The Proposed Temporal Imagery Interpretability Rating Scale

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Developing a new interpretability scale to adapt to the evolution of
satellite imaging

This blog
post was written by Dr. Peter Wegner, chief strategy officer at
Spaceflight
Industries
, and
originally published in SatNews. You can find the original article
here.

As a geospatial intelligence company, BlackSky provides analytics
products and services to customers worldwide. Our mission is to share timely
and relevant insights about places, events, and assets that are critical to
operations and decisions.

To garner timely insights, we are developing and launching a
satellite constellation that provides high revisit imagery over the world’s
most important geographies, delivering unique observations throughout the day
as well as improved situational awareness and predictive analytics for
forecasting or anticipating events on a global scale.

This is a new approach to satellite imaging and data collection. What
it uncovers differs from traditional satellites imaging. Historically,
constellations haven’t provided multiple visits a day to one location, tracking
changes and developments over a short period of time. As such there is no
well-defined, industry standard to measure and analyze the imagery collected
for the purpose of global monitoring.

Drawing inspiration from the current scaling system, the National Imagery Interpretability
Rating Scale
(NIIRS), we at BlackSky propose the introduction of a new scale: The
Temporal Imagery Interpretability Rating Scale. This new scale will help the
industry define and classify data and imagery being collected in the NewSpace
era of smallsats and big data.

The History
of the NIIRS Scale

In April 1972 an ad hoc team of U.S. Intelligence Community
members was formed to devise a means of measuring and accounting for areas
searched using satellite imagery with an emphasis on recording the interpretability
and quality of the imagery used in the search. Out of this work, in March 1973
a specialized imagery interpretability rating scale, NIIRS, was introduced.

The NIIRS scale defines different levels of image
quality and interpretability based on the types of tasks an analyst can perform
with images, the higher the rating, the higher the quality of the imagery. The NIIRS
scale has become a well-known and widely used tool to characterize the
interpretability of satellite imagery and has provided imagery analysts and
consumers of satellite imagery a simple, easy-to-use, yet powerful tool to
assess, describe, and share satellite imagery. 

The
Evolution of Data Collected

For much of the history of commercial spaceflight, high-resolution
satellite imagery has not been widely accessible. The cost to build, launch,
and operate a single high-resolution imaging satellite could reach (and exceed)
half-a-billion dollars! Given the significant capital investment, access to high-resolution
satellite imagery was limited to a very select group of government customers
and large multi-national corporations, and even for those customers it would be
rare to get imagery of a specific site more than once per day.

The advent of small satellite systems, low-cost launch
capabilities, and high-speed cloud processing technologies has ushered in a new
generation of low-cost, high-resolution satellite imaging constellations that
are able to collect multiple images of a given target each day, and in some cases,
 they can provide multiple images within
an hour! This enables a new level of temporal information to be extracted from
satellite imagery; that is persistent change detection and monitoring of
time-critical activities.

The
(Proposed) Temporal Imagery Interpretability Rating Scale (TIIRS)

Today there is no common, well-defined means for analysts to
measure and account for the temporal information contained within a set of
satellite images collected from a single target over a period of time with a
given frequency. The industry could benefit from the development of a new
system: Temporal Imagery Interpretability Rating Scale.

This scale would be leveraged as a mechanism to define different levels of temporal information that can
be extracted from a set (or stack) of satellite images collected over a certain
frequency of time. This TIIRS scale would be based on the types of temporal
information an analyst can discern with a set of images collected with a given
frequency (or TIIRS rating). 

The use of a TIIRS scale would allow imagery analysts and
consumers to define the level of persistence needed to answer specific
questions or to monitor critical activities. For example, a TIIRS-3 level of
monitoring would enable an imagery consumer to determine quarterly output from
a large surface coal mine, whereas a TIIRS-7 level of monitoring would allow a
retail corporation to monitor the number of cars in the parking lot of each
critical store location on an hourly basis. Just as with the NIIRS Scale, the
TIIRS Scale can be broken down into smaller increments. For example, imagery
collected a frequency of TIIRS-5.5 would correspond to an image collected every
4 days. 

A notional TIIRS rating scale is shown below:

TIIRS Rating Level Civilian Terrestrial ExampleFrequency of time between collections
0Unable to collect imageryImagery never collected
1It is possible to detect changes in forest health, land erosion, and urban sprawl>10 years
2It is possible to detect new facility construction1-10 years
3It is possible to determine crop health, annual population surveys, and quarterly industrial output and commodities production1 month – 1 year
4It is possible to detect monthly changes in oil storage, monthly industrial output and commodities production1 week – 1 month
5It is possible to detect movement of ships into and out of major ports1 day – 1 week
6It is possible to count cars in parking lots to determine daily retail throughput1 hour – 1 day
7

It is possible to track cars in a busy urban setting1 min – 1 hour
8It is possible to track moving aircraft in a scene1 sec – 1 min
9It is possible to detect an explosion< 1 second

Utility of a Combined NIIRS Scale and TIIRS Scale

With the combination of the NIIRS scale and the proposed TIIRS
scale, future imagery analysts and consumers could more efficiently describe
the level of persistent monitoring and corresponding imagery resolution needed
to solve a specific intelligence problem. For example, to count the specific
number of vehicles in a Home Depot parking lot every hour an imagery customer
may specify images with a resolution rating of NIIRS-5 with a collection
frequency of TIIRS-7.  

 Conclusion

The introduction of the NIIRS Scale offered a tremendous advantage
to imagery analysts and consumers as a mechanism to describe the utility of
satellite imagery of varying resolution. The emergence of large constellations
of small, low-cost imaging satellites adds a new dimension to the satellite
imaging industry. This new dimension is the value of imagery collected with
varying levels of frequency; sometimes referred to as the time value of
imagery. The TIIRS Scale provides a means for future imagery analysts and
consumers to compare, contrast, discuss, and categorize the value of imagery
collected at various frequencies.