Introduction to Geographic Information Systems

1. GIS in the Sciences ERTH 4750 (38031) Introduction to Geographic Information Systems Steve Signell, Instructor (signes@rpi.edu) Robert Poirier, TA (poirir@rpi.edu) School of Science Rensselaer Polytechnic Institute Thursday, January 23, 2013

2. Acknowledgements • This lecture is partly based on: • Huisman, O., de By, R.A. (eds.), 2009. Principles of Geographic Information Systems. ITC Press, Enschede, The Netherlands • Fox, P., 2012. Introduction to Geographic Information Systems for Science. Course lecture at RPI, Troy • Xiaogang (Marshall) Ma, 2013. Introduction to Geographic Information Systems for Science. Course lecture at RPI, Troy

3. Contents • Introductions • Course outline • Logistics and resources • Assessment and assignments • Goals and learning objectives • Introduction to GIS • Next classes

4. Introductions • Instructor: Steve Signell • TA: Robert Poirier

5. Introductions • Name, major, year. • Interests, goals, outcomes • Classes or experience in: • Geography, cartography • Other spatial analysis • Web development (html, javascript) • Mathematics • Smart phones? • Questions

6. Logistics • Class: ERTH 4750 • Hours: 10am-11:50pm Monday, Thursday • Location: DCC 232 • Instructor: Steve Signell – signes@rpi.edu • Contact hours: by appointment • Contact location: • TA: Robert Poirier, poirir@rpi.edu • Web: http://tw.rpi.edu/web/Courses/GIScience/2014 • Schedule, syllabus, reading, assignments, etc.

7. Course Outline (tentative) • Week 1 (Jan. 23) Introduction to Geographic Information Systems • Week 2 (Jan. 27/Jan. 30) GIS I: Projections & vector data with Qgis • Week 3 (Feb. 3/Feb. 6) GIS II: Raster Analysis with Qgis • Week 4 (Feb 10/Feb. 13) Geodata I: Scrounging 101, tracking down Geodata • Week 5 (Feb. 18/Feb. 20) Geodata II: Mobile data collection* • Week 6 (Feb. 24/Feb. 27) Introduction to Spatial Databases • Week 7 (Mar. 3/Mar. 6) Spatial Queries in PostGIS • Week 8 (Mar. 10/Mar. 13) no classes - spring break • Week 9 (Mar. 17/Mar. 20):Collaborative GIS I: Literate Programming & GitHub • Week 10 (Mar. 24/Mar. 27) Geodata on the Web I: Geoserver, Google, CartoDB • Week 11 (Mar 31/Apr. 3) Geodata on the Web II: Leaflet.js & D3.js • Week 12 (Apr. 7/Apr. 10) Collaborative GIS II: Web Map Mashup • Week 13 (Apr. 14/Apr. 17) Multidimensional data I: Ocean Data View* • Week 14 (Apr. 21/Apr.24) Multidimensional data II: 3D Visualization* • Week 15 (Apr. 28/May 1) Wrap up: Review & the future of GIS • Week 16 (May 5): Monday: Final project presentations

8. Assessment and Assignments • Short written assignments & quizzes (25%) • Participation in lab, lecture & group project (25%) • Individual project (50%) • Vector and raster data • Written & Oral Reports • Must have dynamic web map component • Late submission policy: first time with valid reason – no penalty, otherwise 20% of score deducted each late day

9. Assessment and Assignments • Reading assignments • Are given almost every week • Most are background and informational • Some are key to completing assignments • Some are relevant to the current week’s class (i.e. follow up reading) • Others are relevant to following week’s class (i.e. pre-reading) • Undergraduates - will not be evaluated on but we will often discuss these in class and participation in these is taken into account • Graduates – are likely to be tested as part of assignments, i.e. an extra question

10. Goals • To provide students an opportunity to learn geospatial applications and tools. • To introduce relational analysis and interpretation of spatial data and presentation on maps. • Introduce spatial database concepts and technical aspects of query languages and geographic integration of graphic and tabular data. • To introduce intermediate aspects of geospatial analysis:  map projections, vectors & geoprocessing, raster analysis, collaborative mapping, GIS on the cloud and web mapping. • To gain experience in end-to-end GIS applications via group and individual term projects.

