Chaos Computer Club - archive feed

Lukas berichtet, wie aus der Idee, eine vernetze Lampe für das Camp zu bauen, nach einigen Planänderungen nun eine Chamäleon-Lampe geworden ist. Die Chamäleon-Lampe kann über einen Farbsensor Farben aus der Umgebung scannen und seine Lichtfarbe daran anpassen. Der Quellcode der Lampe findet sich unter https://git.chaotikum.org/chamaeleonidae Ein Vortrag im Rahmen der Fünf-Minuten-Termine. Die Idee ist einfach: An jedem vierten Mittwoch des Monats nutzen wir das volle Haus zum Open Space / Chaostreff und jede Person, die möchte, kann kurz vorstellen, was auch immer ihr vorschwebt. about this event: https://chaotikum.org/blog/2019/07/22/5-min-termine8/

Malte und Fabi haben für das CCCamp eine Lichtinstallation gebaut, die auf dem Camp auch mehr oder weniger gut funktioniert hat. In diesen fünf Minuten berichtet Malte aber nicht über die von künstlichem Feuerschein beleuchteten Rieseneiswürfel, sondern wie er aus den Ersatzteilen und Resten dieses Projekts und einer kaputten Ikea-Lampe spontan auf dem Camp ein interaktives buntes Licht mit integrierter Tastatur gebaut hat. Der Quellcode des Projektes findet sich hier: https://git.chaotikum.org/malte/taster-lampe Ein Vortrag im Rahmen der Fünf-Minuten-Termine. Die Idee ist einfach: An jedem vierten Mittwoch des Monats nutzen wir das volle Haus zum Open Space / Chaostreff und jede Person, die möchte, kann kurz vorstellen, was auch immer ihr vorschwebt. about this event: https://chaotikum.org/blog/2019/07/22/5-min-termine8/

Over the last several years, Element 84 has been centrally involved in NASA’s transition to the cloud, supporting their Earth Observing System (EOS) and Earthdata programs representing over 20PBs of remote sensing data and preparing for an order of magnitude increase with upcoming missions. Based on this experience, and backed by a variety of great open-source software, we have created a self-service remote sensing data management platform for smaller projects and teams. Cubesatdata.com is designed to support data management following downlink of L0 data and includes end-to-end system architecture, cloud archive optimization, data pipeline processing and archives of convenience, as well as a robust user-interface for search, discovery, and visualizations. This managed service provides a lower cost of entry for academic institutions, nonprofits, and other small businesses who lack the domain expertise or the desire to support an end-to-end data management system. This talk will focus on how the Cubesatdata.com service works and what open-source software made it possible. None about this event: https://talks.2019.foss4g.org/bucharest/talk/BPV3CK/

GeoNode is a Web Spatial Content Management System based entirely on Open Source tools whose purpose is to promote the sharing of data and their management in a simple environment where even non-expert users of GIS technologies can view, edit, manage, and share spatial data, maps, prints and documents attached. GeoNode was initiated in 2010 by the World Bank and OpenGeo but from 2011 is entirely run by the developer community that the project has been able to attract. It claims some large organizations among its contributors such as the United Nations, the World Bank and the European Commission as well as many NGOs and private companies. GeoNode is based on a set of robust and widespread open source components as Django as a basic framework, GeoServer for geospatial data management and OGC services and OpenLayers/Leaflet as mapping application. It can also communicate with PostgreSQL for vector data management. GeoSolutions has been involved into a number of projects, ranging from local administrations to global institutions, involving GeoNode deployments, customizations and enhancements. A gallery of projects and use cases will showcase the versatility and effectiveness of GeoNode, both as a standalone application and as a ser None about this event: https://talks.2019.foss4g.org/bucharest/talk/7FSDBW/

Developing meaningful and interactive materials for the GIS classroom is a major challenge for educators. In this talk, I present a framework for developing GIS educational resources - including interactive in-class activities and out-of-class exercises - through an open and collaborative approach. None about this event: https://talks.2019.foss4g.org/bucharest/talk/HYT3HJ/

