Show filters Hide filters

Refine your search

Publication Year
Author & Contributors
1-36 out of 65 results
Change view
  • Sort by:
22:43 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

Using Spatial Business Intelligence For Asset Management

The maintenance of waterways is expensive. Optimization of reconstruction projects can save money and limit hindrance for the public. In this presentation I show how the implementation of Spatial OLAP can give better insight in the quality of the construction of waterway banks. By spatially overlaying inspection results with construction records, a better estimation can be made about the overall quality, potential danger and repair costs. Spatial OLAP is an excellent way to provide insight into the different variables involved in the planning proces of maintenance.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
24:39 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

TileServer: Hosting Map Tiles And MBTiles

OpenGIS Web Map Tiling Service (WMTS) is becoming the standard used for distributing raster maps to the web and mobile applications, cell-phones, tablets as well as desktop software. Practically all popular desktop GIS products now support this standard as well, including ESRI ArcGIS for Desktop, open-source Quantum GIS (qgis) and uDig, etc. The TileServer, a new open-source software project, is going to be demonstrated. It is able to serve maps from an ordinary web-hosting and provide an efficient OGC WMTS compliant map tile service for maps pre-rendered with MapTiler, MapTiler Cluster, GDAL2Tiles, TileMill or available in MBTiles format. The presentation will demonstrate compatibility with ArcGIS client and other desktop GIS software, with popular web APIs (such as Google Maps, MapBox, OpenLayers, Leaflet) and with mobile SDKs. We will show a complete workflow from a GeoTIFF file (Ordnance Survey OpenData) with custom spatial reference coordinate system (OSGB / EPSG:27700) to the online service (OGC WMTS) provided from an ordinary web-hosting. The software has been originally developed by Klokan Technologies GmbH (Switzerland) in cooperation with NOAA (The National Oceanic and Atmospheric Administration, USA) and it has been successfully used to expose detailed aerial photos during disaster relief actions, for example on the crisis response for Hurricane Sandy and Hurricane Isaac in 2012. The software was able to handle large demand from an ordinary in-house web server without any issues. The geodata were displayed in a web application for general public and provided to GIS clients for professional use - thanks to compatibility with ArcIMS. It can be easily used for serving base maps, aerial photos or any other raster geodata. It very easy to apply - just copy the project files to a PHP-enabled directory along with your map data containing metadata.json file. The online service can be easily protected with password or burned-in watermarks made during the geodata rendering. Tiles are served directly by Apache web server with mod rewrite rules as static files and therefore are very fast and with correct HTTP caching headers. The web interface and XML metadata are delivered via PHP, because it allows deployment on large number of existing web servers including variety of free web hosting providers. There is no need to install any additional software on the webserver. The mapping data can be easily served in the standardized form from in-house web servers, or from practically any standard web-hosting provider (the cheap unlimited tariffs are applicable too), and from a private cloud. The same principle can be applied on an external content distribution network (Amazon S3 / CloudFront) to serve the geodata with higher speed and reliability by automatically caching it geographically closer to your online visitors, while still paying only a few cents per transferred gigabyte.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
19:46 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

Using OSGeo Live In MSc Teaching

Big Data in the Earth sciences, the Tera- to Exabyte archives, mostly are made up from coverage data whereby the term "coverage", according to ISO and OGC, is defined as the digital representation of some space-time varying phenomenon. Common examples include 1-D sensor timeseries, 2-D remote sensing imagery, 3D x/y/t image timeseries and x/y/z geology data, and 4-D x/y/z/t atmosphere and ocean data. Analytics on such data requires on-demand processing of sometimes significant complexity, such as getting the Fourier transform of satellite images. As network bandwidth limits prohibit transfer of such Big Data it is indispensable to devise protocols allowing clients to task flexible and fast processing on the server. The EarthServer initiative, funded by EU FP7 eInfrastructures, unites 11 partners from computer and earth sciences to establish Big Earth Data Analytics. One key ingredient is flexibility for users to ask what they want, not impeded and complicated by system internals. The EarthServer answer to this is to use high-level query languages; these have proven tremendously successful on tabular and XML data, and we extend them with a central geo data structure, multi-dimensional arrays. A second key ingredient is scalability. Without any doubt, scalability ultimately can only be achieved through parallelization. In the past, parallelizing code has been done at compile time and usually with manual intervention. The EarthServer approach is to perform a semantic-based dynamic distribution of queries fragments based on networks optimization and further criteria. The EarthServer platform is comprised by rasdaman, an Array DBMS enabling efficient storage and retrieval of any-size, any-type multi-dimensional raster data. In the project, rasdaman is being extended with several functionality and scalability features, including: support for irregular grids and general meshes; in-situ retrieval (evaluation of database queries on existing archive structures, avoiding data import and, hence, duplication); the aforementioned distributed query processing. Additionally, Web clients for multi-dimensional data visualization are being established. Client/server interfaces are strictly based on OGC and W3C standards, in particular the Web Coverage Processing Service (WCPS) which defines a high-level raster query language. We present the EarthServer project with its vision and approaches, relate it to the current state of standardization, and demonstrate it by way of large-scale data centers and their services using rasdaman.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
23:58 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

