Geo Information Systems Part 1 Introduction and Overview Prof. Dr.-Ing. Raimar J. Scherer Institute of Construction Info

1. Geo Information SystemsPart 1 Introduction and OverviewProf. Dr.-Ing. Raimar J. SchererInstitute of Construction InformaticsDresden, 04.07.2006

2. Quality of engineering studies The quality of an engineering study is maximal as high as the quality of the used data base (input data). The loss of quality of an engineering study in relation to its maximal achievable quality is determined by the quality of the engineering model (approach), i.e. of the applied engineering knowledge quality of study quality of data wrong knowledge knowledge applied wrong data

3. Steps of Modelling The following steps of modelling are necessary in order to be able to calculate or simulate a scientific or engineering problem on a computer

4. Steps of Modelling • Given is a physical / engineering problem, e.g. the stream around a building and hence the wind exposure of a building • In order to solve the problem, one builds a physical model corresponding to the reality, e.g. linear vibration. The problem will be described qualitatively. • The physical model will be transformed to a mathematical model. Now the problem can be described quantitatively and is able to be solved objectively and comprehensively. • In principle, a computer is only able to carry out additions, i.e. all mathematical operations must be reduced to that. In case of a differentiation, this means that the derivative will be replaced by the difference quotient and hence the problem will be linearised. • In contrast to formal mathematics, computer provide only a finite number of numbers. There does not exist ∞, but only a largest INTEGER and a largest REAL number, e.g. 1E99=1099. Furthermore a floating point number can only comprise a finite number (usually 8, 16 or 32) of decimal places. This causes the need of rounding.

5. Model Errors • Model Error: The transition from reality to the mathematical model contains the Model Error, that arises e.g. by simplifications or approximations in order to make the problem solvable, e.g. by modelling a building as a linear oscillator. Model Errors often are also the consequence of the current state-of-the art, which may not afford a better model. • Methodological Error: Arises from the fact, that every mathematical operation must be traced back to additions. E.g. for finite element analysis this leads to a linear system of equations. • Rounding Error: Due to the transition from the infinite number of real numbers to the finite domain of floating-point numbers, each number must be truncated from a certain digit. This leads to an error in the last digit. If one has a complex physical system (e.g. multi-storey buildings) and hence a large mathematical system the number of operations is very high. Every operation causes a rounding error. The accumulation of these rounding errors can cause wrong results and maybe lead to uncertain interpretations.

6. Error Checking During a simulation the three kinds of errors mentioned above may add up. This leads to the question, how to check the results of a computer calculation. One possibility is to monitor the real model for some input values – as far as this is possible in reality – and compare them with the computed values • if these values are coincident, then the chance is high, that simulation errors are low, but it is also possible, that the different kind of errors erased mutually for the particular test case and hence errors are high for other cases • if there is no coincidence, at least one of the above mentioned errors occurred. The model error and methodological error can be checked analytically, i.e. error bounds can be specified. To check the rounding error, a special arithmetic of the computer is needed, which controls the rounding operation. This leads to the principle of interval computation, for which special computers are available.

7. Information System Definition An Information System is in its simplest form a request-response system based on a data source Data base Server data storage data mgmt. An Information System consists of • Data base • data storage • data management system • user interface • to formulate request • provides answers • data interface • acquisition of data • continuous updating of data standardized request response collection Clients individual adapted Applications • investigation • analysis • simulation scanning monitoring • representation: • graphical • alphanum.

8. Space Information System Definition It is an information system managing information of spacially distributed objects and the relationships between each other. Examples are • Facility Management Systems • Construction Side Management Systems • Production Management Systems, including Supply Chain Management (e.g. car production or airplain production) • car maut systems (toll collect in Germany) • Animal Monitoring Systems • Airspace Information Systems in particular information Systems for moving objects

9. Geo-Information System Definition It is an Information System, managing information of objects, which are part of the earth or which do have a strong relation to the earth, namely which are stationary, non-moving objects. The information are preferably to be managed through a "cartographic" representation, i.e. on a 2D basis. This means data management, as well as request and the representation of responses are outstanding good in cartographic from. Usually the information system do have a very high information density concerning the observed earth surface. Other representation forms are not excluded, but are complementary. Complementary representation forms are: • any statistical representation, bar chart, pie chart • cross section • digital terrain model in 3D with buildings • iso-lines of terrain, snow height, CO2 concentration

10. Example: Hurricane We have to distinguish between • Investigation of the hurricane  non – GISA hurricane is a moving object. Therefore it is not appropriate to manage the hurricane information by a GIS, but through a space information management system. The air and the objects in a hurricane are highly moving objects and even their relationships are highly time-dependent • Consequences of a hurricane  GISLooking on the consequences, we are only interested what happens with the objects on the earth, because of the hurricane. All those objects are stationary, non-time-dependent, hence it is appropriate to manage the information through GIS. We may only be interested in 2 time spots, namely before and after the hurricane. We are interested in the destructiveness zone of the hurricane and there in the strength of destructiveness, which can be represented by iso-lines (lines or coloured area), the priority of help, etc.

11. Investigationof the hurricane non – GIS Satellite picture of Hurricane Juan (2003)

12. Consequences of a hurricane  GIS Wind velocity in km/h SS: Saffir-Simpson-Hurricane Scale facility Path and damaged area after Hurricane Bertha (1996), USA During or after a natural disaster GIS helps to analyse the damage. Storm data (wind areas, fragility curves, etc.) may be associated and hence damage distributions can be estimated. Distribution of offshore business in the Gulf of Mexico. Overlaying simulated hurricanes’ wind speeds gives an indication of the exploration fields and offshore structures that will be most seriously affected and the losses that are to be expected.