Can you calculate the CO2 emissions for your city now or for the future? Ubigu Ltd, Tietotakomo, Gispo Ltd, Finnish Environment Institute and City of Tampere in Finland have crafted an open source climate tool during spring 2019. It was created using QGIS, PostGIS, GeoServer and Oskari map service for detecting what areas have more CO2 emissions than others taking into account also carbon sinks. The climate tool is used to do better land use planning to achieve CO2 neutral city. The base of the calculation comes from 250*250 m urban zone grid by Finnish Environment Institute where we have information about workplaces, demography and buildings. The tool utilizes also different climate parameters and combines the information to the grids. The user interface was created with QGIS and where analysis was driven with algorithms stored to PostGIS database. The tool also provides CO2 visualisation of the analysis results via GeoServer and in the end Oskari map service. In this presentation we will go through the background and demonstrate the use of the tool. None about this event: https://talks.2019.foss4g.org/bucharest/talk/B9F3TW/

This is the welcome speech of Mr. Dumitru Prunariu. None about this event: https://talks.2019.foss4g.org/bucharest/talk/PCWRFQ/

During the last decades, production of Land Cover maps (LC) at a continental and global scale has increased thanks to the progress in Earth Observation capacities, as well as due to high demand for these maps for many applications (e.g. climate change monitoring). However, the usefulness of these maps strongly depends on their accuracy. Therefore, for a fruitful LC maps exploitation, accuracy assessments (i.e. validation and inter-comparison) must antedate. Spatial analysis of the errors should then complement the accuracy assessment to provide insights into the local errors patterns which may not be outlined by traditional accuracy assessment techniques. According to this, we propose here a comprehensive analysis to target accuracy of LCs by focusing on the African continent. Two datasets, GlobeLand30 (GLC30) at and CCI Land Cover - S2 Prototype Land Cover 20m Map Of Africa (CCI Prototype Africa), at 30m and 20m resolution respectively, were considered. Inter-comparison was performed by means of traditional accuracy indexes computed from the error matrix (i.e. Overall Accuracy, Producer’s and User’s accuracy etc). Harmonization of the two maps in terms of resolution and classification nomenclature is prerequisite for inter-comparison. This was achieved by taking advantage of QGIS functionalities (e.g. resampling). Results of the accuracy assessment provide overall quality metrics for the map as well as quality indicators for each LC class. Additionally, spatial association statistics were adopted to investigate local patterns of the errors. The analysis was performed by means of GRASS and custom developed Python scripts exploiting cutting-edge data analysis libraries such as Pandas, Dask, and PySAL. By “virtual” overlaying CCI with GLC30, we computed which classes of CCI are under each pixel of GLC30, and what is the pixel fraction of a CCI class at each GLC30 pixel. Results of the overlay were stored in a vector point file whose coordinates represent centers of pixels of GLC30. If the classes of GLC30 and CCI for a point are not the same this results in an error with magnitude represented by the pixel fraction itself. Error fractions at each GLC30 pixel were analysed by means of Local Indicators of Spatial Association (LISA) to map non-random pattern in the spatial distribution of the errors as well as to assess their intensity and spatial association typology. By considering the results of accuracy assessment and LISA outputs, a comprehensive comparison of the GLC30 or CCI Prototype Africa is achieved. The results provide a guideline for detecting source of the error, which is potentially useful for future LC production (i.e. sampling design of training data). Lastly, it has been demonstrated that processing of massive datasets for accuracy assessment can be accomplished with Free and Open Source Software (FOSS). None about this event: https://talks.2019.foss4g.org/bucharest/talk/YJ8KJS/

GeoStyler is a react-based Open Source UI library for creating style editors for WebGIS applications. Cartographic styling of geodata on the web has been a recurring topic in the geoinformatics world. There are various standards - official standards as well as industry standards and project-related styling rules. However, we think that an interactive web-based software is the best solution to enable users to easily style their geodata. There are isolated solutions for some of the above mentioned standards, but no comprehensive web interface for converting styling rules into various formatshas been lacking so far. This universal web interface has been in development since mid-2018. Under the project name "GeoStyler", a web-based Open Source tool for the interactive creation of cartographic style regulations for geodata is being developed. Currently the following formats can be used: Style regulations are OGC SLD, OpenLayers Styles, QML * and Mapbox Style * (* in development). Supported geodata formats are GeoJSON, OGC WFS and Shapefiles. We want to present the current project status and show the general functionality of GeoStyler. We hope to attract the project to users and developers and to contribute to the Community. None about this event: https://talks.2019.foss4g.org/bucharest/talk/PEVW9K/

