Introducing sp objects Working with Geospatial Data in R Data - - PowerPoint PPT Presentation

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Introducing sp objects Working with Geospatial Data in R Data - - PowerPoint PPT Presentation

Jun 03, 2023 91 likes •400 views

Working with Geospatial Data in R Introducing sp objects Working with Geospatial Data in R Data frames arent a great way to store spatial data > head(ward_sales) ward lon lat group order num_sales avg_price 1 1 -123.3128

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SLIDE 1

Working with Geospatial Data in R

Introducing sp objects

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SLIDE 2

Working with Geospatial Data in R

Data frames aren’t a great way to store spatial data

> head(ward_sales) ward lon lat group order num_sales avg_price 1 1 -123.3128 44.56531 0.1 1 159 311626.9 2 1 -123.3122 44.56531 0.1 2 159 311626.9 3 1 -123.3121 44.56531 0.1 3 159 311626.9 ... 4 1 -123.3119 44.56531 0.1 4 159 311626.9 5 1 -123.3119 44.56485 0.1 5 159 311626.9 6 1 -123.3119 44.56430 0.1 6 159 311626.9 > nrow(ward_sales) [1] 4189

  • No easy way to keep coordinate reference system

information

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SLIDE 3

Working with Geospatial Data in R

Data frames aren’t a great way to store spatial data

> head(ward_sales) ward lon lat group order num_sales avg_price 1 1 -123.3128 44.56531 0.1 1 159 311626.9 2 1 -123.3122 44.56531 0.1 2 159 311626.9 3 1 -123.3121 44.56531 0.1 3 159 311626.9 ... 4 1 -123.3119 44.56531 0.1 4 159 311626.9 5 1 -123.3119 44.56485 0.1 5 159 311626.9 6 1 -123.3119 44.56430 0.1 6 159 311626.9 > nrow(ward_sales) [1] 4189

  • Inefficient for complicated spatial objects
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SLIDE 4

Working with Geospatial Data in R

Data frames aren’t a great way to store spatial data

> head(ward_sales) ward lon lat group order num_sales avg_price 1 1 -123.3128 44.56531 0.1 1 159 311626.9 2 1 -123.3122 44.56531 0.1 2 159 311626.9 3 1 -123.3121 44.56531 0.1 3 159 311626.9 ... 4 1 -123.3119 44.56531 0.1 4 159 311626.9 5 1 -123.3119 44.56485 0.1 5 159 311626.9 6 1 -123.3119 44.56430 0.1 6 159 311626.9 > nrow(ward_sales) [1] 4189

  • Hierarchical structure gets forced into a flat structure
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SLIDE 5

Working with Geospatial Data in R

The sp package:

  • provides classes for storing different types of spatial data
  • provides methods for spatial objects, for manipulation
  • is useful for point, line and polygon data
  • is a standard, so new spatial packages expect data in an sp
  • bject
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SLIDE 6

Working with Geospatial Data in R

Let’s practice!

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SLIDE 7

Working with Geospatial Data in R

sp and S4

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Working with Geospatial Data in R

Two types of sp object

> summary(countries_sp) Object of class SpatialPolygons Coordinates: min max x -180 180.00000 y -90 83.64513 Is projected: FALSE proj4string : [+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0] > summary(countries_spdf) Object of class SpatialPolygonsDataFrame Coordinates: min max x -180 180.00000 y -90 83.64513 Is projected: FALSE proj4string : [+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0] Data attributes: name iso_a3 Length:177 Length:177 ... Class :character Class :character Mode :character Mode :character

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SLIDE 9

Working with Geospatial Data in R

> summary(countries_sp) Object of class SpatialPolygons Coordinates: min max x -180 180.00000 y -90 83.64513 Is projected: FALSE proj4string : [+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0] > summary(countries_spdf) Object of class SpatialPolygonsDataFrame Coordinates: min max x -180 180.00000 y -90 83.64513 Is projected: FALSE proj4string : [+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0] Data attributes: name iso_a3 Length:177 Length:177 ... Class :character Class :character Mode :character Mode :character

Two types of sp object

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Working with Geospatial Data in R

> str(countries_sp, max.level = 2) Formal class 'SpatialPolygons' [package "sp"] with 4 slots ..@ polygons :List of 177 .. .. [list output truncated] ..@ plotOrder : int [1:177] 7 136 28 169 31 23 9 66 84 5 ... ..@ bbox : num [1:2, 1:2] -180 -90 180 83.6 .. ..- attr(*, "dimnames")=List of 2 ..@ proj4string:Formal class 'CRS' [package "sp"] with 1 slot

SpatialPolygons object

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SLIDE 11

Working with Geospatial Data in R

> str(countries_spdf, max.level = 2) Formal class 'SpatialPolygonsDataFrame' [package "sp"] with 5 slots ..@ data :'data.frame': 177 obs. of 6 variables: ..@ polygons :List of 177 .. .. [list output truncated] ..@ plotOrder : int [1:177] 7 136 28 169 31 23 9 66 84 5 ... ..@ bbox : num [1:2, 1:2] -180 -90 180 83.6 .. ..- attr(*, "dimnames")=List of 2 ..@ proj4string:Formal class 'CRS' [package "sp"] with 1 slot

SpatialPolygonsDataframe object

?

