Quality Assurance Framework for Earth Observation (QA4EO)
If the vision of GEOSS is to be achieved, Quality Indicators (QIs)
should be ascribed to data and, in particular, to delivered information
products, at each stage of the data processing chain from collection
and processing to delivery. A QI should provide sufficient information
to allow all users to readily evaluate a product’s suitability
for their particular application, i.e. its “fitness for purpose”. To
ensure that this process is internationally harmonised and consistent,
the QI needs to be based on a documented and quantifiable
assessment of evidence demonstrating the level of traceability to
internationally agreed (where possible SI) reference standards. Such
standards may be manmade, natural or intrinsic in nature. The documented
evidence should include a description of the processes
used, together with an uncertainty budget (or other appropriate
quality performance measure).
The guidelines of QA4EO provide a template and guidance on how to achieve this in a harmonised and robust manner.
One of the key guiding principles of QA4EO is appropriateness underlain
by a community desire to:
● Achieve consistency amongst peers,
● Provide advice and training for newcomers,
● Provide transparency of approach, and
● Improve efficiency.
The QA4EO process and its implementation should NOT be judgemental, bureaucratic or costly.
The Quality Assurance Framework for Earth Observation consists
of ten distinct key guidelines linked through an overarching document
- the GUIDELINES FRAMEWORK.
The naming convention of
the guideline documentation is fully explained in guideline QA4EOQAEO-
GEN-CEK-001 and collates the guidelines in terms of more
specific functions, e.g. Data Quality (DQ), Data Policy (DP) and Communication
and Education (CE). Guideline QA4EO-QAEO-GEN-DQK-
002 (“A guide to content of a documentary procedure to meet the
Quality Assurance requirements of GEO”) is essentially the core requirement
If processes are carried out in
full compliance of this fundamental guide, a user can have confidence
in any resultant output. QA4EO-QAEO-GEN-DQK-002 provides
the template to guide the user through the process, aided by the
other nine key guidelines for specific technical details, but in principle
this guide provides all the information needed to be compliant.
In considering issues of interoperability and international harmonisation
within any specific GEO community it is
often helpful to start with a review of generic activities and from
these define key requirements that drive the QA process. For example,
in the space sector all derived information products originate
from a measurement made by a satellite sensor. Thus, a set of key
activities for every sensor could be defined for implementation during
its development and operation. Guideline QA4EO-QAEO-GENDQK-
001 provides this satellite-based example to illustrate the
This example shows how the top level requirements drive
the need for community references, indicate critical generic deliverables
for bias evaluation through comparisons and act as a starting
point for more detailed technical procedures to underpin the top level
[Figure 3] Schematic summary of the data
quality aspects of the QA4EO process
Quality Indicators: a means of providing a user of data
or derived product (which is the result of a process) with
sufficient information to assess its suitability for a particular
This information should be based on a
quantitative assessment of its traceability to an agreed reference
or measurement standard (ideally SI), but can be
presented as numeric or a text descriptor, providing the
quantitative linkage is defined.
Traceability: property of a measurement result whereby
the result can be related to a reference through a documented
unbroken chain of calibrations each contributing to
the measurement uncertainty.
Reference (measurement) standard: realisation of the
definition of a given quantity, ideally with a stated uncer
tainty, which can be used as a reference; it can be individual
or community defined.
Uncertainty: non-negative parameter characterising the
dispersion of the quantity values that are being attributed
to a measurand (quantity), based on the information used.
Where possible this should be derived from an experimental
evaluation but can also be an estimate based on other
information, e.g. experience.