Cartaro - The Geospatial CMS

Cartaro is a new web mapping platform that makes the power of some of the best open source geospatial components available in a content management system (CMS). Cartaro allows to set-up and run small websites or complex web applications with maps and geodata. It is also suitable for geoportals and spatial data infrastructures whenever there is the need to get everything up and running without much individual programming. The geospatial software stack used in Cartaro consists of PostGIS, GeoServer, GeoWebCache and OpenLayers. The whole stack is managed from within the CMS Drupal. The geospatial components bring professional aspects of geodata management into the CMS. This is namely the ability to persist data as true geometries, thus allowing for complex and fast queries and analyses. It does also mean supporting a whole range of data formats and the most relevant OGC standards. For the latter Cartaro can extend the handling of user roles and permissions, which already exists in Drupal, to define fully granular read and write permissions for the web services, too. In the presentation we will first explain our basic motivation behind Cartaro: that is bringing geospatial functionality to the huge community of CMS developers and users. This community, which is of course much larger than the classical FOSS4G community, has a great potential to make more and better use of geodata than it was possible with most existing tools. We will then demonstrate how far the integration with the CMS reaches and present the Drupal user interface that allows to configure most features of Cartaro. We will show how to create, edit and map geospatial content with Cartaro and we will demonstrate the publication of this content as an OGC web service. We will also go into some details concerning the architecture of Cartaro and explain how we tackled specific problems. A glimpse of the some use cases will demonstrate the real potential of Cartaro. It will also show how the focus and functionality of a Cartaro based application can be extended with the installation of any of the Drupal modules that exist for almost every task one could imagine. The presentation will close with the future perspectives for Cartaro. From a technical point of view this includes the roadmap for the next months. But it also includes a discussion of our ideas about Cartaro's role as self-supporting bridge between the geo and not-so-geo world of open source software.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
23:01 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

LIDAR In PostgreSQL With Pointcloud

How do you store massive point cloud data sets in a database for easy access, filtering and analysis? The new PointCloud extension for PostgreSQL allows LIDAR data to be loaded, filtered by spatial and attribute values, and analyzed via integration with PostGIS. We'll discuss the extension implementation, basics of loading data with PDAL, and how to use PointCloud with PostGIS to do on­the­fly LIDAR analysis inside the database.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
16:26 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

Gestural Interaction With Spatiotemporal Linked Open Data

Exploring complex spatiotemporal data can be very challenging for non-experts. Recently, gestural interaction has emerged as a promising option, which has been successfully applied to various domains, including simple map control. In this paper, we investigate whether gestures can be used to enable non-experts to explore and understand complex spatiotemporal phenomena. In this case study we made use of large amounts of Linked Open Data about the deforestation of the Brazilian Amazon Rainforest and related ecological, economical and social factors. The results of our study indicate that people of all ages can easily learn gestures and successfully use them to explore the visualized and aggregated spatiotemporal data about the Brazilian Amazon Rainforest.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
49:15 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

FOSS4G13 Keynote QGIS 2.0

  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
25:30 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

GraphGIS, Bringing Spatial Functionalities To NoSQL Graph Databases

Driven by the major players in of the Web like Google, Facebook, Twitter, NoSQL databases quickly gained real legitimacy in handling important data volumetry. With a first concept of key-value, NoSQL databases have quickly evolve to meet a recurring relationships between entities or documents. Graph / document paradigm provides flexibility that facilitates the representation of the real world. Beyond the representation of information of social networks, this data model fits very well to the problem of Geo Information, its variety of data models and the interconnections between them. The emergence of cloud computing and the needs driven by the Semantic Web have led publishers of geospatial solutions to consider other ways than those currently used to store and process GIS information. It is in this perspective that Geomatys has developed GraphGIS, a spatial cartridge for OrientDB, the Graph oriented NoSQL database. This solution provides support of geographic Vector, Raster and Sensor data, in multiple dimensions and their associated metadata.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
28:47 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

GIS Is Not Dead, It's Coming For You And It's Been Drinking JavaScript

This talk will discuss several super kick-ass ways that JavaScript and the web have re-shaped GIS and are changing how we visualize, analyze and share geospatial data with each other and the world. GIS is dead? No, it’s not, and it’s coming to find you and spatially kick your ass with a big bag of JavaScript. The world changes fast (hello, Internet). Yet, our industry (map making in one form or another) is stuck, and has generally shown itself to be slow to react to new ideas and paradigms that grow rapidly in other spaces. But there is still hope! GIS is coming back, and it’s being re-tooled with lots of shiny new software and geo-weapons. It’s going to make an assault on all of our previous notions of its old self. Of course this new and shiny GIS resembles its former self in many ways, it's also full many new ideas about how we experience maps and data on the web. As we witness a massive resurgence in JavaScript (hello D3 & node.js), and more emphasis placed on the web in general, we see that there are actually still large holes that should be filled the geo-spatial stack. New waves of JavaScript developers have, and will continue to fill these gaps. This talk will discuss several super kick-ass ways that JavaScript and the web have re-shaped GIS and are changing how we visualize, analyze and share geospatial data with each other and the world.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
24:37 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

