Markus Neteler Fondazione E. Mach - CRI Italy, [email protected]
GRASS GIS and Sextante e t y n l
Quarte Giornate Italiane di gvSIG a a t t I x
, 19-21 April 2011, Udine, Italy e e S
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s e t u r k r a a u M Q SEXTANTE Overview By Victor Olaya
● SEXTANTE ("Sistema EXTremeño de ANálisis TErritorial" in Spanish)
● GIS library written in Java: an extensive set of geoprocessing modules.
● Developed under the auspices of the government of the Spanish autonomous region of Extremadura
● has evolved into an all-purpose solution and continues to cover new fields of application, such as ecology and archaeology e t y n ● l a
Usable as extension in many open source Java GIS a t t I x
, (such as gvSIG, uDig or OpenJUMP) e e S
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Functionality v S g S
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● R Hundreds of modules provide raster and vector data processing tools, e G
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tabular data analysis and diagrams i l 1 a 0 t I 2
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Speciality: WPS support and link to the GRASS GIS geoprocessing r t e a l n e
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s e t u r k r http://www.sextantegis.com/ a a u M Q SEXTANTE History By Victor Olaya
The SEXTANTE project was launched in 2004 with the main goal of developing a GIS solution specially designed for the needs of regional goverment foresters.
● first version based on the German software SAGA with 190+ algorithms
● in the following years gvSIG became a full fledged GIS, including
new features such as support for Web services e t y n l a a
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Sextante was migrated to gvSIG in order to enrich its functionality I x
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The import/export routines and other from the management layer , S I G I G S are used from gvSIG to avoid duplication v S g S
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s e t u r k r a a u M Q SEXTANTE Overview
Functionalities ● pattern analysis ● hydrological analysis ● geostatistics ● geomorphometry and relief analysis, ● including visibility and profiles ●
analysis and calculation of raster layerse t y n ● l a
fuzzy logic a t t I x ● , rasterization and interpolation e e S
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image processing and analysis d n U a
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vegetation indices S I G I
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Features i l 1 a
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Graphical user interface and command line I 2
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geoprocessing manager e a l n e
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a batch processing manager o e i N G
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a model generator (modeller) s e t u r
● k r history of commands executed by the user so a a u
that the processes can be repeated easily. M Q SEXTANTE By Victor Olaya Architecture
GRASS SEXTANTE WPS algorithms algorithms algorithms e t y n l a a t t I x
SEXTANTE GUI , e e S
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, e r t e a
GIS app l n e r t o e (gvSIG, OpenJUMP, i N G
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uDIG, ...) e t u r k r a a u M Q SEXTANTE By Victor Olaya Architecture
GRASS SEXTANTE WPS algorithms algorithms algorithms
SEXTANTE GUI
● Dialogs for executing algorithm are created on-the-fly from algorithm requirements, so GIS app the GUI and the processes are completely e t
(gvSIG, OpenJUMP, y n independent. l a uDIG, ...) a t t I x
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This guarantees that all dialogs follow the d d n U a
same criteria and have a similar , S I G I G S
appearance, making it easier for users to v S g S
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s e t u r k r a a u M Q SEXTANTE – GRASS By Victor Olaya Integration: How it works
● Each call to a GRASS command is wrapped as a SEXTANTE algorithm ● Such call can be used in any of the graphical components of SEXTANTE ● Each user-seen algorithm involves calling several GRASS commands: e t y n ● l a Importing data into GRASS into an „on-the-fly“ session a t t I x
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Processing of data n i d d n U ● a
Exporting and opening results in the GIS app (gvSIG etc) , S I G I G S
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v.edit interfacedescription d R
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Edits a vector map, allows adding, deleting and modifying selected vector features.e a l n e
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vector, editing, geometry s e t u
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s e t u r k r a a u M Q SEXTANTE – GRASS Integration: Modeller e t y n l a a t t I x
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s e t u r k r a a u M Q SEXTANTE – GRASS Integration: Modeller e t y n l a a t t I x
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s e t u r k r a a u M Q SEXTANTE – GRASS Integration: Modeller e t y n l a a t t I x
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s e t Note: Partially functional in gvSIG OADE 2010, more to come u r k r a a in (near) future... u M Q GRASS GIS: Geographic Resources Analysis Support System
Free Software GIS (“software libero”):
Developed since 1982, under GPL since 1998
GRASS master Web:
http://grass.osgeo.org e t y n l a a t t I x
, e e Portable: Versions for GNU/Linux, MS-Windows, Mac OSX, S
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Sample data for download (free North Carolina dataset) i A d R
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Mailing lists in various languages 1 a 0 t I 2
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Commercial support available e r t o e i N G
s e t u r k r a a u M Q The early days of open source GIS: pre-Internet times...
