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<!DOCTYPE html>
<html lang="" xml:lang="">
<head>
<title>Geocoding with sf</title>
<meta charset="utf-8" />
<meta name="author" content="Carlo Greß and Johannes Halkenhäusser" />
<meta name="date" content="2021-11-04" />
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class: center, middle, inverse, title-slide
# Geocoding with sf
## Introduction to Data Science Workshop
### Carlo Greß and Johannes Halkenhäusser
### Hertie School
### 4 November 2021
---
# Table of contents
<br>
1. [What is geocoding?](#definition)
2. [Geocoding in R](#application)
3. [The **s**imple **f**eatures package in R](#package)
4. [How to use the sf package for geocoding](#howto)
5. [A practical application](#application)
6. [Summary](#summary)
---
class: inverse, center, middle
name: definition
# What is geocoding?
---
# What is geocoding?
- Turning addresses or locations into geographic positions
- Location of the Hertie School (Friedrichsstraße 180, 10117 Berlin) -> 52.512963808601505, 13.389202140609111
- The geographic position is commonly expressed in **latitude** and **longitude**
- Latitude refers to the north-south position of a point
- Longitude refers to the east-west position of a point
- **Reverse-geocoding** takes given coordinates and translates them into an address
- Both types of geocoding are helpful whenever the location of variables is at the center of attention:
- Where do legislators have their offices?
- Where do conservative voters live?
- Are there geographical patterns in the development of COVID-19 spread?
---
class: inverse, center, middle
name: application
# Geocoding in R
---
# Geocoding in R
- Before starting with the substantial analysis, input data needs to be read in into R
- Geocoding analysis distinguishes between two main input data types: **Relative** and **absolute** input data
- Relative input data refers to **descriptions** of locations and cannot directly be translated into precise geographic data points
- Instead, reference locations whose coordinates are known are used for approximation
- Absolute input data refers to data that can be directly translated into coordinates
- Postal addresses and ZIP codes, cities, places
- Unsurprisingly, the latter data format is usually desired due to a more intuitive use and higher precision
---
class: inverse, center, middle
name: package
# The **s**imple **f**eatures package in R
---
# The **s**imple **f**eatures package in R
- Simple features is not limited to the package in R, but rather is a formal standard describing the geographic representation of real-world objects in computers
- A **feature** commonly relates to such real-world objects, e.g. a street, a city, or a building
- These are represented by several simple features types
- Most common types: points, linestrings, polygons
- The simple features package in R provides access to the simple feature standard
- It offers multiple functions that are beneficial for working with geodata
- Calculating surface area or distance, identifying whether a point lays in a given area, creating a point at the centre of an area
---
class: inverse, center, middle
name: howto
# How to use the sf package for geocoding
---
#How to use the sf package for geocoding
- Read in the **input data** (for example, your address or the postal code of your home town)
- For this purpose, numerous sources as the *Open Street Map* or the Google Maps API can be used
- The build-in `st_read`-command enables users to read in existing datasets and stores them as data.frame
---
class: inverse, center, middle
name: application
# A practical application
---
class: inverse, center, middle
name: summary
# Summary
---
</textarea>
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