Chaos Computer Club - archive feed

about this event: https://projects.alpaka.space/jhhh19/talk/ZGZALC/

Irre viele Lebensmittel werden jeden Tag wegschmissen, die noch verwendet werden könnten. about this event: https://projects.alpaka.space/jhhh19/talk/USYQZB/

Klima- Alarm ist ein Sensor der die Qualität der Luft in deiner Umgebung misst. about this event: https://projects.alpaka.space/jhhh19/talk/UDU79L/

Rette deine Stadt gegen deinen Kontrahenten der die Umwelt zerstören will. about this event: https://projects.alpaka.space/jhhh19/talk/GQMTFL/

about this event: https://projects.alpaka.space/jhhh19/talk/DYSVB8/

about this event: https://c3voc.de

about this event: https://projects.alpaka.space/jhhh19/talk/X3VJT9/

Kollaborative Webseite zum Quellenaustausch und Diskussion zu politischen Themen Ziel: Die Filter- / Meinungsblase durchbrechen und verschiedene Standpunkte vermitteln about this event: https://projects.alpaka.space/jhhh19/talk/BLASN3/

Natural hazards such as floods are receiving a lot of attention around the world and the vulnerability assessment is a strategy to develop prevention and mitigation plans. But it is important to work under a conceptual framework that considers communities as socio-ecosystems, especially with climate change. In Colombia, floods have always been a serious threat for its population, and many coastal communities could be in risk. To face these hazards, mangrove forests are fundamental elements for the resilience of coastal livelihoods and the entire coastal zones. Then the COASTMAP URABÁ project that is being carried out since 2017 in the Urabá gulf in Colombia and that so far has created free access maps of two coastal communities using the mapping methodology created by the HOT team, has allowed the development of a Flood Vulnerability Index for coastal social-ecosystems (FVIc) that could be used in all the coastal communities of the country. None about this event: https://talks.2019.foss4g.org/bucharest/talk/B7EWW9/

The figure of the Earth can be modelled either by a cartesian plane, a sphere or an (oblate) ellipsoid, in decreasing order with respect to the approximation quality. The shortest path between two points on such a surface is called a geodesic. Studying geodesic problems on ellipsoids dates back to Newton. However, the majority of open-source GIS systems today use methods on the cartesian plane. The main advantages of those approaches are simplicity of implementation and performance. On the other hand, those approaches come with a handicap: accuracy. We experimentally study the accuracy-performance trade-offs of various methods for distance computation (as well as similar geodesic problems such as azimuth and area computation). We test projections paired with cartesian computations, spherical-trigonometric computations and a number of ellipsoidal methods such as [Andoyer'65] and [Thomas'70] formulas, [Vincenty'75] iterative method, great elliptic arc's method, and [Karney'15] series approximation. We also show that some methods from the bibliography (e.g. [Tseng'15]) are neither faster nor more accurate compared to the above list of methods and thus become redundant. For our experiments we use the open source libraries Boost Geometry and GeographicLib. Our results are of independent interest since we are not aware of a similar experimental study. More interestingly, they can be used as a reference for practitioners that want to use the most efficient method with respect to some given accuracy. Geodesic computations (such as distance computations) apart from being a fundamental problem in computational geometry and geography/geodesy are also building blocks for many higher level algorithms such as k-nearest neighbour problems, line interpolation, densification of geometries, area and buffer, to name a few. # References * Some experimental results can be found here: https://github.com/vissarion/geometry/wiki/Accuracy-and-performance-of-geographic-algorithms * A related talk (with some graphs on performance and accuracy) can be found here https://fosdem.org/2019/schedule/event/geo_boostgeometry * The source code of most of the algorithms of the study is in Boost Geometry: https://github.com/boostorg/geometry but we contain to our study GeographicLib https://geographiclib.sourceforge.io None about this event: https://talks.2019.foss4g.org/bucharest/talk/TANLXN/

This is the closing ceremony of FOSS4G2019 Bucharest! None about this event: https://talks.2019.foss4g.org/bucharest/talk/A9PQLB/

