教學大綱 Syllabus

科目名稱：地理資訊系統與社會科學

Course Name: GIS for Social Science
  • 學年學期：112-1 Fall Semester, 2023
  • 科目代碼：265827001 Course No.265827001

修別：選

Type of Credit: Elective

3.0

學分數

Credit(s)

20

預收人數

Number of Students

課程資料Course Details
  • 開課單位：亞太博一、亞太博二 Course Department:International Doctoral Program in Asia-Pacific Studies/D/1&2
  • 授課老師：廖興中 Instructor: LIAO HSIN-CHUNG
  • 先修科目：無Prerequisite(N/A)
  • 上課時間：四34C Session: thu10-13

課程簡介Course Description

This course focuses on the principles of Geographic Information Systems (GIS) as a way of analyzing and understanding society. GIS is a tool to provide geospatial information analysis and display results. Industry-standard GIS software will be used in this course. Students learn the concepts of spatial analysis with GIS; use techniques in importing and creating spatial and attribute data; recognize critical components of cartography to design maps, and build attribute and spatial queries for problem-solving based on spatial relationships. Laboratory exercises incorporate the use of GIS software (ArcGIS) in the analysis of social issues.

核心能力分析圖 Core Competence Analysis Chart

能力項目說明

    課程目標與學習成效Course Objectives & Learning Outcomes

    The objectives of the course are to acquaint graduate students with methods to analyze spatially-referenced data with the procedures appropriate for a social science’s theoretical base. The course contact hours are organized into three major foci: (a) essential theoretical concepts and the constituent reference to Census Bureau demography; (b) the visualization of social data facilitated by Geographic Information Systems software; and (c) techniques to construct or analyze social point, line, and polygon data using exploratory and confirmatory spatially centered procedures to actual social theories and data using a pedagogical  analytical approaches. Weekly readings and homework will emphasize applications of these procedures to actual social theories and data using a pedagogical model of application, interpretation, and presentation of empirical analyses by students. The semester-length project is a key instrument by which students will demonstrate competence in spatial analysis methods covered in the course.

     

    每周課程進度與作業要求 Course Schedule & Requirements

    教學週次Course Week 彈性補充教學週次Flexible Supplemental Instruction Week 彈性補充教學類別Flexible Supplemental Instruction Type

    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

    （9/14）

     
    • Introduction
    • Course Overview
    • What is GIS
    • Understanding ArcGIS & GIS Terminology

                           No Class
    • ArcGIS Basics
    • Loading Data
    • Scales
    • Navigation
    • Online Help

    3

    1

    （9/21）
    • Making Maps
    • Microsoft Team link:

    https://teams.microsoft.com/l/meetup-join/19%3ae648cdedd23d4606ae21aa120cb94d14%40thread.tacv2/1694523595773?context=%7b%22Tid%22%3a%2235157425-5c3c-4672-aaa4-68fb6a8c9612%22%2c%22Oid%22%3a%22681805e4-8520-4468-a9be-1c83cf6791ff%22%7d

     

    • GIS and Mapping: Pitfalls for Planners(Kent & Klosterman 2000)
    • Types of Maps
    • Elements of Cartography

    3

    3

    （9/28）
    • 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

    （10/5）
    • Working with Maps & Data II
    • GIS, Public Service_PA (Haque, 2003)
    • Four Ways We Can Improve Policy Diffusion Research_PA(Fabrizio Gilardi1, 2016)
    • Attribute Query
    • Joining & Relating
    • Data Classification
    • Projection

    3

    3

    （10/12）
    • Working with Census Data I
    • GIS Education in U S Public Administration Programs Preparing the Next Generation of Public Servants (Nancy J. Obermeyer, Laxmi Ramasubramanian & Lisa Warnecke, 2016)
    • Understanding Census Data & Geometry
    • Accessing Census Data

    3

    3

    （10/19）
    • Working with Census Data II
    • Spatial data mining and geographic knowledge discovery—An introduction (Mennis & Guo 2009)
    • Spatial analysis and GIS in the study of COVID-19. A review_PH(Ivan Franch-Pardo a,⁎, Brian M. Napoletano b,⁎, Fernando Rosete-Verges a, Lawal Billa c, 2020)
    • Interpreting Census Variables
    • Charts & Graphs for Data Display

    3

    3

    （10/26）
    • Geoprocessing
    • PPGIS_PA (Ganapati, 2011)
    • Geoprocessing Tools: Buffers, Clips, Unions

    3

    3

    （11/2）
    • Address Mapping
    • Geographic Information Systems and the Spatial Dimensions of American Politics (Cho & Gimpel 2012)
    • Geocoding

    3

    3
    （11/9）
    • Final Project Proposal Discussion
    • None
    • Individual Discussion in Office
    		    

    （11/16）
    • Network Analysis
    • Measures of Spatial Accessibility to Health Care in a GIS Environment (Luo & Qi 2003)
    • Accessibility, equity and health care_PH(Tijs Neutens, 2015)
    • Spatial Accessibility

    3

    3

    （11/23）
    • 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)
    • Spatial Big Data Analysis of Political Risks_PS(Chuchu Zhang 1,2,y, Chaowei Xiao 3,*,y and Helin Liu, 2019)
    • Explore Spatial Data with GeoDa (Anselin 2003)
    • Spatial Weight Matrix
    • Spatial Autocorrelation
    • Exploratory Spatial Data Analysis

    3

    3

    （11/30）
    • 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)
    •  Spatial spillover effects of corruption in Asian_PS(Masoud Khodapanah1 | Zahra Dehghan Shabani2 |
      Mohammad Hadi Akbarzadeh1 | Mahboubeh Shojaeian1, 2020)
    • Explore Spatial Data with GeoDa (Anselin 2003)
    • Exploratory Spatial Data Analysis
    • Spatial Weighted Regression

    3

    3

    （12/7）
    • Spatial Heterogeneity
    • Poverty GWR_PH  (Tzai-Hung Wen1, Duan-Rung Chen2, Meng-Ju Tsai3, 2010)
    • Geographically Weighted Regression

    3

    3

    （12/14）
    • Spatio-temporal Analysis
    • A Spatial Scan Statistic (Kuldorff 1997)
    • SaTScan User Guide (Kuldorff 2006)
    • Mapping the relational construction of people and places(Michael Donnelly, Sol Gamsu & Sam Whewall, 2020)
    • Qualitative GIS(Marianna Pavlovskaya, 2016)
    • SaTScan

    3

    3

    （12/21）
    • Final Project Workshop
    • None
    • Open Lab

    3

    3

    （12/28）
    • Final Project Presentation
    		  
    • Potluck (Drinks and Snacks)

    3

    3
    （1/4）
    • Final Project Presentation
    		  
    • Potluck (Drinks and Snacks)
    		 3 3

    （1/11）
    • Final Exam
    		  
    • Take-Home Final Exam

    0

    6

     

    授課方式Teaching Approach

    30%

    講述 Lecture

    10%

    討論 Discussion

    0%

    小組活動 Group activity

    60%

    數位學習 E-learning

    %

    其他： Others:

    評量工具與策略、評分標準成效Evaluation Criteria

    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 (Presentation of the assigned article and the output of the Lab practice)
    • 10% for the classroom discussion
    • 10% for the participation

    指定/參考書目Textbook & References

     

     

    See the Schedule.

    已申請之圖書館指定參考書目 圖書館指定參考書查詢 |相關處理要點

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    課程相關連結Course Related Links

    
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    課程附件Course Attachments

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