Module Code and Title:       GIS202            Geographic Information Sciences II

 

Programme(s):                      BSc Environmental Management

 

Credit Value:                         12

 

Module Tutor(s):                   Samir Patel (Coordinator)

                                                Radhika Chhetri

Jesse Montes

                                                Nima Wangmo

 

General objective(s) of the module:

 

This module follows on the general introduction to GIS in a previous semester and allows students delve deeper into problem solving and decision making using geospatial analysis techniques, applicable to a range of disciplines but with particular emphasis on environmental management. The module is based on GeoTech Center’s model course on geospatial analysis.

 

Learning outcomes – Upon successful completion of the module, students will be able to:

 

·         Prepare GIS data for use in analysis.

·         Determine an appropriate approach to solving a problem or answering a question using geospatial tools and methods.

·         Run geoprocessing tools individually.

·         Implement a model to run several geoprocessing tools in sequence.

·         Organize the data sets resulting from analysis.

·         Apply the principles of geospatial analysis to an environmental management problem.

·         Present the results of a geospatial analysis using appropriate terminology and visualizations.

 

Skills to be developed:

 

·         Students should learn how to work more intimately with data: describe and demonstrate how to access different sources of data, describe and demonstrate the process of creating data, and discuss the fundamental concepts of data quality.

 

Learning and teaching approaches used:

 

The module will be conducted over 15 teaching weeks as follows:

·         3 hrs/wk lecture & discussions.

·         3 hrs/wk practical in a computer lab.

·         2 hrs/wk outside of class, on average, for independent study, including some field work using GPS in coordination with requirements of other modules this semester.

 

Assessment:

 

Semester-End Examination (SE):30%

Continuous Assessment (CA):     70%

CA Assessment	Weight	Assessment Detail
Quizzes (4% x 5)	20%	Short written individual quizzes of 30 min duration each, covering approximately 3 weeks of subject matter.
Presentations (2 x 10%)	20%	Individual 10 min presentation with 2-5 min Q&A.
Group Assignment	10%	GIS-based group project output report (1000 words plus data and maps)
Individual project	20%	GIS-based individual work and output report (1000 words plus data and maps).

 

Pre-requisite knowledge: GIS201 Geographic Information Sciences I

 

Subject matter:

 

I.              Review of the basics of geospatial data

a.    Review the basics of geospatial data including data organization in an appropriate format such as a geodatabase; the importance and role of coordinate system definition and projection between coordinate systems; the differences between vector and raster data formats; and basic cartographic and data presentation techniques.

II.            Introduction to geospatial analysis

a.    Start to think about using geospatial data to explore data relationships.

b.    Learn how to prepare a simple data set using a straightforward method such as a join.

c.    Classify quantitative data using a variety of statistical methods.

d.    Create a scatter plot of data and present results of analysis in graph and cartographic format.

III.           Using Advanced Attribute and Spatial Queries for Data Exploration

a.    Given a data set, perform advanced queries to prepare the data for use in analysis; spatial and attribute selections.

b.    Use a data dictionary to decipher coded data in an attribute table.

c.    Determine how to use queries to address a question.

d.    Learn about selection by location and buffering.

IV.          Vector data analysis: overlay techniques

a.    Learn vector overlay analysis tools and concepts including union, intersect and identity, and how these tools can be used to analyse multiple geospatial data sets to answer a question.

b.    Convert from coverage format to modern GIS data format.

c.    Learn about changing environment settings to enhance data organization.

V.            Vector data analysis: creating a site selection model

a.    Learn proximity analysis including buffering points, lines and polygons.

b.    Learn the concept of a geospatial data model by developing flow charts.

c.    Develop a model that satisfies multiple location criteria for a given project.

VI.          Vector data analysis: network analysis

a.    Prepare a vector data set for use in a network routing exercise including building topology.

b.    Use network techniques to create efficient routes including modelling of impedances.

c.    Generate service areas based on network analysis.

VII.         Building an automated model

a.    Learn how to implement a multi-step model using automation tools, e.g. Model Builder in ArcGIS.

b.    Learn to set appropriate environmental settings prior to running a model.

c.    Set model parameters in order to alter model inputs.

d.    Export their model to a script and edit the script using Python.

VIII.        Raster data analysis: working with topographic data

a.    Learn how to use raw elevation data to create slope, aspect and hillshade surfaces.

b.    Use elevation and derived data sets to analyse an environmental issue.

c.    Reclassify raster data and use in a map algebra-based model, including weighting techniques.

d.    Use viewshed analysis to enhance site selection.

IX.          Raster data analysis: working with hydrographic data

a.    Obtain appropriate data sets and use them to do a surface hydrological analysis.

b.    Generate streams using flow direction and accumulation surfaces.

c.    Create watersheds based on topographic data.

d.    Use hydrographic data to analyse a scientific question.

X.             Raster data analysis: density surfaces

a.    Interpolate data density surfaces from point data using appropriate methods.

b.    Convert between vector and raster format.

c.    Develop an approach to a given question using density techniques.

XI.           Final Project

a.    Solve a problem using geospatial technology from goals and data acquisition to analysis and processing to cartographic presentation and publishing.

b.    Create own data using electronic methods.

 

Essential Readings:

 

1.    Chang, K. (2007). Introduction to Geographic Information Systems. New Delhi: Tata McGraw-Hill Education.

2.    DiBiase, D. (continually updated). Nature of Geographic Information. Penn State: https://www.e-education.psu.edu/natureofgeoinfo/

3.    Schmandt, M (continually updated). GIS Commons: An Introductory Textbook on Geographic Information Systems: http://giscommons.org

4.    Fundamentals of Remote Sensing, published by Natural Resources Canada: http://www.nrcan.gc.ca/sites/www.nrcan.gc.ca/files/earthsciences/pdf/resource/tutor/fundam/pdf/fundamentals_e.pdf

5.    Sutton, T., Dassau, O., Sutton, M. (2009) A Gentle Introduction to GIS, Eastern Cape, South Africa: http://download.osgeo.org/qgis/doc/manual/qgis-1.0.0_a-gentle-gis-introduction_en.pdf

 

Additional Readings:

 

1.    Ballard, A. (2011). Course Resources for GST102 – Spatial Analysis. GeoTech Center Model Courses (GST 102 Spatial Analysis Course). http://www.geotechcenter.org/model-courses.html

2.    Bolstad, P. (2012). GIS Fundamentals: A First Text on Geographic Information Systems, 4^th ed. Eider Press.

3.    ESRI ArcNews, http://www.esri.com/news/arcnews/index.html

4.    ESRI ArcUser, http://www.esri.com/news/arcuser/index.html

5.    Law, W. and Collins, A. (2013). Getting to Know ArcGIS Desktop, 3^rd Ed. Esri press.

6.    GeoTech Teaching Resources, http://www.geotechcenter.org

7.    Gorr, W.L. and Kurland, K.S. (2010). GIS Tutorial 1: Basic Workbook 4^th ed. Esri Press.

8.    Scally, R. (2006). GIS for Environmental Management. Esri Press.

 

Date last updated: May 30, 2015