The Copernicus Global Land Service (CGLS) aims to provide yearly-updated land cover maps, including land cover fractions (i.e. the fraction of each land cover class within each pixel). It makes use of FOSS software (Python, R, GDAL) for all data processing steps. Our work in the project focuses on two aspects: land cover fraction mapping at the continental level (Africa) and yearly map updating. For land cover fraction mapping, to select the most appropriate method, a number of machine learning algorithms were run on over 300 covariates: Proba-V image time series (100m, 4 bands), DEM, soil and climate properties. Random Forest performed the best with RMSE=16.6, MAE=9.2, and 68±4% overall accuracy. To generate yearly map updates, we investigated different vegetation indices and break detection methods, as well as their scalability to big data (MODIS time series, 2009-2019). All change detection methods tended to overestimate change. Proba-V Mission Exploitation Platform Spark cluster was used to run chunked jobs in parallel. In the future, CGLS aims to move to Sentinel-1+2 for land cover classification and Landsat 5+7+8 for change detection for higher spatial and spectral resolution, but that makes big data challenges even bigger. None about this event: https://talks.2019.foss4g.org/bucharest/talk/BJURSG/

Vector tiles are an established format to publish highly interactive maps for use on mobile devices and desktop browsers. A benchmark compares MVT tile generation and tile serving performance of specialized servers like t-rex and proven map servers like UMN Mapserver. None about this event: https://talks.2019.foss4g.org/bucharest/talk/VUHLFF/

Funded be the European Commission as a H2020 project, openEO aims for a new web service standard to process Earth Observation data cubes. At its core, openEO provides an http application programming interface (API) that defines how users can discover Earth observation data cubes and process them on compliant cloud back-ends. The back-ends run their own API instance, translating the http requests to their environment. The front end API implementation can serve different languages (R, Python, Javascript) on the client side. The openEO project has foreseen that APIs are implemented with an open source license (Apache 2.0). A number of back-ends are already available that are compatible with this suggested openEO standard. For instance, within the Joint Research Centre (JRC) of the European Commission, an API implemented in Python is being developed that can discover and process geospatial data collections available in the JRC Earth Observation Data and Processing Platform (JEODPP). For the back-end, an in-house library is being developed under the European Union Public Licence (EUPL). In this presentation, we will highlight the openEO concepts and focus in particular on the JRC back-end implementation details. None about this event: https://talks.2019.foss4g.org/bucharest/talk/ZDVLRS/

(G)EO Hack 19 is an innovative hackathon at the interface of traditional and scientific knowledge that will take place during the GEO Ministerial Summit.The EO-based challenges will be co-designed by indigenous youth communities throughout the world to encourage the co-development of innovative EO-based applications that are locally relevant and enhance the communities way of learning. The primary goals of the activity are to promote the use of open EO data among indigenous communities and ultimately to co-design locally relevant free and open source software that promote new means for aligning local/ traditional knowledge and science co-production across cultural and generational lines. None about this event: https://talks.2019.foss4g.org/bucharest/talk/ES9YTG/

Created to serve a locally-led global map making network, the original Open Green Map (OGM) - www.opengreenmap.org, a social mapping platform, was launched by Green Map System in 2009. In the decade since, an 8 language interface and mobile site collector are among the features that attracted users in 40 countries. Dubbed ‘open’ as sites could be enhanced by the public, more than 40,000 sites were added to the OGM locally on 600 unique maps. Many of these maps became the backbone for local engagement projects and led to interactive spin off editions, print maps, experiences and media projects. Already recognized in 65 countries, Green Map Icons bring a wide range of sustainability resources to light. These lively symbols identify, promote and link local resources in an eye-catching, easy to grasp manner that systematically connects themes and places in meaningful way. Green Map has always served a mixed group of participants, including NGOs, schools and local governments. Since the globally-designed set of shared icons date to 1996, for many early users, Green Map was their first internet project. These evolving Icons have been provided as a font so they could be used with any graphic design or GIS application. None about this event: https://talks.2019.foss4g.org/bucharest/talk/W7JXB9/

During this 90 minutes slot, the results obtained by the teams at EO Data Challenge will shortly present their results. The following talks will be presented: Visualization and Analysis of Big Multidimensional Geospatial Data on the Web (Candan Eylül Kilsedar), STAC for the decentralized Web (Volker Mische), WebGL for in-browser GeoTIFF processing (Iván Sánchez Ortega), Citizen science in support of landslide detection and monitoring (Vasil Yordanov), EO Data Challenge results (Bang Pham Huu) EO Data Challenge results (Ivian Adrian Albu), LeafS - LEveraging Artificial Intelligence for Forest Sustainability (Teodora Selea). None about this event: https://talks.2019.foss4g.org/bucharest/talk/K7ADDK/

