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The creator of the Terrain Analysis System (TAS) has decided to migrate his package to open source. The new version of the software, now called “Whitebox Geospatial Analysis Tools” is available for download from the department homepages.

Prof. John Lindsay is currently looking for potential graduate students (Masters) to join his research programme at the University of Guelph. Interested individuals are encouraged to contact him.

Map of events

The lecture theatre during Geomorphometry 2009 is Y35F32 where Y stands for Irchel campus, 35 is the building number, F is the floor and 32 is the room number.**
Download the campus map as PDF.**

Other useful links:

[ZVV] (Zurich public transport association): Timetable, information about tickets and fares, leisure and tourist information; [SBB] (Swiss Federal Railways): Timetable, information about tickets and fares. Both the ZVV and the SBB timetables combine information about the schedules of trains, trams, busses, ships.; [Website of Zurich Tourism]: Accomodation, tours and excursions, restaurants, events etc. [Zurich Airport]: Flight, transfer and general travel information; [Zurich webcams]; [Switzerland Tourism]; [MeteoSwiss]; [Webmaps]; [Webmap of Zurich Tourism]

Hotels Conorado and Sternen-Oerlikon offer special rates for university-related stays!

For all logistics issues, please feel free to contact the logistics chief: Ralph Straumann.

Attachment: Geomorphometry2009.zip

Perhaps some of presentations could be of interest to geomorphometrists?

Lucian Drãgut, Ulrich Walz and Thomas Blaschke have organized the 6th Symposium- The third and fourth dimensions of landscapes- within the European Conference IALE2009. The contents of presentations in the symposium, as well as introduction and concluding remarks are available below:

1. Introduction

2. Höchstetter & Walz- 3D-metrics in landscape ecology – Methods and examples of use

3. Laszczak & Kozak- Assessment of structural connectivity of a forested landscape in Poland using graph theory approach

4. Victorov- Landscape metrics selection based on the mathematical models of landscape patterns

5. Wickham & Riiters- A critique of patch-based landscape indicators for detection of temporal change in fragmentation

6. Van Eetvelde & Käyhkö- The applicability of quantitative techniques for assessing spatio-temporal patterns of landscape changes

7. Werbrouck, Van Eetvelde, Antrop & De Maeyer- Integrating historical maps and LiDAR elevation data for landscape reconstruction

8. Marceau- Scale issues in Landscape Ecology research: A synthesis

9. Scolozzi & Geneletti- A method to assess landscape functional connectivity at local scale for target species

10. Díaz-Varela, Álvarez-Álvarez & Marey-Pérez- Influence of landscape pattern on scale divergence in categorical maps

11. Völker & Büker- Automatic remote sensing methods for the monitoring of agricultural landscape lements in the context of IACS and cross compliance. Poster.

12. Stupariu, Patru-Stupariu & Cuculici- Geometric techniques in quantifying landscape irregularities. Poster.

13. Nedkov & Gikov- Modeling landscape heterogeneity in mountain areas: a case study from Rhodope Mountains, Bulgaria. Poster.

14. Concluding remarks

This is a sample code to process Baranja hill DEM using a combination of R, SAGA, ILWIS and Google Earth (under MS Windows machines). All four packages are available as open source or freeware (GE). You first need to obtain and install R (including the maptools, gstat, rgdal and RSAGA packages), ILWIS 3.5, SAGA GIS and GRASS GIS. After you finished installing R, SAGA, ILWIS, GRASS, copy the code down-below and start running it line by line. If you experience problems, send as a post via the R-sig-geo or ILWIS mailing list. Note: in order to use the functionality of ILWIS, SAGA, GRASS, you need to install them first. These are not internal packages in R!