Reusable satellite and street maps data will be presented in this talk. Powered by open data and build with open source! Learn about the MapTiler data infrastructure and the high-resolution imagery available for Europe and the US, ready for your next project. Open geospatial data is the new raw material every GIS expert can build upon. Free vectors and rasters are everywhere, but come in many flavors which often make them challenging to leverage. This talk aims at presenting an innovative approach for harmonizing open geospatial data using the MapTiler software tools, powered by open-source. Several open data use cases and processing pipelines will be presented at the global scale, from mapping the OpenStreetMap planet to color toning high volumes of open imagery. Local use cases will also be shown, including on open data released by mapping agencies, such as the Ordnance Survey or the French IGN. Emphasis will be put on creating and sharing ready to use datasets that one can easily self-host and redistribute. Description of new geodata services and cloud infrastructure will finally demonstrate how open source technology significantly adds value to open data for the benefit of all, from the community to the business perspective None about this event: https://talks.2019.foss4g.org/bucharest/talk/NSMXGV/

# MapServer, Optimize for performance The MapServer software offers many powerful and advanced features that many users haven’t found yet. Come and learn some of the tricks to optimize configurations to achieve excellent performance in the rendering of stunning cartographic maps. Complex road shield labeling is one of the use cases that will be shared. Many of the tricks are based on advanced preprocessing of the data sources using the GDAL/OGR tools. Another subject will be around different ways to use tile indexes and how that can influence flexibility and performance. Some advanced line symbology examples will be highlighted, that are used in a larger open source development with Mapserver. Finally, we will show how to measure and even set up automatic tests to verify the results. The presenter is a frequent Mapserver user. None about this event: https://talks.2019.foss4g.org/bucharest/talk/QWB9AD/

Working Group 4, also called Spiral 4, of the UN Open GIS Initiative aims to provide solutions to collect geospatial data for UN missions. Due to the diversity and complexity of source data and mission fields, one single solution for geospatial data collection could not satisfy the requirements from the UN. Furthermore, most of the UN missions take place in regions where geospatial data are very limited. Spiral 4 has been working to develop and provide several solutions for divers and difficult requirements from the UN. In this talk, we will present the vision and solutions that we are developing so far, such as live drone maps, open geo-CMS, and quality control tools. We will also discuss and share the lessons learned from Spiral 4. None about this event: https://talks.2019.foss4g.org/bucharest/talk/D3YTDW/

You may have heard about the GeoCat Bridge plugin for ArcMAP. A plugin to facilitate hybrid open source/proprietary environments. We’re planning a similar tool for QGIS. We'll present the current status and challenges in this presentation. Main goal of this plugin is to ‘facilitate publication to an open OGC/INSPIRE SDI as easy as possible’. To facilitate this we apply various principles: - Publish data as layer/coverage/featuretype in GeoServer or Mapserver - Require minimal metadata to comply to OGC/INSPIRE - Register datasets in a catalog with proper linkage to/from the data services - Migrate data to GeoPackage, Postgres or reference existing data An important aspect to focus on is metadata management. Last year an initiative started to improve metadata management in QGIS. Some major improvements have been introduced. The Bridge tool will benefit from these developments. New options are the ability to import, export, validate and publish INSPIRE/ISO metadata. Improve SLD creation (for usage in Geoserver). Proper linkage between the catalog and the gis server. None about this event: https://talks.2019.foss4g.org/bucharest/talk/HKHWK9/