Our seas and oceans are substantially polluted by conventional and chemical munitions from the two World Wars. They were introduced by different pathways e.g. mine laying, naval battles and shipwrecks. However, the biggest amount originates from large scale ammunition dumping activities after World War II. The goal of the OpenSource based Ammunition Cadastre Sea is therefore data acquisition, assessment and monitoring of the status of ammunitions in our seas and oceans and their effects. Almost all relevant data in this field has a spatial context. Therefore the idea is capturing, visualizing and analyzing everything that is related to ammunition in the sea (e.g documents, maps, high-resolution measurements) and combine everything by spatial relationships. In addition, a key component of the Ammunition Cadastre Sea are European research projects e.g. DAIMON or North Sea Wrecks. DAIMON (Decision Aid for Marine Munitions) uses for example artificial intelligence to analyze complex situations and provides recommendations for actions. None about this event: https://talks.2019.foss4g.org/bucharest/talk/NPY8RV/

The availability of the growing volume of environmental data from the Sentinel satellites represents a unique opportunity for the operational usage of Earth Observation (EO) for wetland inventorying, assessment and monitoring on global scale. However, it also poses major challenges in terms of data access and exploitation to achieve its full potential. GlobWetland Africa (GWA) Toolbox is an outcome of an initiative of the European Space Agency launched to facilitate the exploitation of satellite observations for the conservation, wise-use and effective management of wetlands in Africa. It is a fully free and open-source software toolbox that seamlessly combines algorithms from a number of EO and GIS tools like SNAP, QGIS, OrfeoToolbox, GRASS GIS, TauDEM together with customised Python and R scripts (e.g. for hydrological modelling) into one GUI based on QGIS. This is achieved by relying heavily on the QGIS Processing Toolbox. The algorithms are then combined into workflows, which guide less experienced users through step-by-step process of EO data analysis for wetland delineation, wetland habitat mapping, monitoring of inundation regimes and water quality as well as for mangrove mapping and river basin hydrology assessments. None about this event: https://talks.2019.foss4g.org/bucharest/talk/LSUCTK/

The defining characteristic of point cloud data is that they are large, and tools such as [Entwine](https://entwine.io) and the Entwine Point Tile specification can help you overcome their bigness. We will discuss how we used Entwine and EPT to construct point cloud web services for the [USGS 3DEP LiDAR data](https://usgs.entwine.io) of the United States as an Amazon Public Dataset. We will also demonstrate how to leverage EPT web services with open source software such as [PDAL](https://pdal.io) to extract information, enhance data utility, and reduce data volume for tasks such as filtering, object identification, and visualization. You will learn about how these tools work together with others such as [GDAL](https://www.gdal.org/) and [PROJ](https://proj4.org/) to provide data management and processing pipelines for expansive data holdings. None about this event: https://talks.2019.foss4g.org/bucharest/talk/9M3WQB/

The sheer amount of statistics collected as the world entered the age of Big Data transformed computers from simple tools for processing data into complex machines able to present the results of this processing as compelling visuals with little to no human input. And when it comes to presenting the evolution of phenomena that vary in space and time, there is no better solution than a map. As part of a project involving a major institutional client, we developed a FOSSGIS-based custom spatial visualisation widget for use with Microsoft’s PowerBi. Integrating with an environment that includes a plethora of graphical representations for data, the developed widget, built on top of OpenLayers, provides a novel view of data with spatial characteristics. Unlike the default map widgets, it allows the use of custom, time-enabled geometries, as well as custom basemaps, consumed using open standards (GeoJSON, WMS), custom projections (with Proj4js), feature zoom across the International Date Line and complex visualisation using charts on top of choropleth maps. We thus show the advantages of using open-source GIS technology on top of proprietary frameworks, providing advanced, project-specific features supported by a wide community. None about this event: https://talks.2019.foss4g.org/bucharest/talk/A9LKYS/