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SLIDE 12

Working with Geospatial Data in R

S4

  • One of R’s object oriented (OO) systems
  • Key OO concepts
  • class: defines a type of object, their aributes and their

relationship to other classes.

  • methods: functions, behavior depends on class of input
  • S4 objects can have a recursive structure, elements are

called slots

  • hp://adv-r.had.co.nz/OO-essentials.html#s4
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Working with Geospatial Data in R

> # 1. Use a dedicated method > proj4string(countries_sp) [1] "+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0" > # 2. Use the @ followed by unquoted slot name > countries_sp@proj4string CRS arguments: +proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0 > # 3. Use slot() with quoted slot name > slot(countries_sp, "proj4string") CRS arguments: +proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0

Accessing slots

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SLIDE 14

Working with Geospatial Data in R

Let’s practice!

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SLIDE 15

Working with Geospatial Data in R

More sp classes and methods

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Working with Geospatial Data in R

Hierarchy of SpatialPolygonsDataFrame

[,1] [,2] [1,] -94.81758 49.38905 [2,] -94.64000 48.84000 [3,] -94.32914 48.67074 [4,] -93.63087 48.60926 [5,] -92.61000 48.45000 SpatialPolygonsDataFrame list Polygons Polygon list

@data @polygons @bbox … @Polygons @plotOrder @labpt … @coords … … … … …

countries_spdf

@labpt

Polygons Polygons Polygons Polygon Polygon Polygon

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Working with Geospatial Data in R

Other sp classes

Polygons Polygon SpatialPolygonsDataFrame

+ data.frame

SpatialPolygons @bbox @proj4string

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Working with Geospatial Data in R

Other sp classes

Lines Line SpatialLinesDataFrame

+ data.frame

SpatialLines @bbox @proj4string

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Working with Geospatial Data in R

Other sp classes

SpatialPointsDataFrame

+ data.frame

SpatialPoints @bbox @proj4string

[,1] [,2] [1,] -94.81758 49.38905 [2,] -94.64000 48.84000 [3,] -94.32914 48.67074 [4,] -93.63087 48.60926 [5,] -92.61000 48.45000

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SLIDE 20

Working with Geospatial Data in R

Subseing sp objects

> # Subset by index > str(countries_spdf[1, ], max.level = 2) Formal class 'SpatialPolygonsDataFrame' [package "sp"] with 5 slots ..@ data :'data.frame': 1 obs. of 6 variables: ..@ polygons :List of 1 ..@ plotOrder : int 1 ..@ bbox : num [1:2, 1:2] 60.5 29.3 75.2 38.5 .. ..- attr(*, "dimnames")=List of 2 ..@ proj4string:Formal class 'CRS' [package "sp"] with 1 slot

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Working with Geospatial Data in R

Let’s practice!

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Working with Geospatial Data in R

Introduction to tmap

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Working with Geospatial Data in R

tmap displays spatial data

  • Similar philosophy to ggplot2:
  • a plot is built up in layers
  • ggplot2 expects data in data frames, 


tmap expects data in spatial objects

  • layers consist of a type of graphical representation and

mapping from visual properties to variables

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Working with Geospatial Data in R

Building plot in layers

> library(tmap) > data(Europe) > tm_shape(Europe) + tm_borders()

A SpatialPolygonsDataFrame Specify spatial data Add a layer to the plot

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Working with Geospatial Data in R

Building plot in layers

> library(tmap) > data(Europe) > tm_shape(Europe) + tm_borders() + tm_fill(col = "part") + tm_compass() + tmap_style("cobalt")

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Working with Geospatial Data in R

> library(tmap) > data(Europe) > tm_shape(Europe) + tm_borders() + tm_fill(col = "part") + tm_compass() + tmap_style("cobalt")

tm_fill() tm_borders() tm_polygons() tm_bubbles() tm_dots() tm_lines() tm_raster() tm_text()

Building plot in layers

Adding another data layer

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Working with Geospatial Data in R

> library(tmap) > data(Europe) > tm_shape(Europe) + tm_borders() + tm_fill(col = "part") + tm_compass() + tmap_style("cobalt")

Building plot in layers

A non-data layer Control over other visual elements

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Working with Geospatial Data in R

Key differences to ggplot2

  • No scale_ equivalents, tweaks to scales happen in

relevant layer call

  • tm_shape() defines default data for any subsequent

layers, you can have many in a single plot

  • No need for x and y aesthetics, these are inherent in

spatial objects

  • No special evaluation, when mapping variables they must

be quoted

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SLIDE 29

Working with Geospatial Data in R

Let’s practice!