Instructor: Steve Signell - email@example.com
TA: Robert Poirier - firstname.lastname@example.org
Meeting times: Monday and Thursday morning 10:00am - 11:50am
Office Hours: By appointment
Class Listing: ERTH 4750 (38031)
Class Location DCC 232
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 will meet for 3 to 4 hours per week, comprising 1.5 hours of instruction and approximately 2 hours of lab.
- 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 Thursday 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)
Feb. 6 (Thursday) Lab: Viewing and analyzing raster data with QGIS
- Dataset 1 DEM [Download]
- Dataset 2 NLCD [Download]
- NLCD symbology file NLCD symbology [Download]
Homework for Monday:
- Work with your group to make a list of what kinds of data you'd like to acquire for your portion of our class RPI 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)
Feb. 13 (Thursday) Lab: GeoData Scrounging 101
Homework for Thursday:
- Work with your group to find and download at least 5 datasets for your group project.
- Find and download at least 5 datasets for your personal project.
Graded Assignment #1: Due Thursday, Feb. 2O:
Feb. 18 (**TUESDAY!**) Lecture: GeoData II: Mobile data collection: Guest Lecturer Bryan McBride (Fulcrum)
Readings for Tuesday:
- 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
Feb. 13 (Thursday) Lab: Mobile data collection with Fulcrum
Homework for Thursday:
- Complete Graded Assignment #1-- due at beginning of class on Thursday.
Feb. 24 Monday Lecture: Introduction to Spatial Databases
Readings for Monday:
Feb. 27 (Thursday) 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
Mar. 6 (Thursday) Lab: Spatial Queries in PostGIS
Homework to complete before Thursday:
- 1-page proposal for your individual project due Thursday. 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 8 (Mar. 10/Mar. 13: no classes - spring break)
Mar. 20 (Thursday) Lab: The Process of GIS
Homework to complete before Thursday:
- 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 in the giscience.tw.rpi.edu PosgreSQL database so I can check your work and help troubleshoot any problems.
Mar. 24 (Monday) Lecture: Visualizing & Sharing Geodata on the Web I
Homework due Monday:
- Updated map and 1-page writeup for group projects. One submission per group, submitted electronically (via email).
- 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
Assignment 3 due (electronically) by the start of class Monday.
Apr. 10 (Thursday) Lecture/Lab: Webmapping Wrapup & Geoserver reboot:
Week 13 (Apr. 14/Apr. 17)
- Monday-lecture: Multidimensional data I: Guest Lecturer Robert Poirier (RPI): Ocean Data View
- Thursday-lab: Ocean Data View
Thursday-lab: Field Trip to KitWare
Week 15 (Apr. 28/May 1)
- Monday-lecture: Wrap up: Review & the future of GIS
- Thursday-lab: Work on group & individual projects.
Week 16 (May 5): Monday: 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 in class (not to exceed 10% of total)
- Late submission policy: first time with valid reason – no penalty, otherwise 20% of score deducted each late day
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. of an academic grade penalty or . 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
Enrolled students may miss at most one class without permission of the instructor. Missed classes will contribute to class participation assessments.