Machine Learning For Remote Sensing : Orfeo ToolBox Meets OpenCV

Orfeo ToolBox is an open-source library developed by CNES in the frame of the Orfeo program since 2006, which aimed at preparing institutional and scientific users to the use of the Very High Resolution optical imagery delivered by the Pleiades satellites. It is written in C++ on top of ITK, a medical imagery toolkit, and relies on many other open-source libraries such as GDAL or OSSIM. The OTB aims at providing generic means of pre-processing and information extraction from optical satellites imagery. In this talk, we will focus on recent advances in the machine learning functionality allowing to use the full extent of OpenCV algorithms. Historically, supervised classification of satellite images with OTB mainly relies on libSVM. The Orfeo ToolBox provides tools to train the SVM algorithm from images and raster or vector training areas, to use a trained SVM algorithm to classify satellite images of arbitrary size in a multithreaded way, and to estimate the accuracy of the classification. The SVM algorithm has also been used for other applications such as change detection or object detection. But even if it is one of the most used function of the OTB, the supervised classification function did not offer a single alternative to the SVM algorithm. However, the open-source world offers plenty of implementations of state-of-the-art machine learning algorithms. For instance OpenCV, a computer vision C++ library distributed under the BSD licence, includes a statistical machine learning module that contains no less than height different algorithms (including SVM). We therefore created an API to represent a generic machine learning algorithm. This API can then be specialized to encapsulate a given algorithm implementation. The machine learning algorithm API assumes very few properties for such algorithms. A method has to be specialized to train the algorithm from a samples vector and a set of target labels or values, and another to predict labels or values from a samples vector. Thanks to templating, these methods handle both classification and regression. Two other methods are in charge of saving and loading back the parameters from training. File format for saving is left to the underlying implementation, and the load method is expected to return a success flag. This success flag is used in a factory pattern, designed to be able to seamlessly instantiate the appropriate machine learning algorithm specialization upon file reading. It is therefore not necessary to know which algorithms the trained parameters files refer to. This new set of classes has been embedded into a new OTB application. Its purpose is to train one of the machine learning algorithm from a set of images and GIS file describing training areas, and output the trained parameters file. Another application is in charge of reading back this file and applying the classification algorithm to a given image. With these two tools, it is very easy to train different algorithms against the same dataset, evaluate them with the help of another application which can compute confusion matrix and classification performances measurement so as to choose one or several best algorithm along with their parameters. The resulting classification maps could then be combined into a more robust one using yet another OTB application, using classes majority voting or Dempster-Shafer combination. Our perspectives for using and improving this new API are manyfold. First, we would like to investigate further the use of the regression mode. We also would like to investigate the performances of the new machine learning algorithms for other tasks achievable with OTB, such as object detection for instance. Last, we would like to evolve the API so as to export any confidence or quality indices an algorithm can output regarding its predictions. This would open the way to the implementation of new active learning tools.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
23:35 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

MapServer Project Status Report - Meet The Developers!

This session starts with a status report of the MapServer project, followed by an open question/answer session to provide a opportunity for users to interact with members of the MapServer project team. We will go over the main features and enhancements introduced in MapServer 6.2 and 6.4, including the addition of the new TinyOWS and MapCache components, the current and future direction of the project, and finally discuss contribution opportunities for interested developers and users. Don’t miss this chance to meet and chat face-to-face with the members of the MapServer project team!
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
26:44 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

Mapbender3 - Create Your Own Geoportal Web Application And Service Repository

Mapbender3 is a client framework for spatial data infrastructures. It provides web based interfaces for displaying, navigating and interacting with OGC compliant services. Mapbender3 has a modern and user-friendly administration web interface to do all the work without writing a single line of code. Mapbender3 helps you to set up a repository for your OWS Services and to create indivdual application for different user needs. The software is is based on the PHP framework Symfony2 and integrates OpenLayers, MapQuery and JQuery. The Mapbender3 framework provides authentication and authorization services, OWS Proxy functionality, management interfaces for user, group and service administration. In the presentation we will have a look at some Mapbender3 solutions and find out how powerful Mapbender3 is! You will see how easy it is to publish your own application.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
28:04 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

