Publications by MD
GEOG71921 Welcome
Welcome to GEOG70922. On this course, lab instructions will be posted as html and a web link will be provided each week for you to work through in the practical sessions. Open R studio from the Start Menu and pres Ctrl + Shift + N. A new script will open. Have a look around the R Studio IDE. Code for you to enter in R Studio will be presented ag...
2049 sym R (1419 sym/22 pcs) 12 img
GEOG70922 Week1
In the first practical for GEOG70922 we will familiarise ourselves with the R working environment and consider the effects of resolution, resampling and spatial data aggregation in our analysis. We looked at these ideas in the lecture and also briefly in GEOG60951. Here we will go into a little more depth and experiment with some simulated (or �...
13420 sym R (7472 sym/87 pcs) 16 img
Document
#load packages install.packages("sp") # for spatial (vector) objects install.packages("dismo") # for generating background data install.packages("adehabitatHR") # for computing home range install.packages("adehabitatHS") # for computing resource selection install.packages("rgdal") # for projections - this can take a while to load so please b...
5 sym R (5941 sym/3 pcs)
Species Distribution Modelling One: Solution
setwd("P:/GEOG70922/Week5") install.packages(c("dismo","maptools","glmnet","maxnet","raster","sp")) library(dismo) files <- list.files(path=paste(system.file(package="dismo"), '/ex', sep=''), pattern='grd', full.names=TRUE ) files env<-stack(files[1:8]) #use the names() function to label each covariate ...
5 sym R (11891 sym/1 pcs)
GEOG70922 Distributions 1
In this week’s pratical we will take our first step into species distribution modelling. We will see that there are multiple options for modelling the distribution of species and that all depend on point data and the extraction of environmental factors to those points. First, let’s set the working directory and install the packages that we wi...
20321 sym R (20585 sym/100 pcs) 28 img
Handy hints for working in R
#working with vectors #characters: vChr<-c("One","Two","Three","Four") #numeric vector vNum<-c(1,2,3,4) #creating a data frame df<-data.frame(vChr,vNum) head(df) ## vChr vNum ## 1 One 1 ## 2 Two 2 ## 3 Three 3 ## 4 Four 4 #set column names colnames(df)<-c("Character","Number") #selecting rows and columns. ...
8376 sym R (12410 sym/93 pcs) 11 img
Week 3 Home range and resource selection
In today’s practical we will look at two spatially oriented and closely aligned areas of species ecology: range and resource selection. We will explore some of the ideas covered in the lecture using a telemetry dataset of Canis lupus (grey wolf) from a 2006 monitoring campaign in the Alberta region of Canada. We will use these data to explore o...
12277 sym R (15728 sym/83 pcs) 17 img
GEOG70922 Space (resource selection and home range)
In today’s practical we will look at two spatially oriented and closely aligned areas of species ecology: range and resource selection. We will explore some of the ideas covered in the lecture using a telemetry dataset of Canis lupus (wolves) from a 2006 monitoring campaign in the Alberta region of Canada. We will use these data to explore opti...
12279 sym R (14725 sym/80 pcs) 17 img
GEOG70922 R Basics
setwd("C:/SE") #working with vectors #characters: vChr<-c("One","Two","Three","Four") #numeric vector vNum<-c(1,2,3,4) #creating a data frame df<-data.frame(vChr,vNum) head(df) ## vChr vNum ## 1 One 1 ## 2 Two 2 ## 3 Three 3 ## 4 Four 4 #selecting rows and columns. #use squared brackets to select x(rows) and ...
22 sym R (1497 sym/16 pcs)
GEOG709222
In practical 2 of GEOG70922 we will cover a range of spatial techniques in R that are central to working with spatial data in ecology. Today you will learn how to: 1) convert tabulated data to spatial point distributions, 2) crop data quickly and neatly to a desired study extent, 3) reclassify a raster for more focussed analysis, 4) provide backg...
20374 sym R (22564 sym/82 pcs) 9 img