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

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

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

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 :)

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

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

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

(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 )

Lets get started

http://www.qgis.org

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

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

● 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

… and start QGIS 1.9 dev.

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

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

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

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

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

Sweden 21,246,594,670.1467 km²

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

Short Break
Kort paus
Kurze Pause

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

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?

Landscape analysis preparation – (1) Raster

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

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

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

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

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

Average

Use the DEM and try it out :)

Average

● 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

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

Here could be another break

Map Presentation

Advanced Landscape Analysis Techniques
The landscape modifier

Advanced Landscape Analysis Techniques

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

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

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)

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

Image Classification

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

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

Thanks for your attention and good luck with your
projects!

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Presentation - Lund 2013 GIS workshop

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Presentation - Lund 2013 GIS workshop