Relationship between Systems Engineering and Geospatial/Geodetic Engineering

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Lead Author: Ulrich Lenk

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This article discusses the relationship between Systems Engineering (SE) and Geospatial/Geodetic Engineering (GGE) as reflected through relationships between several Specialty Engineering disciplines listed in INCOSE (2015) and GGE. There are SEBoK articles in the Knowledge Areas SE and Quality Attributes for most of the disciplines discussed here as well.

Geospatial Aspects in the INCOSE Specialty Engineering Activities and Modeling and Simulation

It is clear that systems that directly include geospatial components/system elements, or that perform navigation operations or deal with referenceable objects in their broadest interpretations require dedicated contributions from the geodetic and geospatial domain, which must be achieved by integrating respective subject matter expertise into SE teams. It is not the intention here to emphasize the need to provide resilient services that are needed by critical infrastructures that are used by all systems, such as power supply and communication. For critical functionalities in systems, respective back-ups need to be in place, such as uninterrupted power supply (UPS) and alternative means of communication that do not rely on PNT services. This must be considered appropriately in the overall system design. Beyond this, with regard to the dedicated Specialty Engineering activities identified by INCOSE (2015), the following sections briefly describe possible geospatial solutions or contributions which may directly support some of the Specialty Engineering activities in particular.

Environmental Engineering/Impact Analysis

Within (environmental) impact analysis, as soon as it comes to a spatial distribution/dispersal of pollutants, this is typically achieved on the basis of specific, partly scientific modules integrated in GIS, such as plume modeling that estimates how chemicals dissolve in the atmosphere under certain meteorological conditions. Other applications include run-off determination for flooding simulations, or dependencies between different types of environmental parameters as may be revealed during geospatial analysis, etc.

Interoperability Analysis

As described above, interoperability has been a major issue in geospatial infrastructures for decades. The OGC was founded in 1994 and the first standard (OpenGIS Simple Features Specification) published by OGC dates back to 1997. But not only OGC is active in the geospatial domain. Other standardization organizations like ISO with its Technical Committee 211 Geographic information/Geomatics, the International Hydrographic Organization (IHO) and NATO publish geospatial standards, and typically there is a close cooperation between these bodies. Besides the numerous currently available standards, it is also interesting from a cost perspective that the use of (geospatial) standards provides for significant cost savings in the development and operation of systems and thus contributes as well to the first topic of the Specialty Engineering activities, the Affordability/Cost-Effectiveness/Life Cycle Cost Analysis. NASA funded a study that was conducted by Booz Allen Hamilton (2005). In short, one result of the study was that the project that adopted and implemented geospatial interoperability standards:

• had a risk-adjusted Return on Investment (ROI) of 119.0%. This ROI is a “Savings to Investment” ratio over the 5-year project life cycle.
• had a risk-adjusted Return on Investment (ROI) of 163.0% over a 10-year period.
• saved 26.2% compared to the project that relied upon a proprietary standard.

Another finding was that standards-based projects have lower maintenance and operation costs than those relying exclusively on proprietary products for data exchange. As a general conclusion from the above, there are substantial contributions from the geospatial domain that support interoperability analyses.

Logistics Engineering

According to INCOSE (2015), “Logistics engineering … is the engineering discipline concerned with the identification, acquisition, procurement, and provisioning of all support resources required to sustain operation and maintenance of a system.” Amongst others, the following elements supporting logistics engineering are identified in (INCOSE 2015) that have a direct relation to geospatial, GIS and PNT/GNSS technologies:

• Sustaining engineering;
• Training and training support;
• Supply support;
• Facilities and infrastructures; and
• Packaging, handling, storage, and transportation (PHS&T).

Typical keywords associated with related activities are:

• “Technical surveillance” where, e.g., fielded systems are monitored with means of geodetic engineering techniques, such as deformation analysis of structures and sites,
• “Simulation” that requires virtual 3D environments and GIS,
• “Facilities” that are nowadays managed with Building Information Modeling (BIM) techniques which have a close connection to GIS,
• “Transfer” and “transportation” where objects, material and goods are moved in space involving amongst others GIS with navigable maps used for planning routes and navigation during transport.

Sometimes, GNSS and real-time GIS technologies are also used for tracking cargo of interest for safety reasons.

Reliability, Availability, and Maintainability

How reliable is a map, or, in the digitized world, a geospatial data set displayed on screen or a mobile device? This is directly related to the necessity of updating geospatial databases according to the operational requirements. Updating and thus maintaining (cf. maintainability) geospatial databases is a costly and sometimes time-consuming operation (cf. again the Specialty Engineering activity “Affordability/Cost-Effectiveness/Life Cycle Cost Analysis”). Efficient updating of geospatial databases themselves from a technical perspective is discussed amongst others in (Peters 2012) and, at least to a certain extent, must be reflected as well in the design of a geospatial data infrastructure. The use of central services for the provision of geospatial data is one possibility to address this issue since then, only one set of data needs to be updated and all others access this data set via services to receive at any time the latest version of available data. The required availability constraints clearly must be addressed in the design of the IT infrastructure that hosts the geospatial database.