In this paper, we address the course of dimensionality and scalability issues while managing vast volumes of multidimensional raster data in the renewable energy modeling process in an appropriate spatial and temporal context. Tensor representation provides a convenient way to capture inter-dependencies along multiple dimensions. In this direction, we propose a sophisticated approach of handling large-scale multi-layered spatio-temporal data, adopted for raster-based geographic information systems (GIS). Moreover, it can serve as an extension of map algebra to multiple dimensions for spatio-temporal data processing. We use the multidimensional tensor framework to model such problems and apply computational graphs for efficient execution of calculation processes. In this approach, spatio-temporal data can be represented as non-overlapping, regular tiles of 2-D raster data, stacked according to the time of data captured. As a case study, we quantify the spatio-temporal dynamics of solar irradiation calculations and 2.5-D shadow calculations for cities at very high space-time resolution using the proposed framework. For that, we chose Tensorflow, an open source software library developed by Google using data flow graphs and the tensor data structure. We provide a comprehensive performance evaluation of the proposed model against r.sun based on GRASS GIS. Benchmarking shows that the tensor-based approach outperforms r.sun by up to 60%, concerning overall execution time for high-resolution datasets and fine-grained time intervals for daily sums of solar irradiation [Wh.m-2.day-1]. Precisely, the main characteristics of the proposed framework include defining, optimizing and efficiently calculating mathematical expressions involving multi-dimensional arrays (tensors); Transparent use of GPU computing such that the same code can be run either on CPUs or GPUs; Implicit parallelism and distributed execution with high scalability offered by data-flow based implementation. Moreover, the Python implementation of the proposed model makes it GRASS GIS ‘Add-on’ compatible. None about this event: https://talks.2019.foss4g.org/bucharest/talk/PUNTKE/

The presentation is more a "behind the scenes" talk, covering topic such as: * the people behind QGIS * the infrastructure behind QGIS * quality assurance efforts * organization and charter * challenges and changes in our organization * financial situation * challenges from being a large OSGEO project None about this event: https://talks.2019.foss4g.org/bucharest/talk/FXAJPH/

SAGA (System for Automated Geoscientific Analyses) is an open source geographic information system (GIS) used for editing and analysing spatial data. It includes a large number of modules for the analysis of vector (point, line and polygon), table, grid and image data. Among others the package includes modules for geostatistics, image classification, projections, simulation of dynamic processes (hydrology, landscape development) and terrain analysis. The functionality can be accessed through a GUI, the command line or by using the C++ API. SAGA has been in development since 2001, and the centre of SAGA development is located in the Institute of Geography at the University of Hamburg, with contributions from the growing world wide community. This talk will focus on the new features that have been added since the previous LTR version (2.3.2) which is the version used in QGis processing. None about this event: https://talks.2019.foss4g.org/bucharest/talk/7RPMVM/

Mapchete (https://github.com/ungarj/mapchete) is a tool written in Python which helps processing large amounts of geodata such as global high resolution datasets. It does so by executing a user-defined Python function on smaller chunks of data (tiles). The standard tiling schemes follow the well-known tile pyramid schemes used by WMTS which also enable mapchete to let the user easily preview process outputs using a built-in development server (Flask) hosting an OpenLayers page. By processing large areas through their much smaller tiles or metatiles, possible memory errors can be avoided. Furthermore, tiles can be processed on multiple CPU cores in parallel which speeds up the processing time. All geospatial data (i.e. raster and feature data) are internally handled and exposed to the user-defined process function either as NumPy arrays (raster) or GeoJSON-like dictionaries (features) which can easily be edited with well-known Python packages like shapely or scipy. For I/O operations mapchete makes heavy use of rasterio (https://github.com/mapbox/rasterio) and Fiona (https://github.com/Toblerity/Fiona). It can read data formats supported by these packages and can currently write outputs into WMTS-like tile directories of GeoTIF None about this event: https://talks.2019.foss4g.org/bucharest/talk/8TLYVA/