A New Dimension To PostGIS : 3D

Talking about 3D used to sound cool. Used to. But for real GIS use, we really need more than just playing with a globe. 3D in GIS becomes cool as soon as we have the ability to deal with full 3D spatial analysis. Just as we already have in 2D, we need functions like intersection, buffer, triangulation and more ... The GEOS library provides us 2D topological processing for years. The CGAL library could now also provide us some interesting additional 3D topological functions. As CGAL is not fully designed for GIS data models, we provide a library inbetween called SFCGAL, in charge of providing a Simple Feature API on top of CGAL. PostGIS 2.1 now allows to link PostGIS and (SF)CGAL, and already provides several exciting 3D functions (and more and more to come). This thrilling talk about PostGIS 3D will therefore focus on : - What kind of project / application needs 3D GIS analysis ? - What can we do right now with PostGIS 2.1 and (SF)CGAL ? - What we will be able to do soon with PostGIS 3D ? - Some tools used to view and manipulate 3D data (QGIS / WebGL based)
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
24:23 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

A New Zealand Case Study: Open Source, Open Standards, Open Data

  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
26:42 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

A Cellular Automata Land-Use Model For The R Software Environment

A cellular automata model of land-use change developed in the free and open source software environment R is presented. The advantages offered by R as a development environment for a CA land-use model are evaluated, and the pros and cons of the approach employed are discussed in depth with reference to commercial alternatives.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
27:23 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

An Open Source Analysis Toolbox For Street Network Comparison

This paper presents a novel open source toolbox for street network comparison based on the Sextante geoprocessing framework for the open source Geographic Information System Quantum GIS (QGIS). In the spirit of open science, the tool- box enables researchers worldwide to assess the quality of street networks such as OpenStreetMap (OSM) by calculating key performance indicators commonly used in street network comparison studies. Additionally, we suggest two new perfor- mance indicators for turn restriction and one-way street comparisons specifically aimed at testing street network quality for routing. We demonstrate the use of this toolbox by comparing OSM and the official Austrian reference graph “Graph Integration Platform” (GIP) in the greater Vienna region.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
24:32 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

Getting The Best Performance For GeoJSON Map Visualizations: PostGIS Vs CouchDB Backend

In order to deliver rich user experience to user, features (attribute data and geometries) have to be sent to the client for mouse-over visual effects, synchronization between charts, tables and maps, and on-the-fly classifications. GeoJSON is one of the most popular encodings for the transfer of features for client-side map visualization. The performance of client visualizations depends on a number of factors: message size, client memory allocation, bandwidth, and the speed of the database back-end amongst the main ones. Large GeoJSON-encoded datasets can substantially slow down loading and stylization times, and also crash the browser when too many geometries are requested. A combination of techniques can be used to reduce the size of the data (polygon generalization, compression, etc). The choice of an open-source DBMS for geo-spatial applications used to be easy: PostGIS is powerful, well-supported, robust and fast RDBMS ? On the other hand, unstructured data, such as (Geo)JSON, may be better served by document-oriented DBMS such as Apache CouchDB. The performance of PostGIS and CouchDB in producing GeoJSON polygons with different combination of factors that are known to affect performance was tested: compression of GeoJSON (zip) to reduce transmission times, different levels of geometry generalization (reducing the number of vertices in transferred geometries), precision reduction (the reduction of numbers of decimal digits encoding coordinates), and the use of a topological JSON encoding of geometries (TopoJSON) to avoid redundancy of edges transferred. We present the results of a benchmark exercise testing the performance of an OpenLayers interface backed by a persistence layer implemented using PostGIS and CouchD. Test data were collected using an automated test application based on Selenium, which allowed to gather repeated observations for every combination of factors and build statistical models of performance. These statistical models help to pick the best combination of techniques and DBMS, and to gauge the relative contribution of every technique to the overall performance.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
36:34 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

GDAL/OGR Project Status

An overview of the capabilities of the GDAL/OGR (Geospatial Data Abstraction Library) project will be covered, followed by a focus on new developments in the last two years and future directions for the project.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
25:25 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

ESA User Services Powered By Open Source

  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
25:39 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

OpenLayers 3: Under The Hood

OpenLayers 3 is the next generation of web mapping. A radical new architecture and the use of cutting edge JavaScript techniques, libraries, and tools enables a full suite of previously unimaginable functionality while maintaining a compact, high performance library. In this talk we'll show you how to use this functionality in your applications, and peek under the hood to see how OpenLayers 3's architecture makes it possible. We'll include: Virtual globe (Cesium) integration: a carefully designed camera and data source abstractions permit close integration with the virtual globes. Switch between 2D and 3D views of the same data, or display synchronized 2D and 3D views side by side. Multiple rendering back-ends: a pluggable rendering architecture supports multiple renderers for maximum performance and portability. A Canvas 2D renderer provides fast, reliable rendering on current devices, a DOM renderer provides fall-back capabilities for older browsers, and a WebGL renderer opens the door to the next generation of performance for the most demanding applications. Rich data sources: generic and powerful core data representations of tiled, single image, and vector data make it easy to add support for a wide range of geospatial data sources. Smooth and flexible interaction and animation: an optimized rendering path ensures that interaction remains smooth at all times. Compact library size: use of the Closure suite of tools creates keeps the build size small while keeping the source code readable.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
22:46 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

