uk: Комп'ютерні науки

description: PgMetadata is made for people using QGIS as their main GIS application, and PostgreSQL as their main vector data storage. The layers metadata are stored inside your PostgreSQL database, in a dedicated schema. Classical fields are supported, such as the title, description, categories, themes, links, and the spatial properties of your data. PgMetadata is not designed as a catalog application which lets you search among datasets and then download the data. It is designed to ease the use of the metadata inside QGIS, allowing to search for a data and open the corresponding layer, or to view the metadata of the already loaded PostgreSQL layers. By storing the metadata of the vector and raster tables inside the database: - QGIS can read the metadata easily by using the layer PostgreSQL connection: a dock panel shows the metadata for the active layer when the plugin detects metadata exists for this QGIS layer. - QGIS can run SQL queries: you can use the QGIS locator search bar to search for a layer, and load it easily in your project. The administrator in charge of editing the metadata will also benefit from the PostgreSQL storage: - PostgreSQL/PostGIS functions are used to automatically update some fields based on the table data (the layer extent, geometry type, feature count, projection, etc.). - The metadata is saved with your data anytime you backup the database - You do not need to share XML files across the network or install a new catalog application to manage your metadata and allow the users to get it. The plugin contains some processing algorithms to help the administrator. For example: - a script helps to create or update the needed "pgmetadata" PostgreSQL schema and tables in your database - a algorithm creates a QGIS project suitable for the metadata editing. This project uses the power of QGIS to create a rich user interface allowing to edit your metadata easily (forms, relations). Why use another interface when QGIS rocks ? More PgMetadata features will be shown during the presentation: - Modification of the template to tune the displayed metadata - Export a metadata dataset to PDF, HTML or DCAT - Publish the metadata as a DCAT catalog with Lizmap Web Client module for PgMetadata. It can then be harvested by external applications (Geonetwork, CKAN) - The data model is very close to the QGIS metadata storage and the DCAT vocabulary for compatibility. We will also show the last features such as the new support of the PostgreSQL rasters

uk: вхід без авторизації

name: PgMetadata - A QGIS plugin to store the metadata of PostgreSQL layers inside the database, and use them inside QGIS


Fabian Schindler-Strauss

type: Person

keywords: foss4g2022 generaltrack Stateofsoftware

cs: Informatika

de: Informatik

fi: tietojenkäsittelytiede

uk: Комп'ютерні науки

en: Computer Science

fr: Informatique

da: Datalogi

es: Ciencias de la Computación

nl: Informatica

cs: Technické vědy

de: Ingenieurwissenschaften

fi: tekniikka

uk: Інженерія

en: Engineering Sciences

fr: Ingénierie

da: Ingeniørvidenskab

es: Ingeniería

nl: Engineering

description: pygeofilter (github.com/geopython/pygeofilter/) is a library to support the integration of geospatial filters. It is split into frontend language parsers (CQL 1 + 2 text/JSON, JFE, FES) , a common Abstract Syntax Tree (AST) representation and several backends (database systems) where the parsed filters can be integrated into queries. ## Parsers Currently pygeofilter supports CQL 1, CQL 2 in both text and JSON encoding, OGC filter encoding specification (FES) and JSON filter expressions (JFE) as input languages. Additionally pygeofilter provides utilities to help create parsers for new filter languages. The filters are parsed to an AST representation, which is a common denominator across all filter capabilities including logical and arithmetic operators, geospatial comparisons, temporal filters and property lookups. An AST can also be easily created via the API, if necessary. ## Backends pygeofilter provides several backends and helpers to roll your own. Built-in backends are for Django, SQLAlchemy, raw SQL, (Geo)Pandas dataframes, and native Python lists of dicts or objects. ## Usage pygeofilter is used in several applications, such as PyCSW (pycsw.org/), EOxServer (github.com/EOxServer/eoxserver/) and ogc-api-fast-features (github.com/microsoft/ogc-api-fast-features/)

TIB AV-Portal

type: Service

type: WebContent

type: MediaObject

@language: en

cs: přihlášení není vyžadováno

de: keine Anmeldung erforderlich

uk: вхід без авторизації

en: no login required

nl: geen login vereist

name: pygeofilter: geospatial filtering made easy

type: Organization

name: Open Source Geospatial Foundation (OSGeo)

