Group Independent Study Advisor: Peter Fox firstname.lastname@example.org
Meeting times: bi-weekly or by arrangement
Office Hours: By appointment
Class Listing: ERTH 496x
Table of Contents
- Syllabus/ Calendar
- GIScience Applications
- Course Learning Objectives
- Assessment Criteria
- Academic Integrity
- Suggested Prerequisites
- Attendance Policy
Introduction to relational analysis and interpretation of spatial data and their presentation on static and interactive maps using PostGIS, qGIS, Leaflet.js and Geoserver. Geographic spatial data concepts covered are map projections, vectors & geoprocessing, raster analsysis, interpolation, collaborative mapping, GIS on the cloud and web mapping. Database concepts of building and manipulating a spatial database, SQL, spatial queries, and integration of graphic and tabular data are also covered. During each class we will discuss topics and do examples. Related take-home exercises will be assigned. Depending on class size, students may be asked to present assignments to the rest of the class. Each student will do a semester-long project on some topic of particular interest to them, but also of relevance to the class. These projects will be presented to the class during the last week. 4 credit hours.
Each Topic requires 3-4 hours per week of effort, comprising 1.5 hours of reviewing materials and approximately 2 hours of lab work.
- Install QGIS on your laptop
- NAIP link:http://raster.nationalmap.gov/ArcGIS/services/Orthoimagery/USGS_EDC_Ortho_NAIP/ImageServer/WMSServer?
- Install QGIS on your laptop!!!
Homework: Finish modules from Lab:
- Vector Symbology (Module 3, Lessons 2.11, 2.12(optional), QGIS Training Manual)
- Classifying Vector Data (Module 4, Lessons 2.2-2.5 QGIS Training Manual)
- Using Map Composer (Module 5, Lesson 1, QGIS Training Manual) NOTE: just use our Troy, NY data instead of Swellendam
- What is Raster Data? (ESRI ArcGIS Online Help Manual)
- Cell Size of Raster Data (ESRI ArcGIS Online Help Manual)
Lab: Viewing and analyzing raster data with QGIS
- Dataset 1 DEM [Download]
- Dataset 2 NLCD [Download]
- NLCD symbology file NLCD symbology [Download]
- Work with the group to make a list of what kinds of data you'd like to acquire for your portion of the class mapping project.
- Make a list of data you'd like to acquire for personal project.
- Introduction to the National Map (video)
- Why the World needs Open Street Map
- Interview with the author of 'Why the World needs Open Street Map'(Video)
Lab: GeoData Scrounging 101
- Group work to find and download at least 5 datasets for the group project.
- Find and download at least 5 datasets for your personal project.
Self-Assessment: Complete by ~ mid - October:
Lecture: GeoData II: Mobile data collection:
- Watch this cheezy but actually pretty OK 3-minute video intro to GPS
- Read parts I,II and III of the NYS GPS Guidelines (p. 6-11)
- Peruse this page on Fulcrum Features
- Look through the Fulcrum 'App Gallery' to see how Fulcrum is used in different disciplines
Lab: Mobile data collection with Fulcrum
Lecture: Introduction to Spatial Databases
Readings for Monday:
Lab: Setting up a PostgreSQL/PostGIS Database
Homework for Thursday:
- Install PostgreSQL 9.3.3 Download and install the EnterpriseDB installer for your operating system. After installation, open the PostgreSQL 'Application Stack Builder' to add PostGIS to your installation (Spatial Extentions--> PostGIS).
- Install BoundlessGeo plugin for QGIS
Lab: Spatial Queries in PostGIS
Homework to complete :
- 1-page proposal for your individual project. Not Graded
- Complete sections 1-9 in the Boundless Introduction to PostGIS. Exercise data can be downloaded from here.
You may skip Sections 2 & 3 if you already have a spatial database created.
Week of Oct. 10 - no meeting
Lab: The Process of GIS
Homework to complete:
- Complete sections 10-13, and 18-19 in the Boundless Introduction to PostGIS. Exercise data can be downloaded here. Please run your queries and save your outputs.
Lecture: Visualizing & Sharing Geodata on the Web I
- Updated map and 1-page status writeup for group project.
- Creating a simple map of points
- Customizing, sharing, and embedding your maps
- Map election results
- Create an intensity map from point data
- Join data from two tables using SQL
- Projections, the_geom and the_geom_webmercator
ADVANCED: Webmapping Wrapup & Geoserver reboot:
Week 14 (end of term)
- Final project presentations
- 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, reference frames, multivariate analysis, correlation analysis, regression, interpolation, exptrapolation, and kriging.
- To gain experience in an end-to-end GIS application via a term project.
Through class lectures, practical sessions, written and oral presentation assignments and projects, students should be able to:
- 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.
- Via written assignments addressing each learning objective with specific percentage of grade allocation provided for each assignment and question
- Via projects and presentations
- Via participation (not to exceed 10% of total)
- Late submission policy: N/A
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. First violation results in zero grade for the relevant portion of the work. Second offence results in a fail grade . If you have any question concerning this policy before submitting an assignment, please ask for clarification.
- Knowledge such that gained in geography, cartography.
- or permission of the instructor
Assessed by participation.