As the United Nations (UN) is a complex organization carrying out divers tasks in the world, most functions for an enterprise GIS are required. In order to support the requirements from the UN, the UN Open GIS Initiative was founded in 2016 with goals to provide GIS solutions for the UN based on open source software. The working group 3 of the initiative, named Spiral 3, aims to develop and deliver geo-analytic functions to the UN. In particular, a number of geo-analytic functions are developed by Spiral 3 to support field operations such as UN peace keeping operation. In this paper, we present a development use-case of geo-analytic functions for the UN, which is composed of four steps; analysis of requirements and functional specification, definition of development environment and system architecture, system development and test, and documentation of user manual and education materials. First, a comprehensive study on UN operations has been carried out, which covers the following tasks; situational awareness, security operations, military operations, protection of civilians, human rights violation investigation, epidemiological analysis, mission’s support and logistics operations, electoral support, disarmament, demobilizations and reintegration program, and humanitarian response operations. From this study, we derived 26 primitive geo-analytic functions. The users of geo-analytic functions for these tasks include mostly officers at field offices and geo-analysis experts at mission headquarters. Second, the system development environment was determined as Java using GeoTools for the compatibility and portability. The geo-analytic functions were developed as a plug-in of uDig, which is a Java-based open source desktop GIS. It means that the preparation and pre-processing of data for geo-analysis and the visualization of the analysis are supported by uDig. Third, an experiment of the developed system was performed with a scenario of Ebola virus spread. It shows that the system properly supports the field operations of Ebola virus spread. The experiment also shows the strength and weakness of the developed geo-analysis functions in comparison with commercial GIS. As the fourth step of the development, a user-manual is published via web and an education material was also developed under the OSGeo-UN Committee Educational Challenge Program. Through the use-case study presented in the paper, we would like to share the experiences and lessons about the development of geo-analytic functions, which would be used as a reference for other geo-analytic function development. None about this event: https://talks.2019.foss4g.org/bucharest/talk/PRXB9V/

A number of climate change research projects discover dependencies between dynamics of vegetation indexes and dynamics of meteorological parameters, which make possible estimation and monitoring of growing season parameters using remote sensing data. In our study, we use Normalized Difference Water Index (NDWI) that can be derived automatically from the daily satellite imagery collected by MODIS sensor. The NDWI indicates amount of liquid water in plant tissue, and then reflects change of vegetation growing conditions and particularly growing season change. To ensure monitoring of growing season parameters we elaborated an automated software complex that incorporates desktop Geographic Information System (GIS) software (QGIS was used), geospatial database and complex of computational tools. The GIS is used as an infrastructure element for operating and visualization purposes, while the database together with computational tools enable storage and multipurpose processing of meteorological and remote sensing data. The meteorological data is collected for the past period of 130 years and NDWI data for the 20 years. Developed complex is tested on the example of Republic of Komi (Northern part of European Russia) that is covered by Taiga and Tundra natural zones and impacted by different climate forming factors. Currently we describe architecture of the elaborated complex and design of data processing chains. Elaborated complex ensure automation of downloading raw remote sensing data and reprocessing it into gridded NDWI maps. In this context, it can be underlined that daily collected MODIS imagery can be discovered as big geospatial data, due to this we were needed to resolve a number of optimization tasks to implement its processing. Subsequently, NDWI data is used to produce gridded map series that reflects time and spatial dynamics of growing season characteristics. Produced data have a special significance for areas with sparse meteorological network. Keywords: GIS, Remote Sensing Data, Climate Change, Growing Season, Vegetation Indexes, MODIS, NDWI. None about this event: https://talks.2019.foss4g.org/bucharest/talk/77BJYC/

With the LiDAR developments, point cloud is becoming a valuable resource to build 3D models of Digital Twins, the virtual representation of a real world physical feature (object or system). Even though 3D point cloud can be more suitable to depict the real world, it requires HPC. 3D model representations help applications to quickly handle and navigate data comparing to point cloud. However, the 3D model construction of every physical feature usually necessitates expensive time and labor resources to organize and extract the features outlines by interactive manual operations. Recently, deep learning is used to derive semantic classes necessary for 3D modeling by automated classification and segmentation. PinSout (Point-in Space-out) is a new framework to automatically generate CityGML LOD4 from raw 3D point cloud data by using PointNet. This framework extracts each object required for 3D indoor space modeling from point cloud after learning the deep model with the annotated dataset of Standford Building Parser. After the semantic segmentation, it computes the contour of an object using PCL to augment each spatial indoor model. Finally, the extracted objects are stored into 3D CityDB and provided as CityGML LOD4 data. None about this event: https://talks.2019.foss4g.org/bucharest/talk/VT9Q73/