Fig: Screenshots of R + SAGA/GRASS/ILWIS integration

######## R script ###############
# DEM processing and extraction of channel networks;
library(maptools)
library(rgdal)
library(RSAGA)
# ! first download and install SAGA GIS [http://www.saga-gis.org], ILWIS GIS [https://52north.org/download/Ilwis/52n-Ilwis-v3-05-02.zip] and GRASS GIS [http://grass.itc.it] to your machine!
rsaga.env(path="C:/Progra~1/saga_vc")
ILWIS <- "C:\Progra~1\N52\Ilwis35\IlwisClient.exe -C"
MGI_Z6 <- "+proj=tmerc +lat_0=0 +lon_0=18 +k=0.9999 +x_0=6500000 +y_0=0 +ellps=bessel +towgs84=550.499,164.116,475.142,5.80967,2.07902,-11.62386,0.99999445824 +units=m"
# The coordinate system is "MGI Zone 6"; see [http://spatial-analyst.net/wiki/index.php?title=MGI_/_Balkans_coordinate_systems]
setwd("C:/tmp")
# obtain the data:
download.file("http://geomorphometry.org/system/files/BaranjaHill.zip", destfile=paste(getwd(), "BaranjaHill.zip", sep="/"))
fname <- zip.file.extract(file="DEM25m.asc", zipname="BaranjaHill.zip")
file.copy(fname, "./DEM25m.asc", overwrite=TRUE)
list.files(pattern="asc")
dem25m <- readGDAL("DEM25m.asc")
proj4string(dem25m) <- CRS(MGI_Z6)
# view the data in ILWIS:
writeGDAL(dem25m[1], "dem25m.mpr", "ILWIS")
# set the right coordinate system!
download.file("http://spatial-analyst.net/CRS/gk_6.csy", destfile=paste(getwd(), "gk_6.csy", sep="/"))
shell(cmd=paste(ILWIS, "setcsy dem25m.grf gk_6.csy -force"), wait=F)
shell(cmd=paste(ILWIS, "open dem25m.mpr -noask"), wait=F)
# make a relief view in ILWIS:
shell(cmd=paste(ILWIS, "run C:\Progra~1\Ilwis3\Scripts\Hydro-DEM\dem_visualization dem25m.mpr dem25m_c.mpr"), wait=F)
# load to SAGA and derive drainage network:
rsaga.esri.to.sgrd(in.grids="dem25m.asc", out.sgrds="dem25m.sgrd", in.path=getwd())
# First, fill the spurious sinks:
rsaga.get.modules("ta_preprocessor")
rsaga.get.usage("ta_preprocessor", 2)
rsaga.geoprocessor(lib="ta_preprocessor", module=2, param=list(DEM="dem25m.sgrd", RESULT="dem25m_f.sgrd", MINSLOPE=0.05))
# Second, extract the channel network:
rsaga.get.modules("ta_channels")
rsaga.get.usage("ta_channels", 0)
rsaga.geoprocessor(lib="ta_channels", module=0, param=list(ELEVATION="dem25m.sgrd", CHNLNTWRK="channel_ntwrk.sgrd", CHNLROUTE="channel_route.sgrd", SHAPES="channels2.shp", INIT_GRID="dem25m.sgrd", DIV_CELLS=3, MINLEN=40))
channels <- readOGR("channels.shp", "channels")
spplot(channels["LENGTH"], col.regions=bpy.colors())
# derive Topographic Wetness Index:
rsaga.geoprocessor(lib="ta_hydrology", module=15, param=list(DEM="dem25m.sgrd", C="catharea.sgrd", GN="catchslope.sgrd", CS="modcatharea.sgrd", SB="TWI.sgrd", T=10))
# Export of grids to Google Earth using SAGA GIS:
rsaga.geoprocessor(lib="pj_proj4", 2, param=list(SOURCE_PROJ=paste('"', proj4string(dem25m), '"', sep=""), TARGET_PROJ=""+proj=longlat +datum=WGS84"", SOURCE="TWI.sgrd", TARGET="TWI_ll.sgrd", TARGET_TYPE=0, INTERPOLATION=0))