PyModis: The Python Library For MODIS Data

pyModis library is a Python library to work with MODIS sensor satellite data. It was originally developed as an interface to download MODIS data from the NASA FTP server but it has grown into a powerful library which also offers further operations on the data. pyModis has several features: - it supports downloading of large numbers of original MODIS HDF/XML files. This is ideal for the automated continuous updating of a local archive through a cron job; - it can parse the XML file to obtain metadata information about the related HDF files; - it can convert a HDF MODIS file to GEOTIFF format; - it can create a mosaic of several MODIS tiles to obtain large coverages including the creation of the merged XML metadata file with information of all tiles used in this mosaic. For format conversion and mosaicing the MODIS Reprojection Tool (MRT) is required, because at time MRT is the best free and open source software to manage original MODIS data and convert them into a different projection system or format while taking care of the special features of the original Sinusoidal projection. pyModis is composed of three modules: - downmodis.py contains a class downModis used to download MODIS data, it requires a “password” for the FTP transfer (usually your email address) and a path where to store the downloaded data. Other parameters are optional, such as the date range or the MODIS product to be downloaded; - parsemodis.py contains two classes, parseModis that parses metadata of a HDF file returning all useful information. It has also the capability to create a configuration file for MRT; the other class is parseModisMulti, it reads metadata of several HDF files, hence it is used to create the XML file for a mosaic. This class is also able to return the bounding box of all the tiles; - convertmodis.py is the module to do some simple operations on the original HDF files such as reprojection. It contains three classes and all of them require the MRT software to be installed. convertModis converts HDF files to GeoTIFF format; createMosaic creates a mosaic from several MODIS HDF files into a single HDF file; and processMosaic converts the raw data of MODIS using swath2grid from MRT-Swath. In pyModis the user can also find five command line tools to easily work with pyModis library: - modis download.py is the tool to download data, - modis parse.py reads metadata of a HDF file, prints information or writes them to a file, - modis multiparse.py reads metadata of several HDF files and prints bounding box or writes the MODIS XML metadata for a mosaic, - modis mosaic.py creates a HDF mosaic from several HDF files, - modis convert.py converts MODIS data to GeoTIFF or other formats and as well as different projection reference systems. During the presentation all these topics will be discussed and illustrated along with more information about the future of pyModis and the tools for the community (how to contribute or how to report a bug or an enhancement).
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
30:25 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

Raster Data In GeoServer And GeoTools: Achievements, Issues And Future Developments

The purpose of this presentation is, on a side, to dissect the developments performed during last year as far as raster data support in GeoTools and GeoServer is concerned, while on the other side to introduce and discuss the future development directions. Advancements and improvements for the management of raster mosaic and pyramids will be introduced and analyzed, as well as the latest developments for the exploitation of GDAL raster sources. Extensive details will be provided on the latest updates for the management of multidimensional raster data used in the Remote Sensing and MetOc fields. The presentation will also introduce and provide updates on the JAITools and ImageIO-Ext projects. JAITools provides a number of new raster data analysis operators, including powerful and fast raster algebra support. ImageIO-Ext bridges the gap across the Java world and native raster data access libraries providing high performance access to GDAL, Kakadu and other libraries. The presentation will wrap up providing an overview of unresolved issues and challenges that still need to be addressed, suggesting tips and workarounds allowing to leverage the full potential of the systems.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
25:38 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

The Importance Of Open Source Geospatial Labs In Widening Geospatial Education Worldwide

The importance of Open Source Geospatial Labs in widening Geospatial education worldwide Suchith Anand, University of Nottingham, UK Charlie Schweik, University of Massachusetts, Amherst, USA Helena Mitasova, North Carolina State University Maria Antonia Brovelli, Politecnico di Milano, Italy Serena Cotezee, University of Pretoria, South Africa Phil Davis, GeoTech Center, Delmar College, USA Patrick Hogan, NASA, USA Raphael Moreno, University of Colorado, Denver, USA Jeremy Morley, University of Nottingham, UK Although there has been tremendous growth in geospatial science over the last decade, the number of universities offering teaching in geospatial science in developing countries is very low. There are number of factors for this including high cost of software, lack of trained staff etc. But with the advent and maturity of free and open source geospatial software many universities in developing countries across the world will be establishing courses in geospatial science in the next few years. It was with this bigger mission in mind that in Sep 2011, the Open Source Geospatial Foundation (OSGeo) and the International Cartographic Association (ICA) signed an MoU with the aim of developing on a global basis collaboration opportunities for academia, industry and government organizations in open source GIS software and data. Within a span of one year, we now have established labs across the planet in 6 continents . We have now grown to 20 research labs across the world (6 in Europe, 3 in North America, 3 in South America, 4 in Asia, 3 in Africa and 1 in Australia). The three main aims of the ICA-OSGeo Lab Network are to provide expertise and support for the establishment of Open Source Geospatial Laboratories and Research Centers across the world for supporting development of open-source geospatial software technologies, training and expertise ; to provide support for building-up and supporting development of open source GIS training materials; to enable development of collaboration opportunities for academia, industry and government organizations in open source GIS for the purpose of creating a sustainable ecosystem for open source GIS globally. The availability of free and open source GIS will make possible for large number of universities especially in developing countries to also start courses in geospatial science. This will in true sense bring down the entry barrier for many students especially in developing countries to learn GIS. The OSGeo.org’s education and curriculum committee has a significant history of collaboration and established significant social capital among the network of participants. but up until now, we have only been able to achieve collaboration in the form of individual posts of metadata and links to educational material [2]. With the emergence of this lab network model, coupled with the right incentives, we are confident that this network can do more collectively on the education front, and we have not yet formed closer collaborative ties in the area of open geospatial application and research. Recently the authors listed above have been collaborating on a grant proposal to establish a new effort for this open geospatial lab network that mimics open source software collaboration and that includes three key components: (1) a coordinated teaching program; (2) a repository and a system for the management of new derivatives; and (3) a organized cross-node research program focusing on applications of open geospatial technologies to support local governance and management in several key environmental management areas. In this presentation, we will describe elements of this proposal, partly in an effort to encourage others at FOSS4G to consider joining in the effort, and to solicit other collaborative ideas from the audience.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
26:53 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

