Workshop I gave at the University of Lund in 2013

1. Workshop – Lund 2013 1
Landscape ecology analysis with QGIS
Workshop at Lund University (2013) by Martin Jung

2. Workshop – Lund 2013 2
About me
● Currently master student in Biology at the University of
Copenhagen
● BSc thesis about plant-pollinator networks in Białowieza
● Interested in Ecology, Conservation and species distributions

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Visit my homepage for news about conservation, ecology and QGIS
→ http://conservationecology.wordpress.com/
QGIS and me
● Primary GIS system since
2008
● Contributed a new plugin
called LecoS to the QGIS
community
● Since 2012 support of QGIS-
users on gis.stackexchange

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Roadplan for today
● Introduction in QGIS, install of QGIS and dependencies
● Get familiar with basic Raster and Vector layer processing
(introduction of common plugins)
● … Short break somewhere here ...
● Landscape Analysis with QGIS
● Map presentation
● Advanced QGIS techniques examples + Questions :)

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What is GIS?
A geographic information system (GIS) is a system designed
to capture, store, manipulate, analyze, manage, and present
types of geographical data. Wikipedia.com

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Open Source GIS solutions
● QGIS started in 2002 as an
Open Source project
● Primarily intended as
interface for Geo-databases
(POSTGIS)
● Increasing popularity since
the last years

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Functionalities
● Support for multiple file-formats
● Basic Vector processing
● Raster modifications
● Access to databases (POSTGIS,
MySQL, Spatiallite,… )
● Web-support
(WMS,WFS,Webserver,...)
● Easily extendable
????

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(Dis)Advantages of QGIS
● Pro
– Open Source
– Easy access to other Open
Source Software (R, GRASS,
Python, ...)
– Runs on all mayor OS
– Easy extendable through
plugins
– Very active global community
● Contra
– Missing features (cross-
dependencies)
– Bugs, Errors, Instability
– ( Layout capabilities )

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Lets get started

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http://www.qgis.org

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QGIS 1.9 Master
http://tinyurl.com/QGIS-Install
Workshop-Files
http://tinyurl.com/Lund-Fileshttp://tinyurl.com/Lund-Files

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Now install ...
● Make some room on your computer (at least 1 GB !)
● Install the current Development Version ( QGIS 1.9 ) on your
computer (see provided folder)
Important!
– Make sure the libraries python-scipy and python-numpy are checked

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● Select “Advanced Install”
● “Install from local Folder”
● Mark the following (or all)
– Qgis-dev
– Python-numpy
– Python-scipy
– qgis-grass-plugin
– grass64
How to install (WIN)
Install from local folder

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… and start QGIS 1.9 dev.

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GIS data
Source: maprabu.blogspot.com
Format:
*.shp, *.csv, *.gpx, *.kml, ...
Format:
*.tif, *.vrt, *.hdr, *.asc, ...

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Example Data set
● CORINE 2006 Landcover grid
● Naturalearth (National Boundaries) www.naturalearthdata.com
● GMTED 2010 DEM
● Artdatabanken (through GBIF) www.artdatabanken.se

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Load in: CORINE (g100_06.tif)
● Zoom in / Zoom out
● Explore Properties
● Enable correct styles
● Look into Layer CRS
● Disable the layer
Tasks

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Load in: State provinces (NE_Provinces.zip)
● Look into Attribute table
● Identify & remove Antarctica
● Color provinces according to
size (Graduated)
● Label the provinces
● Select provinces in Sweden
● Subset/reproject to a
Lambert Azimutal Projection
Tasks

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● Calculate the mean (+SD)
province area (in km²) in
Sweden
Final task

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Sweden 21,246,594,670.1467 km²

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QGIS and Plugins
Must have:
● SEXTANTE, Openlayers Plugin, Points2One, MMQGIS, Point
Sampling Tool, Color Ramp Manager, LecoS, ...

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Short Break
Kort paus
Kurze Pause

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The genus Lycaena
Common Copper (Lycaena phlaeas) Purple-edged Copper (Lycaena hippothoe) Scarce Copper (Lycaena virgaureae)

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Research questions
1) Where can those Lycaena species be found in Skane? (what is
the most abundant landcover-type on the landscape scale?) And
does it differ among the species?
2) Is there a different response among the species to landscape
heterogeneity?
3) Does one of the Coppers in Skane prefer higher elevations
compared to the other Coppers?
4) Is there a correlation between the number of Lycaena sp.
occurences and greater distance from forests?