11. Learning Objectives • Through class lectures, practical sessions, written and oral presentation assignments and projects, students should: • Demonstrate proficiency in using geospatial applications and tools (commercial and open-source). • Present verbally relational analysis and interpretation of a variety of spatial data on maps. • Demonstrate skill in applying database concepts to build and manipulate a spatial database, SQL, spatial queries, and integration of graphic and tabular data. • Demonstrate intermediate knowledge of geospatial analysis methods and their applications.

12. Academic Integrity • Student-teacher relationships are built on trust. For example, students must trust that teachers have made appropriate decisions about the structure and content of the courses they teach, and teachers must trust that the assignments that students turn in are their own. Acts, which violate this trust, undermine the educational process. The Rensselaer Handbook of Student Rights and Responsibilities defines various forms of Academic Dishonesty and you should make yourself familiar with these. In this class, all assignments that are turned in for a grade must represent the student’s own work. In cases where help was received, or teamwork was allowed, a notation on the assignment should indicate your collaboration. Submission of any assignment that is in violation of this policy will result in a penalty. If found in violation of the academic dishonesty policy, students may be subject to two types of penalties. The instructor administers an academic (grade) penalty, and the student may also enter the Institute judicial process and be subject to such additional sanctions as: warning, probation, suspension, expulsion, and alternative actions as defined in the current Handbook of Student Rights and Responsibilities. If you have any question concerning this policy before submitting an assignment, please ask for clarification.

13. What is expected • Attend class, complete assignments (esp. reading) • Participate • Ask questions • Work both individually and in a group • Work constructively in group and class sessions

14. Questions so far?

15. Introduction to Geographic Information Systems What is a GIS?

16. GIS as a domain of science and technology Geography Philosophy Landscape Architecture Geographic Information Science & Technology Psychology Various Application Domains Geographic Information Science Application of GI Science & Technology Mathematics They worked on ‘positions’ (land survey) before entering politics Statistics Geospatial Technology Computer Science Engineering George Washington Thomas Jefferson Abraham Lincoln Information Science & Technology From GI System to GI Science & Technology (DiBiase et al. 2006)

17. Geographic Information Science • Hmm, a broad S • From GISystems to GIScience • GIScience: the science behind GISystems technology • considers fundamental questions raised by the use of systems and technologies • is the science needed to keep technology at the cutting edge Courtesy: http://www.ncgia.ucsb.edu/giscc/units/u002/u002.html

18. The purpose of GIS GIS stands for ‘Geographical Information System’. A GIS consists of: • Digital Data –– the geographical information that you will view andanalyse using computer hardware and software. • Computer Hardware –– computers used for storing data, displaying graphics and processing data. • Computer Software –– computer programs that run on the computer hardware and allow you to work with digital data. A software program that forms part of the GIS is called a GIS Application. Image: qgis.org

19. The purpose of GIS Image: qgis.org

20. The purpose of GIS • A biologist might be interested to determine how widespread the invasive Asian clam in Lake George was, and to develop and implement an eradication plan. Asian clam identified in Lake George, NY Image courtesy of lakegeorge.com

21. The purpose of GIS • A geological engineer might want to identify the best localities for constructing buildings in an area with regular earthquakes by looking at rock formation characteristics. Rock outcrop, North San Francisco Image courtesy of Pascal Calarco

22. The purpose of GIS • A forest manager might want to optimize timber production using data on soil and current tree stand distributions, in the presence of a number of operational constraints, such as the requirement to preserve tree diversity. Timber production Image courtesy of futureforest.eu

23. The purpose of GIS • Brainstorm: What are some spatial questions YOU would like answered? (not just science now)

24. Spatial data and geoinformation • Data are representations that can be operated upon by a computer. • Spatial data are data that contain positional values. • Geospatial data are spatial data that are georeferenced. • Metadata are data about data (Who/what/when/where/why) • Information is the meaning of data as interpreted by human beings. • Geoinformation is information that involves interpretation of spatial data.

