GEOSTAT 2010 Introduction System for Automated Geoscientific Analyses SAGA. System for Automated Geoscientific Analyses

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1 SAGA System for Automated Geoscientific Analyses Dr. Olaf Conrad Physical Geography, University Hamburg

2 SAGA Concepts and Basics

3 What is SAGA? SAGA is the abbreviation for System for Automated Geoscientific Analyses SAGA is a Geographic Information System (GIS) software SAGA has been designed for an easy and effective implementation of spatial algorithms SAGA offers a comprehensive, growing set of geoscientific methods SAGA provides an easily approachable user interface with many visualisation options SAGA runs under Windows and Linux operating systems SAGA is a Free Open Source Software (FOSS) MS Windows Linux

4 GIS Basics GIS is the abbreviation for Geographic Information Systems The purpose of GIS is the collection, management, analysis and presentation of spatial data or geodata Collection Data Management Analysis Presentation Geodata are data, which have a spatial relation to the Earth s surface Geodata consist of both, attribute data and geometric data. Geometric data define position and shape. Information is more than just data An information system is more than just a methodology Information systems combine data with a methodological framework Geographic information systems deal with geodata and provide methods specific to geodata

5 GIS Workflow Presentation Analysis Visualisation Generating maps Analysis and Modelling Creation of new geoinformation Management Data storage Structuring Collection Measuring (in situ) Digitalisation Geodata Original (Earth) The reality

6 GIS Geodata Structures Vector Data Raster Data Y p4 p1,1 p2,1 p3,1 p1 p2 (x, y) p3 p1,2 p2,2 p3,2 p1,3 p2,3 p3,3 X Vector data represent geometric properties with vertices, which are given by point coordinates. Lines and polygons are defined by sequences of vertices. In SAGA vector data are referred to as shapes. Each shape has an associated list of attributes. Raster data store usually only one single attribute. They do this for number of point coordinates, which are ordered in a regular raster. Therefore it is not necessary to store each vertex coordinates explicitely. In SAGA raster data are usually referred to as grids.

7 SAGA The Beginning of (the) SAGA The idea for the development of SAGA evolved in the late 1990s during the work on several research projects at the Dept. for Physical Geography, Göttingen. A research focus was the analysis of raster data, particularly of Digital Elevation Models (DEM), which have been used e.g. to predict soil properties, terrain controlled process dynamics as well as climate parameters. This required the development and implementation of many new methods for spatial analysis and modelling. Unluckily everybody involved seemed to prefer a different operating system, software, and programming language. Therefore a common development platform with integrated support for geodata analysis has been created, which then became known as SAGA. In 2004 SAGA has been published as Free Open Source Software. Since then SAGA got a growing world wide user community, which also led to many contributions from outside the original developer team. DiGeM (2001), one of SAGA s predecessors SAGA 1.2 (2005)

8 SAGA Development SAGA s development is mainly driven by the research interests of its inventors Physical Geography Göttingen (now Hamburg), SciLands GmbH Göttingen With SAGA s publication as Free Open Source Software several external inputs enriched the spectrum of developments V. Olaya: SEXTANTE (Sistema Extremeno de Analisis Territorial), SAGA Manual, module & system development T. Schorr: GEOSTEP project, Linux, Unicode and 64bit compatibility, SAGA-Python interface V. Wichmann: PhD Thesis (rockfall modelling), Laserdata GmbH, support & documentation, module & system development V. Cimmery: SAGA 2 User Guide, documentation A. Brenning: RSAGA plugin, accessing SAGA modules from R environment and many other contributions, mainly modules and documentation

9 SAGA Milestones 2001: Begin of the SAGA development (based on DiGeM) : SAGA gets established as common tool of the team 2004, Feb.: SAGA 1.0 published as Open Source Software 2004, Jul.: SAGA 2 development begins (wxwidgets) 2004, Aug.: SAGA Manual of V.Olaya 2005, Jan.: Foundation of the SAGA User Group Association 2005, Feb.: CeBIT Presentation of SAGA 1.2 and 2.0-Beta 2005, Mar.: SAGA 2 runs under Linux 2005, Nov.: First SAGA User Conference in Göttingen 2006, Jun.: SAGA 2.0 Release Candidate , Jul.: First Internat. SAGA User Conference, AGIT/Salzburg 2007, Jun.: SAGA is released 2008, May: A.Brenning publishes RSAGA

