State of the Art and Future Trends in Geoinformatics Gerhard Navratil

Slides:



Advertisements
Similar presentations
Combining OS and OSM Data - A Case Study for geospatial data integration Name: Du Heshan Supervisor: Dr Suchith Anand.
Advertisements

WFM 6202: Remote Sensing and GIS in Water Management
1 Survey Technology. Data Collection Tools Available in the Market 1. Paper Survey 2. Smart Paper 3. Cell Phones 4. Personal Digital Assistants - PDAs.
Case Study: T-Mobile Retail Personal Coverage Check Kiosk Joe Wong, Integral GIS Sean Alexis, T-Mobile April 18, 2007.
Geospatial Technologies Used in Land Administration Kevin Daugherty Land Administration Solutions Manager Geospatial World Forum Rotterdam, Netherlands.
Topographic mapping in Fiji: Challenges and opportunities Conway Pene 2012 Pacific GIS&RS Conference November 2012, Suva.
1.Data categorization 2.Information 3.Knowledge 4.Wisdom 5.Social understanding Which of the following requires a firm to expend resources to organize.
25/11/2013 A method to automatically identify road centerlines from georeferenced smartphone data XIV Brazilian Symposium on GeoInformatics (GEOINFO 2013)
Geographical Information Systems and Science Longley P A, Goodchild M F, Maguire D J, Rhind D W (2001) John Wiley and Sons Ltd 1. Systems, Science and.
Maintainable 3D Models of Cities Gerhard NAVRATIL Rizwan BULBUL Andrew U. Frank Vienna University of Technology Institute of Geoinformation and Cartography.
GI Systems and Science January 30, Points to Cover  Recap of what we covered so far  A concept of database Database Management System (DBMS) 
Collection Development Policies for Digital Maps and Geospatial Information Princeton University Library NGDA Collections Workshop Stanford University.
Introduction to Cartography GEOG 2016 E
Geographic Information Systems and Science SECOND EDITION Paul A. Longley, Michael F. Goodchild, David J. Maguire, David W. Rhind © 2005 John Wiley and.
GIS Overview. What is GIS? GIS is an information system that allows for capture, storage, retrieval, analysis and display of spatial data.
WFM 6202: Remote Sensing and GIS in Water Management © Dr. Akm Saiful IslamDr. Akm Saiful Islam WFM 6202: Remote Sensing and GIS in Water Management Dr.
Geographic Information Systems
Geographic Information Systems and Science SECOND EDITION Paul A. Longley, Michael F. Goodchild, David J. Maguire, David W. Rhind © 2005 John Wiley and.
What do I (an ISE professional) need to be able to do-understand Need to understand the computer tools available to help me do my job better Need to understand.
NPS Introduction to GIS: Lecture 1
USING GIS TO FOSTER DATA SHARING AND COMMUNICATION SEAN MURPHY IVS BURLINGTON, VT.
What is a GIS? F 1.2 Getting Started F 1.2 Some Definitions of GIS F 1.3A Brief History of GIS F 1.4 Sources of Information on GIS.
Spatial Data: Elements, Levels and Types. Spatial Data: What GIS Uses Bigfoot Sightings: Spatial Data.
Kurt Menke, GISP OpenStreetMap. What is it? OpenStreetMap (OSM) Not software It's a collaborative project to create a free & editable map of the world.
9. GIS Data Collection.
Data Acquisition Lecture 8. Data Sources  Data Transfer  Getting data from the internet and importing  Data Collection  One of the most expensive.
Introduction to GIS fGRG360G – Summer Geographic Information System Text Computer system GIS software Brainware Infrastructure Ray Hardware Software.
Spatial data Visualization spatial data Ruslan Bobov
Intro. To GIS Lecture 4 Data: data storage, creation & editing
GEOMATICS AND GEOINFORMATICS IN MODERN INFORMATION SOCIETY PROJECTION OF NEW TRENDS INTO THEIR CURRICULA AT THE UNIVERSITY OF WEST BOHEMIA IN PILSEN Jiří.
The Geographer’s Tools
GIS Lecture 1 Introduction to GIS Buildings. Poly Streams, Line Wells, Point Roads, Line Zoning,Poly MAP SHEETS.
Prepared by: Jennifer McKee With support from: in partnership with: Introduction to ArcPad NSF DUE