13. Map-orientation, Space relations GIS is a cartographic, i.e. map-oriented representation and hence a 2D representation. Therefore one of its big advantages is the layer structure. This contrasts with the modern (3D) design and configuration systems, where an aggregation (assembly) structure is prefered. GIS is hence very geometric-centred. The necessary space relation will be achieved through • primary metric • a 2D co-ordination system • secondary metric • parameters (postal codes, code numbers (phone), district numbers, premises numbers) • names (name of town, boundary, lea) • addresses

14. Space relation through primary and secundary metrics 40 31 50 30 60 1 20 61 75 80 70 a) Coordinates b) District Numbers c) Names of Streets Public Services Dresden Type of Report: Wires - overview Date: 3rd February 1991 District: 1 Street: Kurvenstraße d) Addresses • Glock Manfred 75 Isegrimmweg 25 2 44 72 10 • Glock Udo 1 Filder-29 6 59 10 25 • Glocke Eckhard 0 Heuweg 9A 77 92 15 • - Gerhard 70 Reginen-44 77 19 20 • -Karl-Josef 70 Welfen-66B 4 93 27 11 • Glockenbring Gerhard 1 Schellberg-34 2 64 54 55 • Glocker H. 50 Einstein-29 62 66 23 • Thomas 1 Herder-9 57 91 69 • Glockgether Erika 70 Im Asemwald 28 76 75 81

17. Themes The information of the themes are stored in the attributes of the geo-objects Basic themessecondary metric like: • ownership (real estate register) • digital terrain (data from land surveying office) Visual themes Any information that is acquirable from light, i.e. photography (scanning) and also infrared (heat). This is often represented by false colour representation. Artificial themes • Deduced values • Interpolated values • Simulated values All values not acquirable via light and neither by computation but have to be obtained by inspection are very expensive due to the dense information need. This means they are neither sufficently dense nor sufficently up-to-date.

18. Example for Themes

19. Example for Themes 300 295 290 285 280 275 270 265 260 streets and property boarders building stock toxicity from traffic topography traffic density

20. Overlaid Themes 300 295 290 285 280 275 270 265 260 • We eye inspection we recognized from the overlaid themes, why the concentration of CO2 is • at the street crossing • Extending only into 2 of the 3 streets • We recognize also that there is an anomaly, because the centre of CO2 is not coincide with the crossing center, but show some shift to the right. This is either (1) the typical overlay error (not fitting coordinates)or (2) due to other influences like air movement, a theme not taking in consideration. • Final Goal: • Such recognition should be possible with algorithms

21. Advanced benefit of GIS GIS is more than an information system. It is used to deduce new information from the documented information (facts) through (1) empirical analysis:recognition of relations between the different themes by - eye analysis - statistical analysis (correlation) - data mining Problem: What should be compared point to point information area to area , point to area information? (2) theoretical analysis / simulationthe documented information is used together with- physical- technical- sociological- psychologicalmodels to produce new information (3) An advanced GUI to an information system (request-response system), with very powerful graphical presentation techniques

22. Requirements of GIS • Ability to manage large amount of heterogeneous data which are related to points (and areas) • possibility to request the data in relation to their existence (inventorial), location and themes • combination of requests • derive of new information through combining different theme information via the available space relation (primary, secondary metric) • deduce of new information through • classificationbuilding new sub areas (clusters) in order to enhance homogeneity (pre-condition for the quality of statistical analysis) • correlationrecognition of trends, e.g. space and azimuth depend chances(e.g. earthquake damage patterns) • combination of 5.1 + 5.2trends based on representative values of sub areas (not points) such as mean, extreme, fractal values

23. Classes of GIS(1) Real estate information systems Use: Management of properties and assets = land registry (real estate cataster?) basis: coordinate systems (however, there are several in use in parallel) M 1:500 – 10'000 (large scale) Sometimes extended to M1:100'000 in order to add topography Remark: scale is important, because determines the needed density of data Information: • ownership • cataster charges and restrictions • Debits, loans Geometry • only vector data (due to preciseness) Functionality: • acquisition, management, presentation • high security • high actuality

24. Classes of GIS(2) Space Information Systems Use: Land development and space planning M 1:10'000 – 1'000'000 (middle-small scale) Information: • population, economy • settlement, infrastructure • use of land and resources Functionality: • acquisition, management, presentation • analysis • simulation • free surface modelling Geometry: • vector • hybrid (vector + raster) • 2D – 2.5D

25. Classes of GIS(3) Environmental Information Systems Use: Space-, time- and content-dependent data for the description of the status of the environment and its future development M 1:10'000 – 1'000'000 (middle-small scale) Information: • any environmental information Functionality: • acquisition, management, presentation • analysis • simulation • time-dependent data Geometry: • Vector • hybrid • 2.5D – 3D

26. Classes of GIS(4) net information systems Use: management of production support material like • supply lines and plants (e.g. water, energy, gas, oil, waste) • costumer data (supply of components, logistic, the supply chain of productions) M 1:100'000 – 10'000'000 (very small scale) M 1:1'000 – 10'000 (large scale), e.g. in a plant Information • supplied good • logistic data (where, when, velocity) Function • acquisition, management, presentation • net analysis (shortest path, fastest path, location, ...) Geometry: • Vector • 2.5D

27. Classes of GIS(5) specific domain information system Use: - Navigation: ship, airplane - telecommunication etc.