Resilience Engineering

In recent years there has been an increasing awareness of the vulnerabilities of systems depending on GPS. Resilient PNT is heavily discussed and alternatives like eLoran and Satelles are often mentioned in this context. According to the (Royal Academy of Engineering 2013), “all critical infrastructure and safety critical systems that require accurate GNSS derived time and or timing should be specified to operate with holdover technology for up to three days.” This source also lists other recommendations to be considered for system design. A source that provides example cases on a regular basis is the [Resilient Navigation and Timing Foundation https://rntfnd.org/](RNT Foundation). Examples of official reports in the US and the UK are also Wallischeck (2016) and Royal Academy of Engineering (2011). Jamming and GPS disruptions occur in reality and sometimes even official warnings are issued, e.g. by the US Coast Guard (DHS 2016). [According to the RNT Foundation https://rntfnd.org/2017/07/28/g20-jams-gps/], there was an official warning from the flight authorities during the G20 event in Hamburg, Germany in 2017 to consider the possibility of GPS disruptions caused by intentionally initiated activities and actions to protect the G20 conference. Thus, prudent System Engineers consider these dependencies and make sure that the systems at hand are fault tolerant, i.e. that they do not terminate safe and reliable operation in absence of GNSS signals, or cause major problems when they continue to communicate with other systems.

System Safety Engineering

Although it may not be straightforward, even in System Safety Engineering there are aspects that may be supported by geodetic and surveying engineering. One example may be the monitoring of buildings, i.e. to what extent constructions move under what environmental conditions, especially wind. Another example is the monitoring of natural objects such as volcanoes or slopes to detect the possibility of future volcanic eruptions or potential landslides early.

Usability Analysis/Human Systems Integration

As geographical displays sometimes form a central part in user interfaces and as it could be shown above that spatial data have special aspects to be considered, also in the user interface design, the usability analysis and other aspects of Human Systems Integration (all of these activities are part of Human Factors Engineering, HFE) geospatial expertise may be required for respective systems. But clearly beyond this, in HFE several other aspects are considered as well covering the general interaction of users with systems, cf. (Stanton et al. 2013). Nevertheless, in that particular sense of displaying (virtual) environments HFE is related as well to the science and application of cartography (Kraak and Ormeling 2020) since the latter deals heavily with the different ways of human perception of spatial phenomena.

Modeling and Simulation

Modeling and simulation is a broad field and heavily used in various disciplines and as such also in different SE life cycle processes. Geospatial technologies contribute to these activities amongst others by providing data to create realistic environments, either for 2- or 3-dimensional applications. According to (INCOSE 2015), such a model is then termed a “formal geometric model”. While considering as well temporal aspects and phenomena, also 4-dimensional models are in use. From a conceptual aspect it has to be distinguished what types of geographic information are being modeled, whether they are discrete objects which can be delimited with boundaries or whether they are continuous fields representing “the real world as a finite number of variables, each one defined at every possible position” (Longley et al. 2015), like temperature. For brevity reasons it cannot be the aim to provide in this context a comprehensive introduction into the general theory of geographic representation in GIS with continuous field and discrete objects and how these concepts may be integrated. For this purpose the reader is referred to (Longley et al. 2015), (Goodchild et al. 2007) and (Worboys and Duckham 2004). In this frame the level of discussion is restricted to a more user oriented perspective of geographic information like it is given by classic traditional maps and applications commonly used by the public, like Google Maps/Earth. In traditional cartography a map model was described by the well-known map legend that explained the different features or phenomena depicted. Fairly straightforward models for perspective visualization of landscapes are nowadays created by using so-called Digital Terrain Models (DTM) and rendering them with geospatial imagery while with these types of models, no further descriptive information may be extracted besides the geometric information and the visual interpretation of the imagery to derive what there actually is at this location. A well-known application for this is Google Earth. To provide more information, this is achieved by vector models, and (discrete) objects in a vector model may be further described by attributes (e.g. width of a street). Vector models are created on the basis of so-called “feature catalogues” that define what real world objects with what attributes including their domain values are to be represented. A typical military feature catalogue was created by the Defence Geospatial Information Working Group (DGIWG) for worldwide military mapping projects and is called the DGIWG Feature Data Dictionary ([DFDD https://www.dgiwg.org/FAD/overview.jsp]). Feature catalogues vary with different levels of modeling scales, i.e. large scale models provide a higher granularity than small scale models that serve more overview purposes. INCOSE (2015) lists the following purposes that models can serve throughout the system life cycle:

• Characterizing an existing system,
• Mission and system concept formulation and evaluation,
• System architecture design and requirements flow-down,
• Support for systems integration and verification,
• Support for training, and
• Knowledge capture and system design evolution.