Spatial data models (types)
GROUP 4 FATIN NUR HAFIZAH MULLAI J.DHANNIYA FARAH AN-NUR MOHAMAD AZUWAN LAU WAN YEE.
INFORMATION TECHNOLOGY IN BUSINESS AND SOCIETY SESSION 21 – LOCATION-BASED SERVICES SEAN J. TAYLOR.
Ref: Geographic Information System and Science, By Hoeung Rathsokha, MSCIM GIS and Remote Sensing WHAT.
Software development. Chapter 1 – What is software development?
GIS is composed of layers Layers –land/water –roads –urban areas –pollution levels Data can be represented by VECTORS, or Data can be represented by RASTERS.
Teaching with Multimedia and Hypermedia
Standardization and Research Prof. Dr. Christine Giger Swiss Federal Institute of Technology Zurich © Atlas der Schweiz - interaktiv.
OVERVIEW- What is GIS? A geographic information system (GIS) integrates hardware, software, and data for capturing, managing, analyzing, and displaying.
Geographic Information System GIS This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF GIS Geographic Inf o rmation.
Applied Cartography and Introduction to GIS GEOG 2017 EL Lecture-2 Chapters 3 and 4.
1. Systems, Science, and Study. Outline What is geographic information? Definition of data, information, knowledge and wisdom Kinds of decisions that.
Object Orientated Data Topic 5: Multimedia Technology.
Introduction to GIS. GIS Definitions A map connected to a database A computerized data base management system for capture, storage, retrieval, analysis,
RNR 403/503 Applications of GIS Fall, GIS – What does it mean? Geographic (geospatial) – Place-based, georeferenced, location is quantitatively.
AND THE IOWA GEOMENTORING NETWORK (IGN). ABOUT US Adam Skibbe, GIS Administrator – University of Iowa Department of Geographical and Sustainability Sciences.
ISPRS Congress 2000 Multidimensional Representation of Geographic Features E. Lynn Usery Research Geographer U.S. Geological Survey.
1 Image Et Ville 7 th EC-GI & GIS WORKSHOP – June 2001 – Potsdam THE USE OF « IMAGE » IN GEOGRAPHICAL INFORMATION MARKET : RESULTS OF AN INQUIRY.
INTRODUCTION TO GIS  Used to describe computer facilities which are used to handle data referenced to the spatial domain.  Has the ability to inter-
Probabilistic Latent Semantic Analysis as a Potential Method for Integrating Spatial Data Concepts R.A. Wadsworth 1, A.J. Comber 2, P.F. Fisher 2 1.Centre.
WFM 6202: Remote Sensing and GIS in Water Management © Dr. Akm Saiful IslamDr. Akm Saiful Islam WFM 6202: Remote Sensing and GIS in Water Management Dr.
Mobile GIS CHAPTER 1: GIS AND THE INFORMATION AGE The Information Age:  The world changing and the methods of meeting the needs of those changes are also.
Titre. Geographic Information System GIS offer powerful tools for adding spatial perspectives to: –Planning –Research –Technology transfer –Impact assessment.
UNIT 3 – MODULE 4: Database Management. INTRODUCTION Managing data is a critically important function. It enables strategic searching & manipulation of.
2.2 Interfacing Computers MR JOSEPH TAN CHOO KEE TUESDAY 1330 TO 1530
Introduction to Geodatabases
Czech Technical University in Prague Faculty of Transportation Sciences Department of Transport Telematics Doc. Ing. Pavel Hrubeš, Ph.D. Geographical Information.
LUMEN WinGIS The manageable GIS plus worldwide Microsoft BING maps and Sentinel images incl. NDVI-growth-index-maps + services (download all sensors, storage,
Czech Technical University in Prague Faculty of Transportation Sciences Department of Transport Telematics Pavel Hrubeš Geographical Information Systems.
Laws and Algebras – A Comparison
GIS Basic Training June 7, 2007 – ICIT Midyear Conference
Content Management.
GEOGRAPHICAL INFORMATION SYSTEM
INTRODUCTION TO GEOGRAPHICAL INFORMATION SYSTEM
Geographic Information Systems
Syed Masiur Rahman (student id #220256)
Geographical information system: Definition and components
Presentation transcript:

State of the Art and Future Trends in Geoinformatics Gerhard Navratil

2/34 Gerhard Navratil Contents How to determine State of the Art? GIS: The Early Years Framework Changes Changes in Research Questions Future Challenges

3/34 Gerhard Navratil How to Determine State of the Art? How to Determine Future Trends? Look at industry solutions? Look at publications in journals? Look at presentations in conferences? Look at the development of knowledge! Try to extrapolate!

4/34 Gerhard Navratil GIS: The Early Years 1960‘s: First Steps of GIS –Computers slow –Storage media slow and expensive (tapes) –No graphical out put Nixdorf 820, 1968 (Christian Giersing )

5/34 Gerhard Navratil Early Maps (Marble et al. 1984)

6/34 Gerhard Navratil Early Topics Data storage Networks and topology Attribute modelling Required functionality User interface Graphical output

7/34 Gerhard Navratil Example: Geometry Representation –Vector: Spaghetti, Topology (1980‘s) –Raster: Simple concept, easy to print, scanned maps Efficient storage –Databases save space (relational DB) (Codd 1969) Problems of data combination –Map algebra (Tomlin, 1990) –Line intersection problem

8/34 Gerhard Navratil Example: Line Intersection It Makes Me so Cross (Douglas, 1974) –Task: General purpose FORTRAN routine to decide if two line segments intersect –5 pages of text, 21 special cases It Doesn‘t Make Me Nearly as Cross (Saalfeld, 1987) –New representation (point-vector) –determine r, r' – intersect if both in [0,1]

9/34 Gerhard Navratil What Happened? Implementation led to problems First solution Improvement by different approach More elegant solution  -improvements?

10/34 Gerhard Navratil Framework Changes (80‘s/90‘s) Increasing amount of computing power (from exclusive equipment to ubiquitous infrastructure) Standard graphical user interfaces  GIS on standard office PC‘s

11/34 Gerhard Navratil Problem: Data Supply Main data sources: Scanned maps (outdated) Measurements (slow, expensive) Satellite images (low resolution, expensive) Aerial photography (required digitizing, expensive)  Standard Data Suppliers (e.g., Ordnance Survey)

12/34 Gerhard Navratil Advantages of Standard Data Sources Well developed data capture processes  known quality Clear understanding of the limits of the data (At least some) Liability issues solved

13/34 Gerhard Navratil Disadvantages of Standard Data Sources Standard products with defined quality – only limited options Dependency on a single data provider Market power of producers  Data quality discussed from producer perspective only

14/34 Gerhard Navratil Software Small number of commercial GIS: ESRI Intergraph Siemens MapInfo (Erdas) Almost no independent products (mainly GRASS and Spring)

15/34 Gerhard Navratil Recent Changes New communication technology (Internet, mobile phones, WLAN) Abundant data: –Volunteered Geographic Information (VGI) –Satellite images –Laser Scanning/Digital Photogrammetry Software producing communities (open source software)

16/34 Gerhard Navratil New Tools/Environments GNSS: Positioning information is available high level of quality Smartphones (mobile, bi-directional access to data) Google Earth, Google Maps, Microsoft Bing

17/34 Gerhard Navratil Changes in Research Questions Quality of the new data? Users are no experts  Communication with lay people Data used during execution of a process, not during planning – changes?