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Landscape analysis preparation – (1) Raster

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Landscape analysis preparation – (2) species data
● Enable “Add Delimited text layer”-plugin in the plugin options
● Add GBIF-Lycaena.csv as vector layer

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Landscape analysis preparation –
(3) Data processing
● Remove all points outside Skane
● Check for and remove unsure
determinations (? in name)
● Apply a circular buffer of 1000m
around each point
● Display the result categorized with
different colors

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Research Question 1.)
● Crop your CORINE dataset with your buffered Occurrences
(overlapping buffers are not correctly cropped. Use UnionUnion first)
● Use “LecoS – Land cover statistics” to compute the
“Landscape proportion” of each land cover class
● Then calculate the area in m² per buffer for the most abundant
(Using “LecoS – Polygon overlay”)
● Use “Groupstats” to get the mean/median values per species

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Results Question 1.)
Results Top 3:
12 (non irrigated arable land) →35 %
24 (coniferous forest) → 22 %
23 (broad-leaved forest)→ 13 %
Total Landcover of non-irrigated arable land
Species | Landcover Median
Lycaena hippothoe 695037.9779805 m²
Lycaena phlaeas 910049.726564 m²
Lycaena virgaureae 710038.797649 m²

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Research Question 2.)
● Use “LecoS – Polygon overlay” to compute the Shannon
diversity index for each buffer
● Use “Groupstats” to display results

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Results Question 2.)
Average

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Research Question 3.)
Use the DEM and try it out :)

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Results Question 3.)
Average

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Research Question 4.)
● Combine all types of forested lands into a single raster class (QGIS
Rastercalculator)
● Then use the Proximity tool in the Raster menu
● Use the Save-As function (rightclick raster) to correctly set a nodata-
value
● Create a Vector-grid (5 km rectangles) and count the number of
Lycaena occ. inside.
● Use LecoS to extract the median values inside the grid
A bit more difficult

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Results question 4.)
Spearman's rank
correlation rho
data: layer[[y]] and
layer[[x]]
S = 4172666, p-value =
0.5529
alternative hypothesis:
true rho is not equal to 0
sample estimates:
rho
0.03462806

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Here could be another break

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Map Presentation

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Advanced Landscape Analysis Techniques
The landscape modifier

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Advanced Landscape Analysis Techniques

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Sextante Modeller
Theoretical Idea:
→ Create random points
inside Skane
→ Apply a buffer
→ Calculate number of
occurrences inside buffer
Batchrun for occurrence
probability ?

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Sextante R commands
Command Function
##[datagis]=group Sets the group to “datagis”
##layer = vector or raster Specifies the input layer to use
##distance=number 100 Sets a number field with default 100
##title=string France Get text input. Default is “France”
##field=field layer Select a field from the vector layer “layer”
hist(layer[[field]]) R-command: Histogram for fields from layer
##showplots Has to be set in order to see plot outputs
>t.test(layer[[field]]) Console output with a “>” before command
##output=output vector File output as vector or raster

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Example Script
##[Own Scripts]=group
##showplots
##layer=vector
##y=field layer
##x=field layer
library("car")
plot(as.numeric( layer[[y]] )~as.numeric( layer[[x]] ),pch=19,bty="l",ylab=paste( y ),xlab=paste( x ) )
fit = lm( layer[[y]]~layer[[x]] )
regLine(fit,col="blue",lwd=2)

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Hydrological Analysis
● Using DEMs and
hydrographic information
● What can be calculated:
– Watershed basins
– (Potential) Wetness
– Way of travel, Flood risks
– Potential location of aquifers
...
Potential Wetness based on Topography

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Image Classification

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Home-range estimation
● Possible through plugin
Animove (currently broken)
● Interface to R and package
adehabitat
● Alternative in SAGA and
Grass

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Additional examples, help and tutorials
● http://www.gistutor.com/
● http://qgis.spatialthoughts.com/
● Youtube → search QGIS
● http://gis.stackexchange.com
● QGIS-user mailing list → http://lists.osgeo.org/listinfo/qgis-user

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Thanks for your attention and good luck with your
projects!