Within these different purposes of models in particular the “mission and system concept formulation and evaluation” as well as the “support for training” may be supported by geospatial technologies by providing data and also software components in order to create, store, simulate and visualize real world or virtual models of environments where a system is going to be deployed, or where operations are going to take place (e.g. (Tolk 2012)). “Mission and system concept formulation and evaluation” are related to the definition of the Concept of Operation (ConOPS). By analyzing different variants of system deployment and categorizing them based on defined cost functions it is possible to optimize a system design to provide a solid basis for decision making.

Geospatial Aspects in INCOSE's Cross-Cutting Systems Engineering Methods and Specialty Engineering Activities

Systems Engineering and “architecture definition activities include optimization to obtain a balance among architectural characteristics and acceptable risks. Certain analyses such as performance, efficiency, maintainability, and cost are required to get sufficient data that characterize the global or detailed behavior of the candidate architectures with respect to the stakeholder and system requirements” (INCOSE 2015). Looking at the dedicated Specialty Engineering activities from (INCOSE 2015) and at the plethora of geodetic and geospatial technologies and services available, at least the following Specialty Engineering activities can benefit in particular from Geospatial Engineering activities or need to include respective geospatial considerations.

• Environmental Engineering/Impact Analysis

• Interoperability Analysis

• Logistics Engineering

• Reliability, Availability, and Maintainability

• Resilience Engineering

• System Safety Engineering

• Usability Analysis/Human Systems Integration

INCOSE (2015) also lists so called Cross-Cutting Systems Engineering Methods, including Modeling and Simulation, which are also heavily related to geospatial and GIS technology. The next section will shed more light on potential geospatial contributions to these dedicated activities.

Conclusions

As shown above, geodetic and geospatial technologies and services play a fundamental role in a lot of systems of systems and stand-alone systems. People and the general public are often not aware to what enormous extent their lives and/or activities are dependent on these assets that support national critical infrastructures, including utilities and communication by providing and maintaining reference frames, data and services etc. Against this background the Geospatial/Geodetic Engineering knowledge area would like to raise the awareness within the SE community that respective professional expertise should be consulted in SE processes at an early stage. It is also recommended to make this explicit by including some dedicated subsections in handbooks and guidelines for SE and its supporting disciplines, like it is done for other specialty disciplines in (INCOSE 2015). The next section Further Insights into Geospatial/Geodetic Engineering will provide more details on Geospatial and Geodetic Engineering and respective sources of information, with an emphasis on reliable internet sources for ease of access to the information.

References

Primary References

INCOSE. 2015. Systems Engineering Handbook: A Guide for System Life Cycle Processes and Activities, (4th edition). San Diego, CA, USA: International Council on Systems Engineering (INCOSE), INCOSE-TP-2003-002-04. Kraak, M.-J. and F. J. Ormeling. 2020. Cartography: Visualization of Geospatial Data, (4th edition). London, New York: Taylor & Francis. Longley, P.A., M.F. Goodchild, D.J. Maguire, and D.W. Rhind. 2015. Geographic Information Science and Systems, (4th edition). New York, Chichester, Weinheim: John Wiley & Sons, Inc. Peters, D. 2012. Building a GIS: Geographic Information System Planning for Managers, (2nd edition). Redlands, CA: Esri Press.

Works Cited

Booz Allen Hamilton. 2005. Geospatial Interoperability Return on Investment Study. NASA Geospatial Interoperability Office, April 2005. Royal Academy of Engineering. 2013. Extreme space weather: impacts on engineered systems and infrastructure. London, UK, Royal Academy of Engineering. Royal Academy of Engineering. 2011. Global Navigation Space Systems: reliance and vulnerabilities. London, UK, Royal Academy of Engineering. DHS 2016. US Department of Homeland Security, US Coast Guard, Safety Alert 01-16 Global Navigation Satellite Systems – Trust, But Verify. Washington, DC, January 19, 2016. Stanton, N.A., P.M. Salmon, L.A. Rafferty,‎ G.H. Walker, and Chr. Baber. 2013. Human Factors Methods: A Practical Guide for Engineering and Design, (2nd edition). Farnham: Ashgate Publishing Limited. Tolk, A. 2012. Engineering Principles of Combat Modeling and Distributed Simulation. Hoboken, New Jersey: John Wiley & Sons, Inc. Goodchild, M.F., M. Yuan and Th.J. Cova. 2007 “Towards a general theory of geographic representation in GIS.” International Journal of Geographical Information Science, 21(3):239-260. Wallischeck, E. 2016. GPS Dependencies in the Transportation Sector. Cambridge, MA: U.S. Department of Transportation, Office of the Assistant Secretary for Research and Technology, John A Volpe National Transportation Systems Center. Worboys, M.F., M. Duckham. 2004. GIS: A Computing Perspective, (2nd edition). Bristol, PA: Taylor & Francis.

Additional References

None.

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