Taming Rich GML With stETL, A Lightweight Python Framework For Geospatial ETL

Data conversion combined with model and coordinate transformation from a source to a target datastore (files, databases) is a recurring task in almost every geospatial project. This proces is often refered to as ETL (Extract Transform Load). Source and/or target geo-data formats are increasingly encoded as GML (Geography Markup Language), either as flat records, so called Simple Features, but more and more using domain-specific, object oriented OGC/ISO GML Application Schema's. GML Application Schema's are for example heavily used within the INSPIRE Data Harmonization effort in Europe. Many National Mapping and Cadastral Agencies (NMCAs) use GML-encoded datasets as their bulk format for download and exchange and via Web Feature Services (WFSs).
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
25:06 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

The Met Office Open Data Journey

In November 2011, the UK Met Office launched DataPoint: an Application Programming Interface (API) for the release of its Open Data, in support of the Government’s desire for increased transparency and economic growth. Starting with just a handful of users, the service has grown in data, functionality and usage. This year the we are making further developments, responding to user feedback and ensuring INSPIRE compliance. This presentation will describe the journey so far and a forecast for the future.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
26:53 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

The RAGLD (Rapid Assembly Of Geo-centred Linked Data) Framework

As more linked data and open data emerges a need was identified to meet a rising demand for a suite of application developers’ tools to make it easier to bring together, use and exploit these diverse data sets. RAGLD aims to create a set of tools, components and services to make it easier to develop linked Data applications. This talk will describe the RAGLD framework and examples will be given on how it can be used.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
13:56 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

Using NoSQL & HTML5 Libraries To Rapidly Generate Interactive Web Visualisations Of High-volume Spatio-temporal Data

Twitter has developed over the past few years into a potent source of public opinion and comment. The service passed 500 million users in June 2012, collectively posting hundreds of millions of tweets each day, and several high-profile analyses of this data (such as the Twitter Political Index, which mapped sentiment across the US towards the 2012 presidential candidates over the course of their campaigns) have demonstrated its potential for insight and near-time customer feedback. Handling such large volumes and throughputs of data is a sizeable engineering challenge, however, and several commercial ventures (TweetReach, Tweet Archivist - many others) have sprung up specifically to deal with this complexity - at a cost. In addition, many existing solutions are unable to properly utilise the location data that is present in a significant proportion of tweets, losing out on the rich geographical context. This retrospective aims to demonstrate how an informed coupling of emerging open-source component technologies can be used to resolve the complex problems of i. large stored data volumes, ii. real-time streaming input, iii. concurrency of writes and iv. geographically querying and visualising results - with a minimal development outlay. Specifically, the construction of an open-source process to read, process, write, query and visualise streaming, geolocated Twitter data using the MongoDB NoSQL database and D3.js JavaScript library will be detailed, focusing on how MongoDB handles real-time spatial data (including spatial indexes & querying) and the unique features that make D3 so well-suited to visualising and exploring spatial data in the web browser.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
25:52 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

An Introduction To Open Source Geospatial

  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
28:57 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

Building Catastrophe Models With Open Data And Open Software

A catastrophe model is a tool/technique which estimates the potential loss of property and life following a major catastrophic event. Different types of events or perils are modelled including; windstorm, earthquake, flood, and storm surge. ELEMENTS is the in-house catastrophe modelling software which is developed by Impact Forecasting, part of Aon Benfield Analytics. Behind the software are models for a wide range of different event and peril types across many countries and regions of the world. To develop the different components of the catastrophe model, Impact Forecasting use a variety of proprietary and open solutions. Open Data sources such as OpenStreetMap, SRTM, CORINE land cover datasets are used, amongst others. The open-source programming language, Python, is also used extensively to create hazard footprints and files needed for the catastrophe model. The use of Open Source software and Open Data supplemented with other available proprietary data sources allow Impact Forecasting to build more flexible and transparent catastrophe models.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
29:23 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