In a disaster or humanitarian relief context, time obviously matters. This talk will show how, without concern for the details of servers and storage, you can use small amounts of code to quickly build powerful solutions, using a prototype disaster response pipeline as an example. None about this event: https://talks.2019.foss4g.org/bucharest/talk/ZFWFG9/

We would like to present how our small community of Geoinquiet@s Argentina works. Since 2012 we have been working hard in order to evangelize about free and open source software. Drawing inspiration, and a name, from the Geoinquietos Spain micro chapter a few people started gathering (beer in between) to spread the word about free tools for geomatics. Since then, we have been able to do four conferences, some together with the OpenStreetMap (OSM) community. Recently we became an official OSGEO local chapter (the first constituted in Latin America). In order to keep growing, we have set up an nonprofit organization (Geolibres), to serve as a legal support not only for Geoinquiet@s, but also for OSM Argentina or GeochicasOSM. We propose the bid of Buenos Aires as the location for the 2021 main FOSS4G event, because we believe it would be a great opportunity for the entire region, creating new chances for exchange between key actors in the world of free and open geomatics. Our commitment is for more conferences, workshops and other projects that infect the spirit of free and open source software in more people, communities, companies, organizations and universities every time. None about this event: https://talks.2019.foss4g.org/bucharest/talk/K93FD7/

Agency for Communication Networks and Services of the Republic of Slovenia (AKOS) is the national regulator and one of its missions is to promote competition, to ensure equal conditions for the operation of electronic communication network operators and service providers. AKOS established open source mapping system using PostgreSQL/PostGIS, QGIS and Geoserver for effective supervision of electronic communications and services. Database consists of spatially oriented data as well as attribute data collected from owners of electronic communications infrastructure and different public institutions e.g. The surveying and mapping authority of the RS, Ministry of the interior, etc. Combining these data gives AKOS complete overview of the networks availability and population/homes coverages by various broadband and mobile networks. Database is being updated every few months with newer data, so we can monitor development of broadband services by years and by owners of communications infrastructure. AKOS launched an open portal to enable public access to the part of these data for interested stakeholders in 2019. Main purpose of this portal is to reduce costs of building superfast networks (VHCN), encourage co-usage and joint construction. None about this event: https://talks.2019.foss4g.org/bucharest/talk/8Y9XVL/

<p>A common question seen on many open source mailing lists is “When will you guys fix my bug? It is critical to my company!” This is often followed by one of the developers replying to say “When you write a fix or pay someone to do it”. This leads to the user complaining to everyone that this “snarkiness” is not a “welcoming” response or how unreasonable it is to expect them to learn to program, or to pay. The discussion often descends into a rambling maze of twisty insults and justifications. When the fuss dies down, all the developers go back to doing what they the were doing (something useful) and the user becomes either a dissatisfied user or an ex-user. This talk by two veteran open source developers will help users see that play out from our the developer point of view. We’ll look at the reasons that drive developers to share their code, the licencing conditions covering it, the real life of developers and associated constraints, and what is actually reasonable to expect from both sides. None</p> about this event: https://talks.2019.foss4g.org/bucharest/talk/D9MXGV/

None about this event: https://talks.2019.foss4g.org/bucharest/talk/RSUTDW/

In 2018, Ecometrica Ltd. was tasked with identifying potential deforestation over 7000 sites spread across South America over a one year period. This required the analysis of more than 15 Terabytes of satellite imagery, and was equivalent to processing a total area of approximately 25 million km2 for the entire time sequence. Given the vast area and dense time series data required, we developed an approach that uses freely available data from Sentinel 1 (radar) and the Hansen et. al. Forest/Non-Forest map, and processed the imagery with using an open source stack including data preparation software (SNAP toolbox), Omnibus change detection algorithm, and Python 3.x GIS libraries (GDAL, Fiona and Rasterio etc). None about this event: https://talks.2019.foss4g.org/bucharest/talk/TMEUWB/