geOrchestra gathers an open source community to build an INSPIRE compliant Spatial Data Infrastructure. The result is a customizable, interoperable and free INSPIRE SDI, based on the best geospatial open source components. Referenced on Github, geOrchestra offers a solution to publish and share spatial data on intranet and internet. geOrchestra project is built around several independent and interoperable applications, such as Geoserver, GeoNetwork. These various modules are loosely coupled, meaning that the operation of each module does not affect the other. Communication between modules uses OGC standards. geOrchestra was designed to meet the requirements of the INSPIRE Directive, which aims to establish a spatial data infrastructure at European scale, with the aim to meet the challenges of sustainable development. This talk will describe the geOrchestra community project and give a project status update. None about this event: https://talks.2019.foss4g.org/bucharest/talk/BX3NXY/

The emergence of software-as-a-service platforms for geoprocessing of large raster datasets provides a tempting and fast way to try new raster algorithms or indicators. As with any other SaaS platform, the downside is the inability to run the same process in our own computers; be it because of recklessness during systems design or because of a will and purpose to create vendor lock-in. This talk will analyze such a case of vendor lock-in in raster geoprocessing SaaS, and a means of running the same raster processes efficiently in the end-user's (or operator's) hardware (so-called "edge computing" for the buzzword-inclined). Moving away from SaaS in this case even provides extra benefits, such as better data cacheability and real-time algorithm tweaking. None about this event: https://talks.2019.foss4g.org/bucharest/talk/YKC3DT/

A recent fun blog post turned into an idea for synthesizing imagery training data for ML applications. In the post we presented a method for identifying sasquatch using cloud native geospatial methods and tools. This talk will describe the cloud native approach we took and the opensource tools that were used. We will then describe and demonstrate an idea to create synthetic satellite imagery training data using opensource libraries and tools. None about this event: https://talks.2019.foss4g.org/bucharest/talk/SZDFF3/

Deutsche Telekom AG (DTAG) revolutionises the planning process of fibre networks in order to increase the number of connected households and industries dramatically as well as to shorten the time to market in general. A brand-new world comprising the build up of a major SDI, lots of geodata and heavy geoprocessing is needed to substitute previous manual tasks and to sustain the goals. Think about a project, that will be developed by +10 companies, each with its own frameworks, procedures and deployment workflows. To succeed, you'll need more than confidence in the team. This is also because of other complicating factors like IT security, large data pipelines or ever-changing IT infrastructure. This is where DevOps and AGILE practices came to the rescue. It gave a structure and a common understanding of the workflows to every project member, as well provided enough automation and flexibility to adjust to the constant changes the project undergone. In this talk, we’ll present the key challenges and how DTAG and the team of the FTTH-Factory successfully implements agile and DevOps workflows for the project. If we’re brave, we’ll do DevOps on stage. None about this event: https://talks.2019.foss4g.org/bucharest/talk/DVLP9R/

The brave new world of 3D mapping has taken little notice of time-proven rules of cartography, as if arbitrary viewing angles could somehow obliterate the need to convey a clear hierarchy of features. In this talk we will show how the vector styling capabilities in vts-geospatial may be used to overcome that long-standing shortcoming. From the choice of a basemap through the definition of intellectual and visual hierarchies to the coding of visual style, we will show how to produce 3D maps which aspire not only to the aesthetical appeal but also to the information value of a real cartographic product. None about this event: https://talks.2019.foss4g.org/bucharest/talk/QA3M7X/

QGIS 2.18 has been discontinued - the king is dead. QGIS 3.4 is the new long term release - long live the king! QGIS 3.10 is being developed - The princess is growing In this talk, I'll try to highlight the very best features available in the QGIS 3.x series like: - User profiles - Multiple map views - Native 3D viewer with support for vector features and mesh data - Mesh data support - Autocompleting search - Unified Data Source Manager - GeoPackage as the default format - Select features by value tool - Lots of new processing tools - Project DB/Auxillary storage and easy custom labelling - Editing in place - New renderers - Lots of improvements to Print composer - Valid CRS Extents Preview None about this event: https://talks.2019.foss4g.org/bucharest/talk/9TMMFG/