1987: William Shatner narrates ... e t y n l a a t t I x
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1978: MOSS l 1 a 0 t I 2
1982: GRASS GIS , e r t e a l n e r
OSGeo t o e i N G
1990 1992 1994 2004 2006 s e t u r k r a a GRASS Interagency Open GRASS Open GIS Open Geospatial u Steering Commitee Foundation (OGF) Consortium (OGC) Consortium (OGC) M Q GRASS GIS: Functionality geospatial data integration ● import and export of data in various formats, coordinate systems transformations and projections, transformations between raster and vector data, 2D/3D spatial interpolation and approximation 2D/3D raster data processing ● 2D and 3D map algebra, surface and volume geometry analysis, topographic parameters and landforms, flow routing and watershed analysis, line of sight, insolation, cost surfaces, shortest path, buff ers, landscape ecology measures, correlation, covariant analysis, expert system (Bayes logic) 2D/3D vector data processing ● multi-attribute vector data management, topological digitizing, overlay, buff ers, vector network analysis, spatial autocorrelation, summary statistics, multivariate e t y
spatial interpolation and approximation, Voronoi polygons, triangulation, SQL n l a a t t I x image processing , e e S
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processing and analysis of multispectral aerial and satellite data, image d d n U a
rectification and orthophoto generation, principal and canonical component
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analysis, smap classification and edge detection, radiometric correction I G S
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visualization i A d R ● 2D display of raster and vector data with zoom and pan, 3D visualization of surfaces e G
n : a and volumes with vector data, 2D and 3D animations, hardcopy postscript maps, 1 i l 1 a 0 t I 2 modeling and simulations
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hydrologic, erosion and pollutant transport, fire spread, temporal data support, time l n e r t
stamp for raster and vector data, raster time series analysis o e i N G
s links to Open Source tools e t u r k r ● QGIS, R-stats, gstat, ZOO-WPS, Paraview, GPS tools, GDAL/OGR, PostgreSQL, a a u MySQL, gvSIG-Sextante, ... M Q GRASS GIS: Interoperability – Import e t y n l a a t t I x
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s e t u r k r a a u M Q GRASS GIS: Interoperability – Export e t y n l a a t t I x
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s e t u r k r a a u M Q Visualization: GRASS data export to Paraview and Povray e t y n l a a t t I x
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Stereo rendering in e e S
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Povray rendering (www.povray.org): adding clouds and haze S g S
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s e t u r k r a a u M Q GRASS: Raster and 3D vector Elevation model combined with extruded 3D buildings; also true 3D vector supported e t y n l a a t t I x
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Trento, Italy e t u r k r a a u Optional: KML export for M Q virtual globes GRASS: geocoding of historical maps e t y n l a a t t I x
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s e t u r k r a a u M Q GRASS: geocoding of historical maps e t y n l a a t t I x
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s e t u r k r a a u M Q GRASS: Project database (Location) wizard e t y n l a a t t I x
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s e t u r k r a a u M Q GRASS: Geospatial modeller e t y n l a a t t I x
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Extra bonus: I 2
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s e t u r k r a a u M Q More GRASS GIS Features
Topological Digitizer e t y n l a a t t I x
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viewer: e a l n e r t o e
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s e t u r k r a a u M Q Viewshed analysis with GRASS New, extremely fast viewshed algorithm (yet in GRASS-Addons): r.viewshed
Comparison on a 5m Lidar based DEM (left map) – calculation time: - common command: e t y n r.los: 4.5h l a a t t I x
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s e t u r 5km k r a a Viewshed from u Dos Trento M Q Lidar data analysis in GRASS GIS Multi-return Lidar data
Available Methods: - cell based statistics - binning - spatial approximation e t y n - smoothing l a a t t I x Use cases: , e e S
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- topographic analysis i d d n U a
- Feature extraction (Separation DEM/DSM) , S I G I G S
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s e t u r k r a a u
