When defence and security organisations discuss how satellite imagery can be of benefit, resolution tends to be an important part of the conversation. Those with a degree of technical knowledge will understand the significance of the National Image Interpretability Rating Scale, commonly known as NIIRS, and how this can affect what a defence analyst can actually see on the ground in satellite intelligence.
The NIIRS provides a framework for describing image quality according to the types of features, objects and activities that can be interpreted from the image. NIIRS connects image quality with real observation tasks. For defence, security and intelligence organisations, this provides a much clearer way to assess whether satellite imagery is capable of answering a specific operational or intelligence question.
Understanding the NIIRS scale for defence and intelligence
NIIRS provides a scale indicating how interpretable an image is.
The scale typically runs from NIIRS 0, where meaningful interpretation is prevented by very poor image quality or obscuration, through to NIIRS 9, where extremely fine details can potentially be identified.
Public NIIRS guidance includes representative tasks associated with different levels of image quality. These range from detecting major infrastructure at lower levels through to distinguishing specific equipment features at higher levels.
The scale is relevant for the defence sector. Instead of assessing whether a satellite provides data at a particular spatial resolution, it helps analysts consider whether the image is likely to provide enough detail to detect, recognise or identify the feature they are interested in.
What can different NIIRS levels reveal?
The value of NIIRS becomes clearer when looking at what different levels of satellite imagery analysis can support.
At lower NIIRS levels, analysts may be able to detect large infrastructure or recognise broad patterns of activity. Public NIIRS guidance associates NIIRS 2 data, for example, with tasks including detecting large hangars at airfields, identifying military training areas and detecting large buildings at naval facilities.
At NIIRS 4, considerably more detail becomes available. Representative tasks include identifying large fighter aircraft by type, detecting large radar antennas and identifying tracked vehicles or field artillery by general type when viewed in groups.
At NIIRS 5, analysts may be able to distinguish more specific equipment characteristics. Examples include identifying radar as vehicle mounted or trailer mounted and recognising certain deployed tactical missile systems by type.
At NIIRS 6 and 7, finer distinctions become possible. Published examples include differentiating between helicopter models, examining antenna shapes and identifying specific features associated with vehicles, aircraft and military infrastructure.
For anyone assessing NIIRS for defence applications, these differences are significant.
Detecting that activity is taking place at an airfield is one requirement. Determining the type of aircraft present is another. Identifying a particular equipment configuration requires a further increase in image interpretability.
The required quality of data should be driven by the intelligence question at hand.
Why satellite resolution alone doesn’t guarantee intelligence value
Higher spatial resolution does not automatically mean better intelligence.
Two images with similar ground resolution can provide different levels of interpretability. Sharpness, contrast, atmospheric conditions, viewing geometry, signal quality and image processing can all influence what an analyst is able to extract from the scene.
NIIRS takes resolution into account but it is fundamentally about usable image quality.
Historic guidance does associate different NIIRS levels with approximate ranges of ground resolved distance, but the relationship is not absolute. Models such as the General Image Quality Equation consider several characteristics of an imaging system when estimating NIIRS, including ground sample distance, sharpness and signal to noise performance.
A headline resolution figure alone cannot guarantee that an image will answer the intelligence question being asked.
Using NIIRS for defence intelligence requirements
Satellite data is collected by the defence industry to answer specific questions such as:
- Is activity increasing at a military airfield?
- Has equipment appeared at a previously inactive site?
- What type of aircraft or vehicle is present?
- Has new infrastructure been constructed?
- Is an installation changing over time?
These questions require different levels of data interpretability and NIIRS provides a useful framework for translating an operational requirement into an image quality requirement.
This can also stop organisations paying for higher resolution than a task actually needs. Wide area monitoring may place greater value on coverage and collection frequency. Detailed identification of equipment may require much finer commercial satellite data. Some intelligence requirements may also be better supported by synthetic aperture radar, infrared or multispectral data.
The sensor and data specification should follow the mission.
For defence users working with commercial satellite data, the NIIRS provides a useful measure of data application and usefulness. The highest-resolution image is not always the most useful one; the most useful is the one that answers the question the analyst is actually asking.
