Geography 13
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Geography 13
Introduction to Spatial Data Science
Mike Johnson
- Summer Session A
Comprehensive overview of data science and its applications to Geography and GIS.
Syllabus
—
Lab Activites
–
People
Week 1
: Computational Environment
Lecture 01
:
Introduction
Lecture 02
:
Geoinformatics
Lecture 03
:
The Digital Environment
Lecture 04
:
Data Types & Structure
Exercise 01
:
Set up R & RStudio
Exercise 02
:
Intro to Bash / Git Install
Exercise 03
:
Your first Project
Exercise 04
:
Forking & Rmarkdown
Week 2
: Working with Tables
HOLIDAY
: No Class
Lecture 05
:
Data Frame Manipulation
Lecture 06
:
Data Visualization
Lecture 07
:
Relations & Formats
HOLIDAY
: No exercise
Exercise 05
:
dplyr
verbs
Exercise 06
:
Your first plots
Exercise 07
:
Joins & Pivots
Week 3
: Vector Data 1
HOLIDAY
: No Class
Lecture 08
:
Working with Tables Wrap Up
Lecture 09
:
Spatial Data Libraries
Lecture 10
:
Feature Geometries
HOLIDAY
: No exercise
Exercise 08
:
Lags & Rolling Means
Exercise 09
:
Setting up R as a GIS
Exercise 10
:
Feature Geometries
Week 4
: Vector Data 2
Lecture 11
:
Coordinate Reference Systems
Lecture 12
:
Spatial Predicates
Lecture 13
:
Unary, Binary, Simplification
Lecture 14
:
Point-in-Polygon / Writing functions
Exercise 11
:
Projecting Data
Exercise 12
:
Spatial filtering
Exercise 13
:
Simplification
Exercise 14
:
Your first function
Week 5
: Field Data 1
Lecture 15
:
MAUP and Tesselations
Lecture 16
:
Interactive Web Mapping
Leaflet Examples
Lecture 17
:
The Raster Data Model
Lecture 18
:
Raster Data Manipulation
Exercise 15
:
Building Tesselations
Exercise 16
:
Create a Leaflet map
Exercise 17
:
Your first raster
Exercise 18
:
Managing your data values
Week 6
: Field Data 2
Lecture 19
:
Map Algebra and OSM
Lecture 20
:
Categorization
Lecture 21
:
Terrain Analysis
Lecture 22
: Wrap up
Exercise 19
:
OpenStreetMap and Value Extraction
Exercise 20
:
Climate Classification
Exercise 21
:
Terrain Processing
Exercise 22
: Complete ESCII Evaluations
Final