SemesterFall Semester, 2019
DepartmentMA Program of Public Administration, First Year PhD Program of Public Administration, First Year MA Program of Public Administration, Second Year PhD Program of Public Administration, Second Year
Course NameGIS for Social Science
InstructorLIAO HSIN-CHUNG
Credit3.0
Course TypeElective
Prerequisite
Course Objective
Course Description
Course Schedule

 


































































































































































週次



Week



課程主題



Topic



課程內容與指定閱讀



Content and Reading Assignment



教學活動與作業



Teaching Activities and Homework



學習投入時間



Student workload expectation



課堂講授



In-class Hours



課程前後



Outside-of-class Hours



9/10




  • Introduction

  • Course Overview

  • What is GIS

  • Understanding ArcGIS & GIS Terminology



 




  • ArcGIS Basics

  • Loading Data

  • Scales

  • Navigation

  • Online Help



3



1



9/17




  • Making Maps




  • GIS and Mapping: Pitfalls for Planners(Kent & Klosterman 2000)




  • Types of Maps

  • Elements of Cartography



 



3



3



9/24




  • Working with Maps & Data I




  • Making a Place for Space: Spatial Thinking in the Social Sciences (Logan 2012)




  • Attribute Query

  • Joining & Relating

  • Data Classification

  • Projection



3



3



10/1




  • Working with Maps & Data II




  • Theoretical Foundations of the Sociology of Location (Porter & Howell 2012 pages 1-62)




  • Attribute Query

  • Joining & Relating

  • Data Classification

  • Projection



3



3



10/8




  • Working with Census Data I




  • Theoretical Foundations of the Sociology of Location (Porter & Howell 2012 pages 1-62)




  • Understanding Census Data & Geometry

  • Accessing Census Data



3



3



10/15




  • Working with Census Data II




  • Spatial data mining and geographic knowledge discovery—An introduction (Mennis & Guo 2009)




  • Interpreting Census Variables

  • Charts & Graphs for Data Display



3



3



10/22




  • Geoprocessing




  • Recapturing Space: New Middle Range Theory in Spatial Demography Ch 7-8 (Howell, Porter & Matthews)




  • Geoprocessing Tools: Buffers, Clips, Unions



3



3



10/29




  • Address Mapping




  • Geographic Information Systems and the Spatial Dimensions of American Politics (Cho & Gimpel 2012)




  • Geocoding



3



3



11/5




  • Final Project Proposal Discussion




  • None




  • Individual Discussion in Office



3



3



11/12




  • Network Analysis




  • Measures of Spatial Accessibility to Health Care in a GIS Environment (Luo & Qi 2003)

  • Measuring spatial accessibility to healthcare for populations with multiple transportation modes (Mao & Nekorchuk2013)




  • Spatial Accessibility



3



3



11/19




  • Identifying Statistical Clusters and Exploratory Spatial Data Analysis (ESDA) of Social Data I




  • Richardson in the Information Age: Geographic Information Systems and Spatial Data in International Studies (Gleditsch & Weidmann2012)

  • Explore Spatial Data with GeoDa (Anselin 2003)




  • Spatial Weight Matrix

  • Spatial Autocorrelation

  • Exploratory Spatial Data Analysis



3



3



11/26




  • Identifying Statistical Clusters and Exploratory Spatial Data Analysis (ESDA) of Social Data II




  • Coproduction of Government Services and the New Information Technology: Investigating the Distributional Biases (Clark, Brudney & Jang 2013)

  • County Child Poverty Rates in the US A Spatial Regression Approach (Voss, Long, Hammer & Friedman 2006)

  • Explore Spatial Data with GeoDa (Anselin 2003)




  • Exploratory Spatial Data Analysis

  • Spatial Weighted Regression



3



3



12/3




  • Spatial Heterogeneity




  • Geographically Weighted Regression-Modelling Spatial Non-Stationarity (Brunsdon, Fotheringham & Charlton 1998)

  • Geographically and temporally weighted regression for modeling Spatio-temporal variation in house prices (Huang, Wu & Barry 2010)




  • Geographically Weighted Regression



3



3



12/10




  • Spatio-temporal Analysis




  • A Spatial Scan Statistic (Kuldorff 1997)

  • SaTScan User Guide (Kuldorff 2006)




  • SaTScan



3



3



12/17




  • Final Project Workshop




  • None




  • Open Lab



3



3



12/24




  • Final Project Presentation



 




  • Potluck (Drinks and Snacks)



3



3



12/31




  • Final Project Presentation



 




  • Potluck (Drinks and Snacks)



3



3



1/7




  • Final Exam



 




  • Take-Home Final Exam



0



6




 


Teaching Methods
Teaching Assistant

TBA


Requirement/Grading

The final semester grade will be computed as:




  • 10% for the oral presentation of the final project

  • 40% for the  final project (3000-5000 words)  

  • 15% for the take-home final exam

  • 15% for the assignment

  • 10% for the classroom discussion

  • 10% for the participation


Textbook & Reference

 



 



See the Schedule.



Paper Linking:  https://1drv.ms/u/s!AoacP5CovPLSj0L2Qui91hnbtTvr?e=D6minD


Urls about Course
Paper Linking: https://1drv.ms/u/s!AoacP5CovPLSj0L2Qui91hnbtTvr?e=D6minD
Attachment