Chapter 11 Interpolation with Array of Things Data
11.1 Overview
This workshop continues teaching interpolation in R using Array of Things data. This is based on Part 2 of the Array of Things workshop put together by Marynia Kolak at the CSDS.
11.2 Download data
Please download data for this workshop by going to the following link and right-clicking on “Raw”, then saving the link as a CSV on your computer.
Or, you can run the following code in your console:
download.file("https://github.com/spatialanalysis/workshop-notes/raw/master/data/node_temps.csv", destfile = "node-temps.csv")
Also download a copy of the Chicago Community Area data here, or use the API Endpoint (copy and paste into your console).
library(sf)
areas <- st_read("https://data.cityofchicago.org/resource/igwz-8jzy.geojson")
## Reading layer `igwz-8jzy' from data source `https://data.cityofchicago.org/resource/igwz-8jzy.geojson' using driver `GeoJSON'
## Simple feature collection with 77 features and 9 fields
## geometry type: MULTIPOLYGON
## dimension: XY
## bbox: xmin: -87.94011 ymin: 41.64454 xmax: -87.52414 ymax: 42.02304
## epsg (SRID): 4326
## proj4string: +proj=longlat +datum=WGS84 +no_defs
Challenge
head()
, str()
, summary()
, and plot()
Challenge
ggplot2
.
Challenge
as_Spatial(sf)
should do the trick.
Challenge
Challenge
11.3 Links
- When you can’t find great R documentation of concepts, ArcGIS documentation will do: Semivariogram and covariance functions
- Alternate explanation of how to interpolate with kriging (also uses proprietary GIS software): Kriging interpolation
- Variogram tutorial that provides some good, clear explanation of complicated concepts