I created land-use rasters for the city of Montreal for 2012, 2014, and 2016; all of which I converted from vectors to rasters in QGIS. I want to create a logit model to predict land-use changes. I was suggested to split up the data into a series of reclassified rasters with values 1 and 0 ... 1 representing a specific land use and 0 representing something other than that land use.
My thought is to frame my analysis around the neighborhood effect, whether a cell is susceptible to change as a function of the cells surrounding it.
I've installed all raster packages deemed relevant and uploaded the rasters into R:
install.packages("raster") install.packages("sp") install.packages("rasterVis") install.packages("rgdal") install.packages("dismo") #map raster on Google Map install.packages("lulcc") library(raster) library(sp) MTL_12<-raster("C:\\Users\\Senun\\Docs\\MTL\\QGIS\\MTL_12.tif") MTL_14<-raster("C:\\Users\\Senun\\Docs\\MTL\\QGIS\\MTL_14.tif") MTL_16<-raster("C:\\Users\\Senun\\Docs\\MTL\\QGIS\\MTL_16.tif")
All of my rasters have the same perimeters:
class : RasterLayer dimensions : 3000, 3000, 9e+06 (nrow, ncol, ncell) resolution : 13.03578, 11.03338 (x, y) extent : 267707.3, 306814.6, 5029977, 5063078 (xmin, xmax, ymin, ymax) coord. ref. : +proj=tmerc +lat_0=0 +lon_0=-73.5 +k=0.9999 +x_0=304800 +y_0=0 +datum=NAD83 +units=m +no_defs +ellps=GRS80 +towgs84=0,0,0 data source : C:\Users\Senun\Docs\MTL\QGIS\MTL_14.tif names : MTL_14 values : 0, 1100 (min, max)
I have a lot of "empty space" (0) to account for.
I'm at a loss--this is my first time working with rasters in R--on how to proceed. I couldn't find an example or tutorial dealing with multiple rasters; furthermore I have difficulty identifying my cell values. Should I start with reclassifying my pixels?