18/34 Gerhard Navratil Research Questions on Data (1) Understanding the processes that produce the data –Quality checks? Consistency? Updates? –Data processing steps? Understanding the communities providing the data –What is the incentive? –What is the task for which the data is needed? –Knowledge level of data producers?

19/34 Gerhard Navratil Research Questions on Data (2) Limitations of the data set? –Scale of the data capture? –What is the quality? Is it uniform? Connection between different data sets? –Different communities collecting similar data in the same region? –Similar communities collecting similar data in neighbouring region?

20/34 Gerhard Navratil Research Questions on Users What is the information needed by the user? –Required level of quality? –Required additional information? How to best communicate the information? –Graphical or Verbal or Oral? –User-oriented or as a map? –Level of redundancy?

21/34 Gerhard Navratil Example: OpenStreetMap (1) Data provided by –Communities –Organizations (e.g., Ordnance Survey) –Private persons Data collected by –GPS-tracks –Digitizing aerial images Teheran (OSM, 2011)

22/34 Gerhard Navratil Example: OpenStreetMap (2) Free to use (License: Creative Commons) Usable for routing and mapping Available for large parts of the world Public Transport in Berlin (Melchior Moos, 2008)

23/34 Gerhard Navratil Example: OpenStreetMap (3) User tasks –Cartography (professionals/amateurs) –Navigation (routing) Assessing the quality is difficult –Attribute accuracy in international context? –Completeness? In comparison to what? NAVTEQ/TeleAtlas- data?

24/34 Gerhard Navratil Example: OpenStreetMap (4) Classification in different countries, e.g., highway = tertiary (Wikipedia) (Google Earth)

25/34 Gerhard Navratil Emerging Research Fields Semantics of data Assessment of data quality for VGI User interfaces Processes and time

26/34 Gerhard Navratil Semantics of Data (1) Data from different sources – what happens when we combine them? –Different communities use different classifications – land cover vs. land use? –Comparing apples and oranges? (Comber, 2007) (Wikipedia)

27/34 Gerhard Navratil Semantics of Data (2) Current tool: Ontologies Research questions: Semantics of processes Vagueness Translation of terms between domains Trust in semantic quality of VGI

28/34 Gerhard Navratil Assessment of Data Quality (1) Easy for result of single observation (quality of equipment) Difficult if –Data collected during extended period e.g., land management –Data collected by vast number of people e.g., VGI

29/34 Gerhard Navratil Assessment of Data Quality (2) Ideas for quality assessment in land management: Geometrical quality of cadastral boundaries: Compare data set with original surveys (Navratil et al. 2010) Compare the data sets with orthophotos Result: Varying quality – how to communicate? A: deviations between a few cm and 150m

30/34 Gerhard Navratil User Interfaces New impulses for interfaces from Google Earth, smartphones, etc. How to exert this? How to exploit the new hardware? e.g., smartphones, tablets 2D or 3D? When to use what? Virtual reality or mixed reality? Applications? Benefits? Realization?

31/34 Gerhard Navratil Processes and Time (1) Data are not static – reality changes constantly  Data are connected to the date of collection Data describe/are influenced by processes e.g., sensor networks Consistency checks require combination of processes and data e.g., differential equations (Hofer & Frank 2009)

32/34 Gerhard Navratil Processes and Time (2) Task are described by Location Duration Prerequisites Coordination of tasks requires Start and end location of tasks Duration of navigation between different locations

33/34 Gerhard Navratil Conclusions (1) Finding research topics requires Understand the recent developments Detect changes in the framework Find the consequences of these changes Look for missing links

34/34 Gerhard Navratil Conclusions (2) Future key research topics are Semantics of data Assessment of data quality for VGI User interfaces Processes and time