A Toe In The Water - Using Open Source Software To Support Catchment Management Planning

Integrated river catchment management planning seeks to balance many demands on the water and land, to protect water resources and ecology for the benefit of the economy, society and the natural world. Third sector organisations have a key role in this process - providing both the practical delivery of river restoration work, and an 'honest broker' role between government, private sector interests and local communities, to try and balance these often conflicting interests in a sustainable catchment plan. However, access to the complex evidence, software models and datasets, which are required for strategic environmental management planning, can be difficult for the third sector and community groups, due to reasons such as cost, licensing restrictions or technical capability. As the umbrella organisation of the rivers trusts movement in England, Wales and Northern Ireland, The Rivers Trust has been exploring the potential for open source software and datasets to improve the sharing of information and evidence with a range of stakeholders in the catchment management planning process. A web GIS application for identifying and prioritising barriers to migratory fish (based on Geoserver) and an application to identify sources of diffuse sediment pollution (built on SAGA GIS) will be demonstrated, and plans for future development of open source tools and data sharing is discussed.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
18:37 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

Analysis Of Realtime Stream Data With Anvil

  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
18:55 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

Big Data In Standardization: Can This Fly?

In geo data, a main footprint coming from Big Data stems from remote sensing, atmospheric and ocean models, and statistics data. In the strive for interoperability, standardizaiton bodies establish interface specifications for large-scale geo services. Are these standards really helpful, or do they inhibit performance? We investigate this and show both positive and negative examples, based on OGC, INSPIRE, and ISO standards relevant for scalable geo services.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
23:20 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

A New GIS Toolbox For Integrating Massive Heterogeneous GIS Data For Land Use Change Analysis

Agricultural land use in Germany and related impacts on the environment and the use of natural resources are key research topics at the Thünen-Institute of Rural Studies. As spatial context is essential for the analysis of causal connections, GIS data regarding all necessary information was gathered during different research projects and prepared for processing in a database. In particular, the Integrated Administration and Control System, which was available for certain project purposes for several Federal Laender and years, serves as a very detailed data source for agricultural land use. We use different Open Source GIS software like PostgreSQL/PostGIS, GRASS and QuantumGIS for geoprocessing, supplemented with the proprietary ESRI product ArcGIS. After introducing the used input data and the general processing approach, this paper presents a selection of geoprocessing routines for which Open Source GIS software was used. As an exemplary 'use case' for the conclusions from the consecutive statistical analysis, we summarize impacts of increased biogas production on agricultural land use change highlighting the trend in biogas maize cultivation and the conversion of permanent grassland to agricultural cropland.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
32:08 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

Processing Data In GeoServer With WPS And SQL Views

This presentation will provide the attendee with an introduction to data processing in GeoServer by means of WPS, rendering transformations and SQL views. We will start by a brief introduction to GeoServer WPS capabilities, showing how to build processing request based on existing processes and how to build new processes leveraging scripting languages, and introducing unique GeoServer integration features, showing how processing can seamlessly integrate directly in the GeoServer data sources and complement existing services. The presentation will move on showing how to integrate on the fly processing in WMS requests, achieving high performance data displays of heatmaps, point interpolation and contour line extraction without having to pre-process the data in advance, and allowing the caller to interactively choose processing parameters. While the above shows how to make GeoSever perform the processing, the analytics abilities of spatial databases are not to be forgotten, the presentation will move on showing how certain classes of processing can be achieved directly in the database. Eventually, the presentation will close with some guidance on how to choose the best processing approach depending on the application needs, data volumes and frequency of update, mentioning also the possibly to leverage GeoServer own processes from batch tools such as GeoBatch. At the end the attendee will be able to easily issue WPS requests both for Vectors and Rasters to GeoServer trhough the WPS Demo Builder, enrich SLDs with awesome on-the-fly rendering transformations and play with virtal SQL views in order to create dynamic layers.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
28:27 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

Open Geospatial Data And Services Publication On The Cloud: The INGEOCLOUDS Open Source Approach