cs: Video

de: Video

fi: Video

uk: Відео

en: Video

fr: Vidéo

da: Video

nl: Video

es: Video


uk: Комп'ютерні науки

description: Rockfall Quantitative Risk Assessment at a medium-large scale based on FOSS4G tools. An example of applications in the North-Western Alps Rockfall risk analysis and mitigation activities are key points in land management in mountain areas and along coastal cliffs, aimed at the protection of population, structures, infrastructures and involved economic activities such as viability, industry and tourism. Rockfall is a complex landslide phenomenon, widespread over large areas and characterised by high variability. As a function of the amount of available data to describe such variability, the risk analysis can be carried out at different levels of detail, i.e. at different reference scales, each one characterised by specific objectives, procedures, and input data (Fell et al, 2008). At the detailed scale (＞ 1: 5000), in order to design risk mitigation works, it is necessary to analyse localized rockfall phenomena through specific methodologies requiring a careful identification of danger scenarios, a statistical description of the parameters, and sophisticated probabilistic calculation tools. At the medium-large scale (1: 5000 - 1: 25000), on the contrary, due to the difficulty in finding detailed information over larger slope portions, it is possible to analyse widespread instability sources based on simplified mechanical considerations and several spatial approximations. Such large scale analyses can be used as a management tool for territorial planning and can be easily implemented in GIS software. This work presents a medium-large scale Rockfall Quantitative Risk Assessment procedure fully developed within the QGIS environment. The procedure is based on the IMIRILAND methodology (Castelli and Scavia, 2008), which allows to obtain risk maps through integrated and consequential phases and simple raster calculations. The main steps of IMIRILAND methodology are: • hazard analysis, aimed at defining, for a given rockfall scenario, the potentially involved area, the intensity of the damaging phenomenon and the temporal probability of occurrence; • identification of the elements at risk and definition of their value and their exposure with reference to physical, social, environmental and economic considerations; • analysis of the vulnerability of the elements at risk, i.e. the degree of loss of the element as a consequence of the impact with the falling block; • calculation of the risk, combining the hazard with value, exposure and vulnerability of the elements at risk. The IMIRILAND QRA procedure was applied to the mountain site of Sorba Valley (VC), North-Western Alps. The site involves an area of about 10 km2 with altitudes ranging from 750 m up to 2035 m a.s.l. The site is prone to rockfall events, which historically involved some hamlets and some sections of the valley main road. However, very little information on such events is available, and no indication can be obtained in terms of rockfall recurrence and involved volumes. Due to this, it was not possible to take into account temporal aspects and relative (spatial) risk maps were produced in this work. All the analysis was carried out using open data available as web services and datasets from the Regione Piemonte GeoPortal: • DTM with 5 m x 5 m raster resolution – GeoPortale Piemonte; • Orthophoto AGEA 2018 – GeoPortale Piemonte; • Piemonte Land Cover BDTRE (Base Dati Territoriale di Riferimento degli Enti) – GeoPortale Piemonte; • vehicular mobility TGM (Traffico Giornaliero Medio) – GeoPortale Piemonte. Three rockfall design scenarios were identified regarding homogeneous rockfall source areas associated with different design block volumes. Each scenario included more than 3600 source points, extracted through the analysis of the DTM (slope and aspect) and the observation of the orthophoto for the identification of rocky outcrop zones. For each scenario, a quick estimation of a time-independent hazard was performed using the QGIS QPROTO plugin (Castelli et al, 2021). The plugin is based on the Cone Method (Jaboyedoff and Labiouse, 2011) and runs a visibility analysis through the r.viewshed GRASS GIS module, combined with simplified topographic, geomorphological and mechanical considerations. The result of the analysis is a series of raster maps with the distribution of computed values of velocity, energy, and relative spatial hazard. The following step of the IMIRILAND procedure is the analysis of the damage, based on the collection of information on the exposed elements. To this aim: • the elements at risk were classified according to various Land Cover categories from BDTRE, associated with relative hierarchical values. Physical and social values were taken into account for each element. Physical value is mainly linked with the type of element and with the reconstruction costs while social value is linked to the presence of persons and the social utility of the asset; • the physical exposure of the elements at risk was defined for each hazard scenario with reference to the computed runout area. The social exposure was defined taking into account the time spent by people inside buildings or on the roads. • the physical vulnerability of the elements at risk was defined on the basis of the intensity of the phenomenon in terms of rockfall energy and the type of element. The social vulnerability is the same as the physical one inside buildings and is 100% outside buildings. Physical and social damage maps were then obtained for each hazard scenario through the product of the value, the exposure and the vulnerability of the elements located in the involved area. Due to the lack of information on the temporal probability of occurrence of the scenarios, damage maps correspond to relative, time-independent, risk maps. The results show that the highest risk is concentrated in the inhabited areas and some portions of the valley road, according to the few historical information available on the site. The QPROTO plugin is available at the GIT repository of FAUNALIA (gitlab.com/faunalia/QPROTO) and can be easily used by professionals, public administrators, managers of roads, railways or infrastructures for land planning purposes or for preliminary analyses aimed at defining the most critical zone of a wide area, where resources and more in-depth analyses can be focused for mitigation purposes.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: OpenDroneMap is an ecosystem of free and open source software to collect, process, analyze and display aerial data. In this talk we will present an exciting overview of what's new in the ecosystem, where the project is headed and how you can benefit from using it. In particular, will first provide a brief overview of the ecosystem, what the tools are and how you can start making maps in minutes. A short introduction to the "magic" of the processing pipeline will be presented. We will then touch on state-of-the-art advancements in photogrammetry technology within ODM, how we benefit from a global team of researchers and how that has allowed us to match (and often times exceed) proprietary software results. After a presentation of the technological advancements, we will discuss the importance of people, or how prioritizing people over code and investing into the community has affected both participation and adoption.

uk: вхід без авторизації

name: Aerial Images to Maps: Technological Advancements with OpenDroneMap


Web Mapping with Global Map Projections

uk: Комп'ютерні науки

description: Web Mapping as a technology and a method is now twenty years old. Within the OSGeo Community, it has been fostered by projects such as OpenLayers and Leaflet. They evolved tightly intertwined with the framework imposed by free data providers, initially around commercial efforts like Google and later OpenStreetMap. While useful in providing an easy entry to web mapping, and convenient background layers, these data providers also triggered a regression towards centuries-old cartography techniques, in particular the Mercator projection. This has become a major hurdle to web mapping, particularly concerning global data. The Mercator map projection was created to aid sea faring in the XVI century and was rendered useless with the advent of global positioning systems. Its use in cartography may still be acceptable at large scales, neighbourhood or city level, but at smaller scales it imposes severe distortion to distances and areas. For global datasets in particular, the Mercator projection is unusable, for it cannot represent the full surface of the planet. