Geographic Information System @ NTNU
Course Content

This course introduces basic concepts and tools of geographic information systems (GIS). Theory and frameworks upon which geographic information science is founded are covered where appropriate to provide a context for applied concepts. Lectures will emphasize basic concepts of design, planning and implementation of GIS as they relate to a variety of fields, while the laboratory component will provide hands-on experience with cutting-edge mainstream GIS software. On successful completion of this course, students should be able to understand fundamental concepts of Geographic Information System, and familiarize the usage of current mainstream GIS software. The course consists of tutorials and laboratory sessions. Tutorials are meant to acquaint students with the fundamental concepts and processes in shaping of the land. In particular, a problem-based approach to understanding the violent earth will be adopted through discussions during tutorials.

Course Intro.

01 :: Course Introduction
Contents: (1) About CCH (2) Course Introduction (3) Grading Policy (4) Why do you need to take this course? (5) What will you learn from this course? (6) Textbook & Software

Intro. to GIS & Overview

02 :: Introduction to GIS & Overview
Contents: (1) What is GIS? (2) GIS File Elements (3) Types of GIS (4) Download Geo-Datasets (5) An Overview of ArcGIS Pro (6) References

Coordinate System

03 :: Coordinate System
Content: (1) What is a coordinate system? (2) The shape of the Earth (3) GCS and PCS (4) Latitude and longitude (5) Great Circle (6) Projection (7) Common map projections (8) TWD67TM2 and TWD97TM2 (9) What is vector data? (10) Shapefile structure

Vector Data (I)

04 :: Vector Data (I)
Content: (1) Display XY (2) Join & Spatial Join (3) Add Field & Data Types (4) Select by Attribute (5) Select by Location (6) Calculate Geometry (7) Calculate Field (8) Symbology

Vector Data (I) :: Lab Practice

04 :: Vector Data (I) :: Lab Practice
Content: (1) Download Datasets (2) Display XY (3) Join & Spatial Join (4) Add Field & Data Types (5) Select by Attribute (6) Select by Location (7) Calculate Geometry (8) Calculate Field (9) Symbology

Vector Data (II)

05 :: Vector Data (II)
Content: (1) Extract (Clip/Select) (2) Overlay (Union/Intersect/Identity/Erase) (3) Proximity (Buffer/Near/Create Thiessen Polygon) (4) Dissolve (5) Density (Point/Kernel/Line) (6) Polygon To Line/ Join Features/Feature To Point (7) Symbology

Vector Data (II) :: Lab Practice

05 :: Vector Data (II) :: Lab Practice
Content: (1) Extract (Clip/Select) (2) Overlay (Union/Intersect/Identity/Erase) (3) Proximity (Buffer/Near/Create Thiessen Polygon) (4) Dissolve (5) Density (Point/Kernel/Line) (6) Polygon To Line/ Join Features/Feature To Point (7) Symbology

Invited Talk

06 :: Google Engineer Speech
Content: (1) Cognitive Biases (2) Causal Inference and A/B Test (3) Geographic A/B Test (4) Data Scientist Career

Digitalization

07 :: Digitalization
Content: (1) Usage of Digitalization (2) Digitalization Lab

Midterm Exam

08 :: Midterm Exam
Content: Midterm Exam

Spatial Interpolation

09 :: Spatial Interpolation
Content: (1) Gridding (2) MAUP (3) Spatial Interpolation (4) Inverse Distance Weighting (5) Kriging (6) Natural Neighbor (7) Spline

Spatial Interpolation :: Lab Practice

09 :: Spatial Interpolation :: Lab Practice
Content: (1) Gridding (2) MAUP (3) Spatial Interpolation (4) Inverse Distance Weighting (5) Kriging (6) Natural Neighbor (7) Spline

University Day

10 :: Holiday
Content: Holiday

Spatial Statistics I

11 :: Spatial Clustering
Content: (1) Spatial Data Distribution (2) Centers (3) Central Tendency Problems (4) z-score and p-value? (5) Average Nearest Neighbor (6) Getis-Ord General G (7) Global Moran’s I (8) Incremental Spatial Autocorrelation (9) k-function

Spatial Statistics I :: Lab Practice

11 :: Spatial Clustering :: Lab Practice
Content: (1) Centers (2) Average Nearest Neighbor (3) Incremental Spatial Autocorrelation (4) Getis-Ord General G (5) Repley’s k-function (6) Global Moran’s I

Spatial Statistics II

12 :: Spatial Statistics II
Content: (1) Global vs Local Patterns (2) A Local View (3) Local Moran’s I (4) Getis-Ord Gi* (5) Density-based Clustering (6) Spatial Outlier Detection (7) False Discovery Rate Correction (8) Multivariate Clustering (9) ML Clustering

Spatial Statistics II :: Lab Practice

12 :: Spatial Statistics II :: Lab Practice
Content: (1) Identify the Spatial Distribution of Clusters (2) Group the Village with Similar Demographic Attributes

Raster Data

13 :: Raster Data
Content: (1) What is Raster Data? (2) Satellite Images (3) Raster Information (4) Vector & Raster Conversion (5) Map Algebra (6) Contour (7) Layout (8) References

Zonal Statistics

14 :: Zonal Statistics
Content: (1) Mosaic To New Raster (2) Contour (3) Hillshade (4) Slope (5) Viewshed (6) Zonal Statistics (7) Map Layout

Zonal Statistics :: Lab Practice

14 :: Zonal Statistics :: Lab Practice
Content: (1) Mosaic To New Raster (2) Contour (3) Hillshade (4) Slope (5) Viewshed (6) Zonal Statistics (7) Map Layout

Review

15 :: Review
Content: ---

Final Exam

16 :: Final Exam
Content: Final Exam