H. Mitasova, NCSU M Q M. Brovelli, PdM, Como GRASS GIS e t y n l a a t t I x
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s e t u r k r a a u M Q Tiger mosquito project @ Fondazione E. Mach
Using GFOSS at its best... Scarse meteo-stations or dense MODIS LST maps? Interpolation of meteo data likely complicated due to complex alpine relief: Data density and micro-climatic effects e t y n l a a t t I x
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Stationen 1 i l 1 a 0 t I 2
, Trent Vallarsa Lagorai e r t e a Official temperature map l o n e r t o e from meteo model i N G
s (number of stationens e t u r k r a a variable, data access u limited) M Q Overcoming the clouds problem in satellite based land surface temperature data
A CH Approach: °C Relationship temperature - elevation: gradient method
Elevation model → LST e t y n l a a t t I x
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MODIS LST/Terra, 24 June 2003, 10:30 solar time a 0 t I 2
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Missing pixels due to e r t o e i N
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s e t u r k r a a u M Q Results of MODIS LST reconstruction
Original MODIS LST map, Second and third filter step QA map used as filter applied to MODIS map CH A e t y n l a a t t I x
By NASA algorithm ,
MODIS LST (Aqua satellite) e e S
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1. June 2003, 13:30 solar time i d d (clouds) n U a
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s e t u r k r a a u M Q Neteler, M. 2010: Remote Sensing, 2(1), 333-351 Results of MODIS LST reconstruction
Second and third filter step applied to MODIS map Reconstructed MODIS LST map CH A CH A e t y n l a a t t I x
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MODIS LST (Aqua satellite) e e S
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s e t u r k r a a u M Q Neteler, M. 2010: Remote Sensing, 2(1), 333-351 Parallelised GIS Processing
Infrastructure: FEM-GIS Cluster ● 12 single-blades and 2 double-blades ● In total 300 nodes with 600 Gb RAM ● Circa 2 Tflops/s ● Linux operating system, blades headless e t y n l a ● a t GRASS GIS and t I x
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Queue system for job , S I G I G S management v S g S
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Processing of all 11,000 a 0 t I 2
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maps in parallel: one r t e a l n e
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Computational time: s e t u r 3 weeks with k r a a u
LST-algorithm V1.1 M Q LST Applications: Tiger mosquito survival
Aedes albopictus survival maps from reconstructed Daily MODIS Land Surface Temperature maps Terra-MODIS LST (2000-today) Aqua-MODIS LST (2002-today) January temperature thresholds (2001-2009) s i s y l a n e GIS based a t
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Daily LST maps a
MODIS LST a t
Annual temperature t a I x
reconstruction , 01:30 thresholds (2001..2009) e m e S
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s e t Neteler, Roiz, Castellani, Rizzoli, u r k r a a in review. u M Q LST Applications: Tiger mosquito survival today... e t y n l a a t t I x
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s e t u r k r a a u Roiz D., Neteler M., Castellani C., Arnoldi D., Rizzoli A., 2011: Climatic Factors Driving Invasion of the Tiger M Q Mosquito (Aedes albopictus) into New Areas of Trentino, Northern Italy. PLoS ONE. 6(4): e14800 LST Applications: Tiger mosquito survival in 2050 (A2 scenario) e t y n l a a t t I x
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s e t u r k r a a u Roiz D., Neteler M., Castellani C., Arnoldi D., Rizzoli A., 2011: Climatic Factors Driving Invasion of the Tiger M Q Mosquito (Aedes albopictus) into New Areas of Trentino, Northern Italy. PLoS ONE. 6(4): e14800 Conclusions
● Sextante and GRASS provide complementary functionality
● The integration is becoming smooth
● gvSIG user can now easily use GRASS' capabilities without changing their environment
● Powerful toolsets for empowered people! e t y n l a a t t I x
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Special thanks to... d n U a
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Victor Olaya (Sextante and core GRASS interface) v S g S
● i Benjamin Ducke (Sextante-GRASS integration) A d R
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n Regione Autonoma Friuli Venezia Giulia (support for my presentation) : a 1 i l 1 a 0 t I 2
Markus Neteler
, e r Fondazione E. Mach (FEM) t e a l n e r
Centro Ricerca e Innovazione t o e i
GIS and Remote Sensing Unit N G
s Via E. Mach, 1 e t u r k r 38010 S. Michele all'Adige, Italy a a u http://gis.cri.fmach.it M Q http://www.osgeo.org