10 SAGA User Group Association The SAGA User Group Association has been established in May The primary aim of this non-profit organisation is to guarantee a sustainable long-term development of SAGA. Funding members Dept. Physical Geography and Landscape Ecology, Univ. Hannover ZGIS - Center for Geomatics, Univ. Salzburg Dept. of Geography, Univ. Bonn Physical Geography, Kath. Univ. Eichstätt- Ingolstadt Dept. Remote Sensing and GIS, Univ. Cologne SciLands GmbH, Göttingen Laserdata GmbH, Innsbruck RLP AgroScience GmbH, Neustadt

11 SAGA System Architecture SAGA's system architecture is modular. Its foundation is the Application Programming Interface (API), which provides data object models, basic definitions for the programming of scientific modules and numerous helpful classes and functions. Module libraries are containers for the scientific methods in form of so called modules. API as well as module libraries are not independently running executables but Dynamic Link Libraries (DLL) and have to be accessed through a front end program. A Graphical User Interface (GUI) is one of the two generic SAGA front ends. It allows the user to control the system, is responsible for module and data management as well as for data visualisations. Graphical User Interface (GUI) user interaction, visualisation Module Management loading, execution Module Libraries the implementation of scientific methods Library A Data Management tables, vector, raster data Library B Library C Library D Library E Application Programming Interface (API) data objects, modules, tools and helpers

12 SAGA Key Features Programming language C/C++ object oriented system design rapid application development many free source codes available Application programming interface provides special geodata objects comprehensive set of useful functions supports development of new methods Modular structure methods are collected in module libraries module libraries are dynamical link libraries independence of methods and framework User interfaces graphical user interface command line interpreter interfaces for scripting (Python, Java, R)

13 SAGA License Issues SAGA is a Free Open Source Software (FOSS) Free of charge Transparency, particularly in a scientific meaning World wide community of developers GNU General Public License (GPL) Applies to the GUI and most of the free Modules Programs, which use GPL source codes, have to be published as Open Source Software too GNU Lesser General Public License (LGPL) Applies to the API Programs, which use LGPL source codes, have not to be published as Open Source Software SAGA modules can be proprietary

14 GUI The Graphical User Interface The Graphical User Interface (GUI) allows users to manage and visualise data as well as to perform data analyses and manipulations by executing modules. menu bar tool bar Besides menu, tool and status bars, which are typical for the majority of modern programs, and data views, which are centrally displayed, SAGA interfaces the user with two special controls, a workspace control and an object properties control. The workspace control has sub windows for modules, data and maps. Each sub window shows a tree view, through which associated workspace objects can be accessed and selected. workspace Ansicht Ansicht data view messages, notifications status bar object properties Loaded module libraries for instance are listed in the modules workspace together with a list of their modules. Similarly loaded data sets appear in the data workspace, hierarchically sorted by their data type, and map views are listed in the maps workspace with data sets included in each map.

15 GUI Workspace & Object Properties Dependent on the object which is selected in the active workspace the properties control shows an object specific set of sub windows. Common to all objects are sub windows for settings and descriptions others appear only for specific objects. In case a module is selected, the settings control is populated with module parameters displaying options relevant for the module execution. The description window gives information about the module and its parameters, as supplied by the module programmer. In case a data object is selected the settings control allows the user to change data set name, memory handling and display behaviour. Data object description is complemented by a history, which enables users to reconstruct how the data set was created. Other controls allow the editing of attributes or display a legend. Workspace Modules Data Maps Object Properties Settings Description Settings Attributes Settings Legend

