquial term and ‘
What does this have to do with spectral resolution?
The chloritite at Aqir al-Shamoos has a distinct spectral signature (like a fingerprint). We used hyperspectral imagery to target potential sources of chloritite and compare spectral signatures to locate potential raw material sources for the site.
In order to obtain a detailed spectral signature and detect

Spatial Resolution
Spatial resolution measures the smallest angular separation between two objects. For satellite images, this is represented in pixels and the spatial resolution for a given image is noted as how many meters that pixel represents. For example, the satellite SPOT 4’s multispectral scanner has a spatial resolution of 20m. This means that each individual, square pixel represents a spatial area of 400 square meters. There are instances in which pixel size and resolution are not the same, especially when multiple images are combined and the pixel sizes are averaged to represent a larger area.
In

A preview of the paper ‘Mapping a Subsurface Water Channel with X-Band and C-Band Synthetic Aperture Radar at the Iron Age Archaeological Site of ‘Uqdat al-Bakrah (Safah), Oman‘
The site of ‘Uqdat al-Bakrah was discovered in 2012 and yielded hundreds of Bronze objects. Along with the finds, the curious location at the edge of the Rub al-Khali sand dune desert piqued the interest of a number of archaeological teams.
The ArWHO team focuses on understanding the long-term role of water in Oman. We conducted a geophysical survey in 2017 and we were able to detect a channel-like feature. This is significant. Why? We not only learned a bit more about the paleo-environment, but we can work towards uncovering how the environment supported potential human activities at the site like charcoal production or metalworking.
What does this have to do with spatial resolution?
This study focuses on the methodology used to detect and map the channel-like feature our team discovered at ‘Uqdat al-Bakrah. The C- and X-bands have a shorter-wavelength than the commonly used L-band, BUT they have a higher spatial resolution. L-bands have the ability to penetrate more deeply into soils, but at shallow sandy sites like ‘Uqdat

Temporal Resolution
Temporal resolution refers to the frequency at which imagery is recorded for a particular area. For example, the MODIS satellite captures the same area every one to two days, while most Landsat satellites take images of the same area every 16 days.
Depending on the question or phenomenon being observed,
Radiometric Resolution
Radiometric resolution is the sensitivity of a remote sensing platform to detect slight differences in energy, specifically, radiant flux (radiant energy emitted per unit time).
Remote sensing platforms typically use either a passive or active sensor. Passive sensors record electromagnetic radiation, which is reflected from the earth’s surface. Active sensors coat the earth’s surface in machine-made electromagnetic energy and record the quantity of radiant flux that is emitted back to the sensor.
Check out this list of active and passive sensors.
Radiometric resolution is measured in bits (a number to the exponential power of 2) and the higher the number, the finer the radiometric resolution. For example, the first Landsat satellite has a 6-bit radiometric resolution; however, Landsat 4 and 5 have a finer radiometric resolution of 8 bits.
Radiometric resolution is a bit tricky to understand and I don’t have any explicitly archaeological examples clearly demonstrating this concept (if you do, let me know), but it is important.
Closing Thoughts
Is there one resolution to rule them all? At the moment, there is no way to maximize all four resolutions and, for this reason, trade-offs must be made. However, as this post hopefully demonstrated, resolutions are often entangled with one another.
When it comes to archaeological research, resolution considerations are important when selecting imagery for a given research question or project. Understanding how these concepts work will help you choose which remotely sensed imagery fits your archaeological research goals.
Have you used remotely sensed imagery in your research? Do you know great examples highlighting these concepts? Let me know in the comments section below!
