An introduction to GIS and Remote Sensing with R

Thiago Silva 06/11/2019

There are packages for R that make it surprisingly competent for GIS (Geographic Information System) and remote sensing (satellite/aerial image processing). In this session, I will cover the basiscs of reading spatial data in, performing spatial operations, exporting results and visualizing data and analyses. It will mostly demoed by live coding.

Preparation

You should have the following packages installed ahead of time:

install.packages('rgdal', 'raster', 'sp',
                 'rgeos', 'RStoolbox', 'rasterVis',
                 'sf', 'velox', 'ggplot2', 'ggmap',
                 'mapview', 'tmap')

Data: https://drive.google.com/drive/folders/1B4fRJU0XjpoGnvP9UHNqh8PSWEVl5ctD?usp=sharing

Examples - reading data in

Reading raster data as a raster object:

library(raster)

## Read in a single band raster
ras <- raster(filename)

## Read in a multiband *single file* raster
ras2 <- brick(filename)

## Read in a multiband raster from multiple single-file bands
ras3 <- stack(file1,file2,file3)

Reading vector data as Spatial objects:

library(raster)
library(sp)

## Reading vectors using rgdal. Vector type (point, line polygon)
## is determined automagically

shp <- readOGR(dsn = 'file.shp', layer = 'file')
geojs <- 
geopkg <- 
    
## For shapefiles, the raster package has a handy shortcut:
shp <- shapefile('file.shp')

Reading vector files as sf objects:

library(sf)

geojs <- 
geopkg <- 
    
## there are quick shortcuts. Deafult for attribute table us a tibble.
shp <- read_sf(file)    

Inspecting objects and simple base ploting