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：111-1 Fall Semester, 2022
  • 科目代碼：926847001 Course No.926847001

修別：選

Type of Credit: Elective

3.0

學分數

Credit(s)

10

預收人數

Number of Students

課程資料Course Details
  • 開課單位：亞太碩一、亞太碩二 Course Department:International Master's Program in Asia-Pacific Studies/M/1&2
  • 授課老師：廖興中 Instructor:
  • 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

    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

    （9/15）

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

    The google meet link:

    https://meet.google.com/ftq-eodd-bzp

    Pin Number: 495 717 348#
    • ArcGIS Basics
    • Loading Data
    • Scales
    • Navigation
    • Online Help

    3

    1

    （9/22）
    • Making Maps
    • GIS and Mapping: Pitfalls for Planners(Kent & Klosterman 2000)
    • Types of Maps
    • Elements of Cartography

    3

    3

    （9/29）
    • 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

    （10/6）
    • 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

    （10/13）
    • 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

    （10/20）
    • 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

    （10/27）
    • Geoprocessing
    • PPGIS_PA (Ganapati, 2011)
    • Geoprocessing Tools: Buffers, Clips, Unions

    3

    3

    （11/3）
    • Address Mapping
    • Geographic Information Systems and the Spatial Dimensions of American Politics (Cho & Gimpel 2012)
    • Geocoding

    3

    3
    （11/10）
    • Final Project Proposal Discussion
    • None
    • Individual Discussion in Office
    		    

    （11/17）
    • 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

    （11/24）
    • 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

    （12/1）
    • 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

    （12/8）
    • Spatial Heterogeneity
    • Poverty GWR_PH  (Tzai-Hung Wen1, Duan-Rung Chen2, Meng-Ju Tsai3, 2010)
    • Geographically Weighted Regression

    3

    3

    （12/15）
    • 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

    （12/22）
    • Final Project Workshop
    • None
    • Open Lab

    3

    3

    （12/29）
    • Final Project Presentation
    		  
    • Potluck (Drinks and Snacks)

    3

    3
    （1/5）
    • Final Project Presentation
    		  
    • Potluck (Drinks and Snacks)
    		 3 3

    （1/12）
    • 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

    
https://1drv.ms/u/s!AoacP5CovPLS2CUynrfq6Bq6cZbH?e=lu8bw5

    課程附件Course Attachments

    課程進行中，使用智慧型手機、平板等隨身設備 To Use Smart Devices During the Class

    需經教師同意始得使用 Approval

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