When disaster strikes developing countries, a lack of geographic data is often a hindrance to first response and relief operations. To address this lack of geographic data, remote mapping and especially mapathons have played an important role in collecting geographic data in OpenStreetMap (OSM) that can be used to plan activities in areas effected by disaster or other humanitarian efforts. During mapathons, volunteers from various backgrounds get together to map a specific area using satellite imagery or aerial photographs. The expertise and motivation of these volunteers generally differ. Even though the geographic data in OSM is invaluable in cases where little to no data is available, the quality of the data collected during mapathons is often questioned. In this paper, we present our results from an evaluation of university students’ motivation for participating in mapathons and their productivity (i.e. how much data they contributed). To achieve our aim, we hosted four mapathons for final year university students where the participants were asked to complete a short questionnaire to determine their motivations and personal opinions of the mapathon. Afterwards, the productivity for two mapathons were evaluated. Final year students enrolled in a geoinformatics module were offered extra credit for participating in the mapathons. As a result, the majority of the students participated in all four mapathons and the answers did not differ significantly between the four mapathons. One of the main reasons mentioned, apart from extra credit, was that the participants felt a sense of humanitarianism through contributing to communities in need by assisting. Additionally, the social aspect also came through with a large percentage of the participants indicating that mapathons are fun and that they learned something new, for example by improving their digitizing skills or that humanitarian organizations need help. Participants also indicated that the tools (i.e. OSM and iD editor) were easy to use, but that the imagery is sometimes not good enough due to cloud coverage. The general productivity for two mapathons was evaluated and we found that with more experience the participants were generally more productive. A further step was taken by investigating five individuals productivity. It was clear that their productivity increased, and that they made fewer errors during the subsequent mapathons. The results from this evaluation provided insight and knowledge that could assist mapathon organisers to create a more productive environment for participants with the hopes of encouraging them to produce high quality data. The feedback from students was clear that if they receive information about the aim of a mapathon and why the data is important, they are more motivated to produce high volumes of quality data. None about this event: https://talks.2019.foss4g.org/bucharest/talk/THMVYS/

The SpatioTemporal Asset Catalog specification is an emerging standard for to cataloging geospatial data from different sources, and a specification for serving that data in an API. This talk will be a detailed overview of STAC illustrating it's usefullness in integration with cloud-based processing workflows. It will cover the core set of metadata fields for STAC Catalogs, Collections, and Items, along with available extensions for describing different types of data (EO, SAR, Point Cloud, etc.). With the basics of STAC in hand, we will then go over the available Open Source tools that are available for working with STAC metadata: validators, compliant APIs, client command line tools and libraries for search, access, and exploitation. Finally we will give an overview of available STAC catalogs for searching and accessing publicly available datasets (e.g., Landsat-8, Sentinel-1/2, NAIP) using these Open Source tools. After this talk you should have a good understanding of the metadata used to describe satellite imagery and be able to use existing open-source tools to immediately search and access this data. None about this event: https://talks.2019.foss4g.org/bucharest/talk/JYM89Y/

GeochicasOSM is a community of mainly Spanish-speaking women, from Latin America and Spain, work mapping OpenStreetMap (OSM) and Wikipedia, and related to the geo world and geotechnologies, which work with the goal of closing the gender gap in different communities in which they participate through joint and collaborative projects and initiatives among women. The group was created at the 'SOTM LATAM 2016' Conference in São Paulo (Brazil) and there are currently users in at least 20 countries around 3 continents. The co-founders are Selene, Céline and Miriam, and are based in Mexico and Paraguay. Among its diverse and varied projects, with the common nexus of making women visible, the following can be highlighted: Survey on gender in the OpenStreetMap community; Training spaces; Preparation of maps with different topics with women as focus point; The Violet Streets; Women Mapping the World; The streets of women, which emerged in the framework of International Women Day and it wants to give visibility to gender disparity that exists in the nomenclature of streets while creating collaboration between both communities, GeochicasOSM and Wikipedia, and the show on the roles of women historically and their socio-cultural contributions. None about this event: https://talks.2019.foss4g.org/bucharest/talk/TA7H7D/

Vector tiles are a challenge for the creative mind. In this talk we will take you along the path of making artistic styles for your vector tiles like this [Crafty map](https://apps.webmapper.nl/crafty_map/) and the [Paradise in the Polder map](https://nieneb.github.io/mycelium/). Starting from the importance of having a good and clear tile set to making your own sprites and glyphs with command line tools and software like Inkscape and Gimp. After that we show some trick to add animation with Turf.js and D3.js. Like placing random hot air balloons all over your map! Vector tiles are on the cutting edge of technology and creativity, we combine both to show you the endless possibilities that vector tiles offer! None about this event: https://talks.2019.foss4g.org/bucharest/talk/LLECPZ/