# export to PNG:
rsaga.geoprocessor(lib="io_grid_image", 0, param=list(GRID="TWI_ll.sgrd", FILE="TWI.png"))
# read back to R:
rsaga.sgrd.to.esri(in.sgrds="TWI_ll.sgrd", out.grids="TWI_ll.asc", prec=1, out.path=getwd())
TWI.ll <- readGDAL("TWI_ll.asc")
proj4string(TWI.ll) <- CRS("+proj=longlat +datum=WGS84")
TWI.kml <- GE_SpatialGrid(TWI.ll)
kmlOverlay(TWI.kml, kmlfile="TWI.kml", imagefile="TWI.png", name="Topographic Wetness Index")
# Optional: export to Google Earth using ILWIS:
dem25m.ll <- spTransform(dem25m[1], CRS("+proj=longlat +datum=WGS84"))
corrf <- (1+cos((dem25m.ll@bbox[2,2]+dem25m.ll@bbox[2,1])/2*pi/180))/2
geogrd.cell <- corrf*(dem25m.ll@bbox[1,2]-dem25m.ll@bbox[1,1])/dem25m@grid@cells.dim[1]
geoarc <- spsample(dem25m.ll, type="regular", cellsize=c(geogrd.cell,geogrd.cell))
gridded(geoarc) <- TRUE
gridparameters(geoarc)
gridparameters(dem25m)
# resample the map (Bilinear) to the new geographic grid:
shell(cmd=paste(ILWIS, " crgrf geoarc.grf ",geoarc@grid@cells.dim[[2]]," ",geoarc@grid@cells.dim[[1]]," -crdsys=LatlonWGS84 -lowleft=(",geoarc@grid@cellcentre.offset[[1]],",",geoarc@grid@cellcentre.offset[[2]],") -pixsize=",geoarc@grid@cellsize[[1]],sep=""), wait=F)
shell(cmd=paste(ILWIS, "dem25m_ll_c.mpr = MapResample(dem25m_c.mpr, geoarc, BiLinear)"), wait=F)
shell(cmd=paste(ILWIS, "open dem25m_ll_c.mpr -noask"))
shell(cmd=paste(ILWIS, "export tiff(dem25m_ll_c.mpr, dem25m_c.tif)"), wait=F)
# generate a KML (ground overlay):
dem25m.kml <- GE_SpatialGrid(geoarc)
kmlOverlay(dem25m.kml, "dem25m_c.kml", "dem25m_c.tif", name="Shaded relief in ILWIS")
# export of extracted channels to Google Earth:
proj4string(channels) <- CRS(MGI_Z6)
channels.ll <- spTransform(channels[3], CRS("+proj=longlat +datum=WGS84"))
writeOGR(channels.ll, "channels.kml", "channels", "KML")
# extract the drainage network in GRASS GIS:
library(spgrass6) # version => 0.6-1 (http://spatial.nhh.no/R/Devel/spgrass6_0.6-1.zip (71))
# Location of your GRASS installation:
loc <- initGRASS("C:/GRASS", home=tempdir())
loc
# Import the ArcInfo ASCII file to GRASS:
parseGRASS("r.in.gdal") # commmand description
execGRASS("r.in.gdal", flags="o", parameters=list(input="DEM25m.asc", output="DEM"))
execGRASS("g.region", parameters=list(rast="DEM"))
gmeta6()
# extract the drainage network:
execGRASS("r.watershed", flags=c("m", "overwrite"), parameters=list(elevation="DEM", stream="stream", threshold=as.integer(50)))
# thin the raster map so it can be converted to vectors:
execGRASS("r.thin", parameters=list(input="stream", output="streamt"))
# convert to vectors:
execGRASS("r.to.vect", parameters=list(input="streamt", output="streamt", feature="line"))
streamt <- readVECT6("streamt")
plot(streamt)
######## R script ###############