The GeoExt project [1] is a JavaScript library combining the OpenLayers mapping library [2] and the JavaScript framework ExtJS [3]. The talk will give a brief history of the project, and a summary of its dependencies and versions. Several new features recently developed for the latest GeoExt release will be presented. The talk will include an overview of two more Open Source JavaScript libraries which bring additional power and functionality to GeoExt: BasiGX [4] and GeoStyler [5]. BasiGX is a higher-level JavaScript library that builds on top of GeoExt and focusses on advanced GIS user interfaces and mapping tools for the web. GeoStyler is a JavaScript library for cartographic styling of geodata, and can be combined with a GeoExt solution to apply several formats to layers, e.g. SLD (Styled Layer Descriptor) files. The talk will include examples of real-world projects using GeoExt, along with recommendations on what types of projects are most suitable to develop them using GeoExt and its associated technologies. Finally a roadmap for the future of GeoExt will be outlined along with how developers and users can get involved. None about this event: https://talks.2019.foss4g.org/bucharest/talk/FNANSU/

This abstract focuses on the Resilience Academy which represents the commitment of the World Bank to improve Tanzania’s skill base and to maximize the impact and sustainability through the establishment of university partnerships that transfer skills and risk management tools to the next generation. The Resilience Academy concept embraces the idea that supports the development and sustainability of geospatial and urban resilience competencies in Tanzanian universities and thus enhances the sustainability of digital data set management and eventually risk management practices in Tanzania. None about this event: https://talks.2019.foss4g.org/bucharest/talk/XAFQB9/

Not all open data comes in traditional geospatial formats: for years, organizations around the world have collected photo and video logs of roads for annual surveys, but until recently these have been overlooked as a form of open data. Mapillary now hosts over 500,000km of government road imagery. We will explore how this is being used both to improve government workflows and how traffic signs, crosswalks, and other data can be added to OpenSteetMap by citizens using imagery previously seen only by a handful of government employees. None about this event: https://talks.2019.foss4g.org/bucharest/talk/LKFNAS/

<p>SMODERP2D is a runoff-soil erosion physically-based distributed episodic model used for calculation and prediction processes at agricultural areas and small watersheds. The core of the model is a raster based cell-by-cell mass balance calculation which includes the key hydrological processes, such as effective precipitation, surface runoff and stream network routing. Effective precipitation, the forcing of the runoff and erosion processes, is reduced by a surface retention and an infiltration. Surface runoff consists of two components: slower sheet and concentrated rapid rill flow. Stream network routing is performed line-by-line in user predefined polyline layer. SMODERP is a long-term running project driven by the Department of Landscape Water Conservation at the Czech Technical University in Prague. At the beginning SMODERP has been developed as a surface runoff simulated by profile model (1D). Later the model has been redesigned using spatially distributed method. This version is named SMODERP2D. Ongoing development (https://github.com/storm-fsv-cvut/smoderp2d) is focused on obtaining parameters of the hydrological models, incorporating new infiltration and flow routing routines, and conceptualization of a rill flow and rill development. The model belongs to a family of so called GIS-based hydrological models utilizing capabilities of GIS software for geodata processing. Importantly, the SMODERP2D project is currently entering the open source world. Originally the model could be run only in proprietary Esri ArcGIS platform. A new version of the model presented by this contribution adds support for two key open source GIS platforms, GRASS GIS and QGIS. A newly developed GRASS module and QGIS plugin significantly increases accessibility of the SMODERP2D model for research purposes and also for engineering practice. Middle scale distributed hydrological models often encounter with a high computation costs and long model runtime. Long runtime is caused by high resolution input data which is easily available nowadays. The project also includes an experimental version of the SMODERP2D model enabling the parallelization of computations. This parallelization is done using TensorFlow, and its goal is to decrease the time needed for its run. It is supported by both CPU and GPU. Parallelization of computations is an important step towards providing SMODERP2D web processing services in order to allow quick and easy integration to highly specialized platforms such as Atlas Ltd. None</p> about this event: https://talks.2019.foss4g.org/bucharest/talk/BCVBMK/