How do you find one pixel in a billion? Cloud Optimized GeoTiffs are a new standard for raster data that support file-level access via the internet. Combined with serverless cloud technologies, raster data can now be queried by client-facing applications without the need for a spatial database or specialist server software. In this talk I present how we used COGs and serverless to build a fast and scalable application to query large raster data using point and polygon geometries. As well as providing an overview of the solution architecture, I’ll explore the challenges we face with large raster data and why we chose to develop the solution using these open source standards and technologies. None about this event: https://talks.2019.foss4g.org/bucharest/talk/SQF7YK/

With PyQGIS you can write scripts and plugins to implement new features and perform automated tasks within QGIS, let's see how we can do that more efficiently thanks to some nifty tricks. Thanks to tricks like using decorators and the qgis.utils module one can improve readability and performance by simplifying a lot of code None about this event: https://talks.2019.foss4g.org/bucharest/talk/QQWQQE/

The assessment of renewable energy potentials in urban environments gained a lot of interest in the recent decades due to CO2 reduction goals by cities, national policies as well as directives by the EU. In combination with advances in data creation and processing as well as the definition of standards like CityGML, new ways of modeling urban potentials have been developed. This lead to numerous approaches estimating roof-top solar photovoltaic (PV) production. However, in recent years due to research in building materials, the façades became more attractive and feasible for PV electricity production. This paper describes results on the development of an completely FOSS-based approach to assess the electricity production potential by building façade PV. To estimate solar irradiation we followed the hemispherical viewshed approach described by Fu, 1999. Combining it with an approach to dissect walls into regular 3D point grids (1 meter spacing) we calculate the sun visibility (each hour) and the sky viewshed throughout the year. This results in direct and diffuse irradiation for every wall point. To generate the electricity potential, the irradiation values are summed up for the wall points and are fed into an economic model. This is driven by technical parameters of the installation, such as module efficiency, installation and maintenance costs, figures about payback tariffs and envisaged module lifetime. The overall result is a city-wide PV suitability and electricity production potential map of every building façade. The processing is based on a city model in the CityGML format using the 3DCityDB database and the spatial processing functionalities of PostGIS. A set of Python scripts has been developed as a central control instance. The scripts control the processing of direct and diffuse irradiation as well as clear sky irradiation relying on the external “pvlib” Python library. Furthermore, we use the scripts to manage parallel processing of queries against the database to achieve scalability and improved performance. The parallelisation is done by processing single building walls. We run a case study with approximately 7000 single wall elements to process. We identified so far one of the major bottlenecks of the approach. This are the calculations of sun visibility for every wall point per timestamp (intersection with surrounding buildings) which takes per wall several minutes to process depending on the number of points per wall. Since we implemented a parallel processing of the walls running on a 80-core dedicated server machine, the completion for an entire city of 3 million wall points uses a decent amount of time for the given size of data set. Here we describe a scalable and highly parallelised approach which can be easily implemented through standard tools and libraries. This open up now for distributed approaches using multiple database servers for even better scalability. None about this event: https://talks.2019.foss4g.org/bucharest/talk/RYCCWV/

Introduce process that the world sea surface wind data(ASCAT, WindSAT, SCATSAT) of 12.5km or 25km resolution was displayed mapbox vector tile specification. The process overview is described as being merged into 12 hours, transformed to a geostationary coordinate system, converted to a mapbox vector tile format using the opensource library, and displayed in OpenLayers. None about this event: https://talks.2019.foss4g.org/bucharest/talk/GLPF3W/

In the Czech republic and countries in the central-east European region, the market share of the open source software for geospatial is on very slowly ascending curve. We asked a question, what is the market missing, so that the acceptance of the FOSS4G software could be done in much faster way? We came into several conclusions: * Public administration does miss technical support * Both do need training courses, to pass her required set of skills as fast as possible * Current status of the FOSS4G software is still relatively diverse and the interoperability in some fields is unsatisfied, even though it's already manageable Helping the FOSS4G software to grow into public administration organisations as well as into private sector, we started to work on an ecosystem, where users will find * Training capacities * Technical support * Single point of contact for the development communities This talk is about history of building the ecosystem in the region of the Czech republic, about activities of GISMentors open training initiative and what we do for the ecosystem to grow. Several numbers will be presented about the market and it's development during last five years. None about this event: https://talks.2019.foss4g.org/bucharest/talk/JRGZAG/