MORE READING:

1. Bivand, R. 2005. Interfacing GRASS 6 and R. Status and development directions, GRASS Newsletter, 3, 11–16.
2. Bivand, R., Pebesma, E., Rubio, V., 2008. Applied Spatial Data Analysis with R. Use R Series, p. 400. Springer, Heidelberg, pp. 378.
3. Brenning, A. 2008. Statistical geocomputing combining R and SAGA: The example of landslide susceptibility analysis with generalized additive models. In: J. Böhner, T. Blaschke & L. Montanarella (eds.), SAGA - Seconds Out (= Hamburger Beiträge zur Physischen Geographie und Landschaftsökologie, 19), 23-32.
4. Conrad, O. 2007. SAGA — Entwurf, Funktionsumfang und Anwendung eines Systems fur Automatisierte Geowissenschaftliche Analysen, Ph.D. thesis, University of Gottingen, Gottingen.
5. Grohmann, C.H. 2004. Morphometric analysis in Geographic Information Systems: applications of free software GRASS and R. Computers & Geosciences, 30 (9-10):1055-1067.
6. Hengl, T., 2009. A Practical Guide to Geostatistical Mapping. 2nd Ed, University of Amsterdam, 291 p.
7. Neteler, M. and Mitasova, H. 2008. Open Source GIS: A GRASS GIS Approach, Springer, New York, 3rd edn.

Attachment:

SAGA_ILWIS_GRASS_0.zip

A title in the Developments in Soil Science series volume 33. Read this book using the AmazonOnlineReader!

Table of content:

• Foreword
• **Part 1 **
• 1. Geomorphometry: A Brief Guide
• 1. Mathematical and Digital Models of the Land Surface
• 1. DEM Production Methods and Sources
• 1. Preparation of DEMs for Geomorphometric Analysis
• 1. Geostatistical Simulation and Error Propagation in Geomorphometry
• 1. Basic Land-Surface Parameters
• 1. Land-Surface Parameters and Objects in Hydrology
• 1. Land-Surface Parameters Specific to Topo-Climatology
• 1. Landforms and Landform Elements in Geomorphometry
• **Part 2 **
• 1. Overview of Software Packages Used in Geomorphometry
• 1. Geomorphometry in ESRI Packages
• 1. Geomorphometry in SAGA
• 1. Geomorphometry in ILWIS
• 1. Geomorphometry in LandSerf
• 1. Geomorphometry in MicroDEM
• 1. Geomorphometry in TAS GIS
• 1. Geomorphometry in GRASS GIS
• 1. Geomorphometry in RiverTools
• **Part 3 **
• 1. Geomorphometry - A Key to Landscape Mapping and Modelling
• 1. Soil Mapping Applications
• 1. Vegetation Mapping Applications
• 1. Applications in Geomorphology
• 1. Modelling Mass Movements and Landslide Susceptibility
• 1. Automated Predictive Mapping of Ecological Entities
• 1. Geomorphometry and Spatial Hydrologic Modelling
• 1. Applications in Meteorology
• 1. Applications in Precision Agriculture
• 1. The Future of Geomorphometry
• Bibliography
• Index
• Colour Plate Section

How to cite?

The book can be cited as:

Hengl, T., Reuter, H.I. (eds) 2008. Geomorphometry: Concepts, Software, Applications. Developments in Soil Science, vol. 33, Elsevier, 772 pp.

To refer to a specific chapter, please write e.g.:

Pike, R.J., Evans, I.S., Hengl, T., 2008. Geomorphometry: a Brief Guide. In: Hengl, T. and Reuter, H.I. (Eds), Geomorphometry: Geomorphometry: Concepts, Software, Applications. Developments in Soil Science, vol. 33, Elsevier, 1-28 pp.

*Note that each specific chapter of the book has an unique DOI.

Specific chapter of the book can be obtained separately from the Elsevier’s ScienceDirect service.

How to obtain the data set?

The Baranja Hill data set used in this book can be obtained here. It comprises various data layers ranging from a TOPO DEM, SRTM DEM, original point measurements of heights, contour lines from the 1:25k and 1:5k scale topo-maps and various other thematic layers.

Attachment:

Pike_2008_Geomorphometry_ch1.pdf

Geomorphometry_bookflyer_Hengl.pdf