16 GUI Data Views Maps Print Layout 3D View The standard way to visualise spatial data is the cartographic map. Each spatial data set can be added to a map as thematic layer. Display orders of thematic layers are changed in the maps workspace. In dependence of the data type various display options are available for the creation of expressive maps. Attribute values of vector data can be used as labels, to determine sizes of point symbols or line widths, or to indicate display colours. Raster data are coloured according to their data values, either by using a lookup table or a metric classification scheme. A transparency value allows to use raster data for shading effects. 3d views can easily be created for each map, as far as appropriate elevation data have been loaded. Vector as well as raster data can be edited directly in map views. Further possibilities for data visualisations include histograms and scatter plots. Scatter plots have a built in regression function and can be applied to vector, raster and table data. Besides simple table views with editing and sorting capabilities, also diagrams are available to display table data. Histograms, Scatter Plots Tables, Diagrams Digitising, Editing

17 Modules Overview SAGA comes with a comprehensive and growing set of free modules, most of them published under the GPL 34 libraries with 119 modules in version libraries with 234 modules in version libraries with 300 modules in version libraries with 330 modules in GEOSTAT 2009 version Not all modules are highly sophisticated analysis or modelling tools. Many modules perform rather simple data operations. But several other modules represent the state of the art in their field of analysis. Data Import & Export Cartographic Projections & Georeferencing Many Raster & Vector Data Tools Image Processing Terrain Analysis Geostatistics and many more Data Import & Export Projections Raster Tools Vector Tools Geostatistics Image Processing Terrain Analysis

18 Modules Managing & Executing When SAGA runs the first time it automatically searches and loads all module libraries located in the SAGA folder Notification about loaded module libraries You can load and unload modules via menu A module can be called for execution via the modules menu or from workspace When a module is called it first confronts you with a dialog, in which you have to choose input data sets as well as output data targets and which usually offers several additional options. A module notifies you when it has finished its calculation Loading module libraries Calling a module via menu Executing a module Unloading a module library Calling a module from workspace Module notification

19 Modules Programming CHillshade::CHillshade(void) { Parameters.Add_Grid( NULL, "ELEVATION", "Elevation", PARAMETER_INPUT);... } Parameters.Add_Grid( NULL, "SHADE", "Shade", PARAMETER_OUTPUT); bool CHillshade::On_Execute(void) { CSG_Grid *pdem = Parameters( ELEVATION )->asgrid(); CSG_Grid *pshade = Parameters( SHADE ) ->asgrid();... for(y=0; y<get_ny(); y++) { for(x=0; x<get_nx(); x++) { if( pdem->get_gradient(x, y, s, a) == false ) { pshade->set_nodata(x, y); } else { d = acos(sin(s) * sin(dec) + cos(s) * cos(dec) * cos(a - Azi)); } } } } pshade->set_value(x, y, d);

20 Modules Scripting With the SAGA command line interpreter SAGA CMD you can execute module calculations from a command line or shell. This is not very user friendly, but allows to write batch/shell scripts for further automation of process flows. Tip: A batch script template for executing a module can easily be created via the context menu of a module in the SAGA GUI.

21 Modules Scripting Via the SWIG compiler (Simplified Wrapper and Interface Generator) it is possible to expose the SAGA API as well as SAGA modules to various (script) programming languages, e.g. Python, Java, C#, R. Currently only a Python interface is ready to use. One possibility: running SAGA modules from (web)server processes. A Java interface is in preparation (V.Wichmann), an R interface might follow soon, giving almost full control over SAGA functionality from R environment. Accessing the SAGA API from Python script

22 Installation Download 'saga_2.0.0_bin_mswvc.zip': Windows binaries compiled with MS Visual C This Windows version is a portable software. Just unzip it and start without any further installation process. 'saga_2.0.0_bin_linux.tar.gz': Linux binaries with the wxgtk libraries statically linked. Except that you have at least the GTK 2 and the png (as reported) libraries to be installed, this version is almost portable too (see the 'install.txt' on how to run the executables). 'saga_2.0.0_src.zip': complete SAGA 2.0 source codes, including project and make files for gcc, MinGW, MSVC6/8. 'saga_2.0.0_src_linux.tar.gz': source code distribution for Linux, created with automake. For compilation call './configure', 'make' and as super user 'make install'. 'saga_2.0.0_python_mswvc.zip': scripting interface to the SAGA-API for Python (Win32), including example scripts.