The Open Green Map app has been used by map makers around the world to collect thousands of green sites over the last decade. With a new implementation, the Open Green Map has potential to truly live up to its name, and achieve a sharable, scalable, fast and easy to use application. This is what the project I will present sets out to do. Working on an open source project can sometimes make it seem like compromises around performance or user centric design are reasonable. What if you don't want to compromise in any of these 2 directions? By using an appropriate and modern tech stack, along with generative programming techniques, we hope to introduce a new approach for creating GIS applications. This talk will introduce how the new Open Green Map app works, and advantages of using DLang and Ember for a GIS app. We will also take a look at challenges that arise in relation to implementing GIS applications while having plenty of constraints around resources, and when helpful open source libraries are missing. The presentation will include an overview of the infrastructure, examples of how we generate REST APIs based on the app models and a quick look at how we efficiently display the sites on maps. None about this event: https://talks.2019.foss4g.org/bucharest/talk/VTNTG8/

National Forest Inventory is an independent survey on the state and development of forests. It is based on mathematical–statistical models. The inventory is now divided into three cycles, the first cycle was realized in 2001–2004, the second one was implemented in 2011–2015 and the third one has been carried out in 2016–2020 [1]. The second part of National Forest Inventory (NFI2) results have been processed and divided into thematic chapters including Forest Area, Growth, Mortality, Tree Species Representation, Age Structure, Forest Regeneration, Dead Trees, Game Damage, etc. I would like to aim my talk to the visualisation of the results in the form of graphs and maps. The basis for the graphical results are statistically processed data. The data are stored in a PosgreSQL database in the form of views. The views have the same structure including estimation, maximal, minimal value, standard deviation and ratio for the selected thematic chapter. The graph properties are created by the functions using R Project linked to a set of functions in PosgreSQL that make the graph in the form of raster or vector image. The set of functions in a database prepare data for maps. The data are visualized using suggested templated in QGIS. None about this event: https://talks.2019.foss4g.org/bucharest/talk/BQDXMZ/

It is widely known that China will soon be the leading player in world economy overtaking the traditional hubs of North America, Europe and South-East Asia. Its economic activities increasingly influence countries beyond its own borders and dominate global economic growth. The analysis of the shifting axis uses global trade data that countries report through the Harmonised Commodity Description and Coding System (HS-Codes). The shift of power towards China is evident when the spatial mean of some 220 globally traded commodities is calculated for which data is available. Other geo-(statistical) indicators further quantify and visualise China’s growing economic power while other economic centres cannot keep up with this pace or even decline in importance. None about this event: https://talks.2019.foss4g.org/bucharest/talk/MRTSMJ/

The talk aims to share with other participants how Map Kibera in partnership with World Bank are helping Counties in Kenya to map their projects. Producing maps to be used during participatory Budgeting forums with the public. The maps help inform what other projects citizens want implemented for them in their respective areas after knowing what’s already in place. Kindly see below http://www.mapkibera.org/blog/2018/07/17/mapping-counties-with-participatory-budgeting/ http://www.mapkibera.org/blog/2018/05/30/citizens-and-government-map-makueni-county/ None about this event: https://talks.2019.foss4g.org/bucharest/talk/CXJSDT/

Comet Time Series (CometTS) is an open-source tool that facilitates analysis and visualization of satellite imagery time series. Such analysis can enable population estimation research, change detection methods, or natural disaster monitoring. Historically, analyzing large time series of satellite imagery was achieved using proprietary GIS tools or by time-intensive methods requiring substantial geospatial expertise. CometTS requires only a web browser, Python, and dependent packages to function, obviating the GIS requirement for time series analysis and visualization. CometTS provides a partially automated approach for analyzing a time series of satellite imagery in any user defined area of interest, then calculating relevant statistical quantities (e.g., measures of central tendency and variation), and visualizing their changes over time, all in a matter of seconds. The overall focus of this talk will be on the development and application of CometTS for two analyses: 1) analyzing dynamic population changes over time in Africa and the Middle East and 2) ccreating the first independent estimate of the number of persons without power over time in Puerto Rico following Hurricane Maria. None about this event: https://talks.2019.foss4g.org/bucharest/talk/A8W7SM/