The cloud can be used as an infrastructure, as a platform or as a (desktop) software replacement according to the three different paradigms that it supports (IaaS, PaaS and SaaS). On the other hand at the moment more and more applications are using the cloud as their backend since it promises (unlimited) scalability and elasticity in terms of storage and computing power. In the open source geospatial world a lot of effort has been invested in developing excellent software that can be used to store, manage, visualize and publish on the web geospatial data and services. But when it comes to the cloud those offerings are not always readily available since the software, we all build, does not scale in a way that can take advantage of the cloud. In that respect we worked towards providing scalability and elasticity capabilities for the storage, querying and visualization of geospatial data based on existing open source solutions like the Mapserver, PostGIS, Apache and so on. We also worked on the lower part of the software stack so that we can build an elastic file system for storing geospatial data. So we are in the process of offering a fully open source solution that can take advantage of the cloud and its properties. Moreover we have coupled this solution with support for publishing anyone’s geospatial data as Linked Open Data so that they can be readily combined with other data on the web. In that respect we are using an open source SPARQL endpoint (Virtuoso) that allows us to store geospatially enabled information given that a suitable conceptual model will be provided described in RDF. Thus we allow for seamless integration of published data on the semantic web and we provide the necessary services for integrating this kind of offering in other applications in the future. Additionally we identified an emerging need to allow end users to publish their own data and create dynamically their own customized services on the cloud. Thus we exploit cloud’s “unlimited” storage capabilities to allow end users to publish their own data (as long as it is cost effective, too), combine them with existing data and create their own WMS/WFS customized services and publish them on the web. This has a great value-added for the users since they can actually publish their own maps. Finally, we demonstrate the capabilities of our technical solution by building and offering a set of advanced geophysical services through the platform. These services include a service for creating shakemaps (maps the visualize the effects caused by an earthquake to the environment), predicting landslides (providing maps assessing the possibility of landslides) and handling pollution information in ground waters. In conclusion, we offer an open source software stack that is based on existing open source software and extends it as needed in order to take to the most possible advantage of the properties of the cloud. We have tried to keep the software agnostic for the specific cloud and its capabilities. The work is carried out within the INGEOCLOUDS FP7 Project, co-funded by the EU, and with the participation of companies (AKKA technologies, France), research centers (CNR, Italy and FORTH, Greece) and data providers like geological surveys (GEUS, Denmark; GEO-ZS, Slovenia; BRGM, France and EKBAA, Greece) and earthquake research institutes (EPPO, Greece).
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
29:26 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2013

Online GIS - Meet The Cloud Publication Platforms That Will Revolutionize Our Industry

Web mapping has become very exciting in the last year or two. Many new products have come onto the market that make the creation and publication of web maps easier by an order of magnitude. The demand for quick and easy web maps isn’t a new one, so why is it only now that we’re seeing products that address this need enter the market? The answer is twofold: first, cloud computing has has hugely reduced the cost of running resource hungry map servers; and, second, the open source building blocks that most of the products featured in this presentation utilise have reached the level of maturity required to build reliable, scalable products on top of them. Most of this new generation of cloud based web map publication products are indeed “standing on the shoulders of giants” and wouldn’t exist if it wasn’t for the tremendous work done by the open source GIS community over the last decade. This presentation will be a follow up to my free ebook released in March entitled “Online GIS - Meet the Cloud Publication Platforms that Will Revolutionize our Industry” (www.onlinegis.com), the presentation will take a closer look at the products covered in the book and particular the open source building blocks that make them possible. You no doubt are wondering is why the CEO of a web map software company would want to give a presentation that not only looks at his product but also those of his “rivals”. The short answer is that I get asked all the time what the difference is between these products and also see the same question asked many times in online forums and social media channels, so it’s obviously something that needs answering. I also don’t view most of these products as our rivals, although all of the products featured in this presentation are capable of similar end results; the steps required to achieve those results differ hugely, with each aiming to make that process as smooth as possible for a certain type of user, be it programmer, casual GIS user or GIS analyst. After this presentation you’ll have a good idea of the differences between ArcGIS Online, CartoDB, GeoCommons, GISCloud, MangoMap and Mapbox, you will also have a clearer idea of which of the products is best suited to your unique needs and requirements as well as the open source building blocks that power them. This presentation isn’t going to show you how to use these products, but it will show you what is possible with each of them and what it takes in order to achieve the best results.
  • Published: 2013
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
out of 2 pages
Loading...
Feedback

Timings

  144 ms - page object
  100 ms - search
    8 ms - highlighting
    2 ms - highlighting/15578
    1 ms - highlighting/15553
    1 ms - highlighting/15504
    0 ms - highlighting/15573
    2 ms - highlighting/15574
    2 ms - highlighting/15582
    2 ms - highlighting/15569
    1 ms - highlighting/15527
    2 ms - highlighting/15509
    0 ms - highlighting/15589
    1 ms - highlighting/15512
    1 ms - highlighting/15510
    1 ms - highlighting/15584
    2 ms - highlighting/15501
    1 ms - highlighting/15505
    2 ms - highlighting/15534
    1 ms - highlighting/15557
    1 ms - highlighting/15551
    1 ms - highlighting/15503
    1 ms - highlighting/15539
    1 ms - highlighting/15506
    1 ms - highlighting/15508
    2 ms - highlighting/15514
    2 ms - highlighting/15565
    1 ms - highlighting/15564
    2 ms - highlighting/15572
    2 ms - highlighting/15583
    2 ms - highlighting/15538
    2 ms - highlighting/15590
    2 ms - highlighting/15549
    2 ms - highlighting/15532
    2 ms - highlighting/15533
    3 ms - highlighting/15541
    2 ms - highlighting/15517
    2 ms - highlighting/15587
    1 ms - highlighting/15591

Version

AV-Portal 3.7.0 (943df4b4639bec127ddc6b93adb0c7d8d995f77c)