23 Installation Setup Installation under Windows SAGA is a so called portable Software, which means you do not need any further installation routines. You can even run it from memory stick! Just unzip the downloaded file Run saga_gui.exe For the lazy ones: SAGA (MSW) will also come with an installer Installation under Linux Unzip the binaries and run the shell script saga_gui.sh This works with many but not with all Linux installations. See SAGA WiKi for more information on how to make it work. For SuSE 10.2/11.0 a binary package is available

24 Further Information Explore the world of SAGA GIS Basic information Comprehensive list of references SourceForge > host for OSS projects Download software, documents, data SAGA Wiki Bug, Feature Tracker User Forum User Guide and Manual sourceforge.net/projects/saga-gis User Forum WiKi Vern Cimmery s User Guide

25 Current Research Selected Examples

26 Erosion Risk Estimation (R)USLE LS factor estimation for agricultural management units of the federal state Lower Saxony. Used to estimate risk of soil erosion by water Comparison of different LS calculations

27 GEOSTEP Precision Farming Geoinformationstechnologie für standorteffiziente Pflanzenproduktion = geoinformation technology for efficient site specific plant production Study Area Development of a decision support system for site specific management ( precision farming, precision agriculture ) Integration of climate regionalisation, weather predictions, modelling of soil status, growth and cultivation models, GPS based acquisition of factory data, cost-benefit analysis of management and cultivation practises Funded by the Bavarian Research Foundation Pilot , 6 project partners

28 GEOSTEP GIS-Funktions, Analysis, Models Landwirtschaftliche Agricultural Consultance Beratung SAGA Static Data Collecting data (Digitising) Spatialisation of soil properties... Dynamic Data Weather prediction (WRF) Models of soil status Growth- a. cultivation models Cost-benefit analysis... Server Server Data Base Web-Interface Ubiquitary data access Output of thematic maps... OGC-Interface Machine controlling Calibration...

29 Cellular Automata Water Quality Cellular Automata (CA) models consist of a regular grid of cells and simulate system dynamics by applying simple rules for each cell to determine the status of a cell in the next time step. Originally CA work only with discrete values (= cell states), but in various recent researches the CA concept has been widened to model continuous quantities (e.g. surface water flow, landscape evolution). Left pictures show the steps used for pollutant concentration computation of a lake with in and outflow. Right pictures shows differences in diffusion gradients between two scenarios. Heinrich, R. & Conrad, O. (2008): Diffusion, Flow and Concentration Gradient Simulation with SAGA GIS using Cellular Automata Methods.

30 Forest Fragmentation Borneo Forest fragmentation and degradation as risk for forest reduction. Peat swamp forest, Sabah/Borneo Regenerated good peat swamp forest (canopy height: 30m) Phua, M.P., Conrad, O., Kamlun, K.U., Fischer, M., Böhner, J. (2008): Multitemporal Fragmentation Analysis of Peat Swamp Forest in the Klias Peninsula, Sabah, Malaysia Using GIS and Remote Sensing Techniques 2003

31 Forest Reduction Madagascar SRTM DEM Landsat/Spot Land Cover Classification Maren Horn (2009): Semi-automated Estimation of Potential Natural Vegetation, Diploma Thesis, Univ. Hamburg

32 Heavy Metal Pollution Oker River DEM Creation Pre-Processing Jan Hohlbein (in progress): The Use of LIDAR DEM for Estimation of Heavy Metal Distribution caused by River Transport, Diploma Thesis, Univ. Hamburg Flood Depths

33 Outlook There is many more research going on with SAGA, what clearly influences the direction of the SAGA development. Apart from methodological point of view there are many requests to enlarge SAGA s architecture for more standard GIS functionality Database and web server interfaces (e.g. PostGIS, WFS, WCS) Map layout Vector topology and multidimensional grids My current interest: simulation of process dynamics Runoff Soil Moisture Landscape Evolution