The FOSS4G community is much more than OS Software. The community, while small globally, has had, and continues to have an outsized impact on science using geospatial data. This impact starts with Open Ideas: the community fosters the free-flow exchange of ideas that lead to Open Standards for interoperability, Open Data for democratizing data access, and Open Source Software for the use and analysis of data. Science fields wishing to leverage remote sensing data has historically suffered from several challenges. Archives of remote sensing data can be large, and finding just the desired pieces of data can be time consuming, as every dataset is accessed in different ways. The data then often requires pre-processing and reformatting: reprojection, clipping, assembling time series, or even some more complex operations. Lastly, processing and analyzing these large datasets can take massive computing resources, making large scale studies difficult, if not impossible. The impact of all this on Open Science (the movement to make science more accessible on all levels) is clear - complex custom-made tools required for each dataset does not support making science more accessible. Now, the culmination of several advances in Open Standards, Open Data, and Open Source, along with cloud computing, are helping realize Open Science. And FOSS4G has been here all along, where many of these advances started as Open Ideas. None about this event: https://talks.2019.foss4g.org/bucharest/talk/TMWYYR/

Manual polygon digitization on maps by non-gis people creates possibility to encouter with topology exceptions and user mistakes like holes, slices and so on. We used solution to build blocks grid over Estonia so whole country is covered with various size of blocks based on versatile information like cadasters, roads and addresspoints. Result is massive arrays of relations between blocks identificators and areas. This solution creates one geospatial layer with more than million block identificators which can be used by multiple datalayers. If one block changes then all datalayers where this block were used, are affected. It offers us to discover areas which are not covered or areas which are overlapping each other. In presentation I will talk about why this idea came up, how we created block grid from data we had, how we choosed technology to build whole system and how we succeed in result. Technologies in presentation includes OpenLayers, React, Redux, GeoServer, PostgreSQL, PostGIS, Mapbox Vecor Tile, OGC Standards WFS-T, WMS, SLD and many more. None about this event: https://talks.2019.foss4g.org/bucharest/talk/XRWMPM/

Deltas are the most productive and economically important global ecosystems associated with some of the largest coastal marine fisheries and the majority of global wetlands. They also the most extensive coastal lowlands threatened by climate change and human activities such as agriculture, navigation, fisheries, forestry, fossil energy production and industrial urban development. Under climate- and human-induced sea level rise, sediment trapping behind dams and destruction of natural protective ecosystems, deltas are currently sinking at accelerating rates. Deltas maintenance and reconstruction depends on effective monitoring of vast and intricate areas of channels, lakes, wetlands, beaches, and islands that cannot be effectively accomplished on the ground without prohibitive expense. If ignored, disappearance of deltas will soon have devastating consequences for the livelihood of the half billion people who live in these coastal regions and lead to mass migration. I’ll present ideas & initiatives that seek to monitor deltas remotely and plug spatially-distributed data into models of hydrology, morphology, and ecosystem dynamics using remotely-sensed data from satellite missions that are complemented by ground sensor networks. None about this event: https://talks.2019.foss4g.org/bucharest/talk/ETCXMP/

<p>Most real world features can be presented as vector or raster layers. In open source world, GDAL provides a comprehensive set of tools to interact with such datasets. But vector or raster is not always a suitable description of real world features. Data from oceanography, metrology, hydrology, etc often have multiple components at each location on an irregular structured mesh. A **mesh** can a collection of vertices, edges and faces in 2D or 3D space: - vertices - XY(Z) points (in the layer's coordinate reference system) - edges - connect pairs of vertices - faces - sets of edges forming a closed shape - typically triangles or quadrilaterals (quads), rarely polygons with higher number of vertices  Mesh gives us information about the spatial structure. In addition to the mesh we have **datasets** that assign a value to every vertex. For example, ice cap thickness at particular moment of time. A single file may contain multiple datasets - typically multiple quantities (e.g. water depth, water flow) that may be varying in time. None</p> about this event: https://talks.2019.foss4g.org/bucharest/talk/XD8EZL/