25. Spatial data and geoinformation • Data, Information, Knowledge, Wisdom (DIKW)

26. The real worldand representations of it • When dealing with data and information we are usually trying to represent some part of the real world as it is, as it was, or perhaps as we think it will be. • We say ‘some part’ because the real world cannot be represented completely. • We use a computer representation of some part of the real world to enter and store data, analyze the data and transfer results to humans or to other systems. Image courtesy of NOAA

27. Modeling • A representation of some part of the real world can be considered a model of that part. • This allows us to study the model instead of the real world. • Models come in many different flavors. • Maps • Databases • … • Most maps and databases can be considered static models. • Dynamic models or process models address changes that have taken place, are taking place and may take place. • One fundamental challenge in many uses of GIS is that of understanding phenomena that have (a) a geographic dimension, and (b) a temporal dimension. Spatio-temporal = be of/in space and time “Everything that happens, happens somewhere in space and time. ” -- Michael Wegener (University of Dortmund)

28. Maps • Models of the real world are often visualized in maps. • Cartography: science and art of map making Two major kinds of maps: • Static Maps • Dynamic (Interactive) Maps

29. Static Maps • Paper, PDF, TIFF, jpeg • A static map is always a graphic representation at a certain level of detail. (smaller the scale, the less detail the map can show). Increasing map scale Images made with Google Maps • A static map is always a single snapshot in time.

30. Static Maps More examples of maps Images courtesy of rpi.edu

31. Static Maps More examples of maps Images courtesy of frontierspatial.com

32. Static Spatio-Temporal Maps The maps show current and projected forest types. Major changes are projected for many regions. For example, in the Northeast, under a mid-range warming scenario, the currently dominant maple-beech-birch forest type is projected to be completely displaced by other forest types in a warmer future. Projected shifts in forest types Image source: http://nca2009.globalchange.gov/projected-shifts-forest-types

33. Static Spatio-Temporal Maps Drought’s Footprint (1930 to present) Image source: National Climatic Data Center, NOAA

34. Dynamic Maps • URL, on the web • A dynamic map can present graphic representations at multiple spatial scales, with varying degrees of detail. Increasing map scale Images made with GOOGLE MAPS! • Dynamic maps can incorporate time.

35. Dynamic Maps http://poncamap.sig-gis.com/

36. Dynamic Maps http://adkwebmap.com/hamletViz.php

37. Dynamic Spatio-temporal Maps http://roadtolarissa.com/meteors/

38. (Dynamic) Spatio-temporal Maps w/real-time data http://hint.fm/wind/

39. Dynamic Spatio-temporal Maps http://roadtolarissa.com/twisters/

40. Databases • A database is a repository for storing large amounts of data. • It allows concurrent use. • It supports storage optimization. • It supports data integrity. • It has a query facility. • It offers query optimization. • (Most) modern database systems organize the stored data in tabular format. • A database may have many tables, and each table may have many columns (attributes) and rows (records). Image courtesy of MapInfo User Guide

41. Spatial databases • Spatial databases are a specific type of database. • Besides traditional administrative data, they can store representations of real world geographic phenomena for use in a GIS. • A spatial database, also called a geodatabase, focuses on concurrency, storage, integrity, and querying of spatial data. • A GIS focuses on operating on spatial data with a ‘deep understanding’ of geographic space.

42. Spatial databases • Geographic phenomena have various relationships with each other and possess spatial, temporal, and thematic attributes. • For data management purposes, phenomena are classified into thematic data layers. • Spatial analysis is the generic term for all manipulations of spatial data carried out to improve one’s understanding of the geographic phenomena that the data represent. Image courtesy of Jonathan Campbell and Michael Shin

43. Spatial data and geoinformation • In GIS, one must be mindful of the QUALITY of your data! • Even source data that have been subject to strict quality control, errors are introduced when these data are input to a GIS. • A GIS database normally contains data from different sources of varying quality. • Most GIS analysis operations will themselves introduce errors. • Uncertainty in decision-making depends upon quality of base data and derived information.

44. Spatial data and geoinformation Comparison of seven available digital databases of the streets in part of Goleta, CA, USA (Goodchild 2011)

45. For Next Monday Monday Lecture: GIS I: Projections & vector data Readings: (links at: http://tw.rpi.edu/web/Courses/GIScience/2014) • Maps (Wikipedia) • GIS overview (QGIS website) • Spatial References (QGIS website) • Vector Data (QGIS website) Install QGIS on your laptop! (qgis.org)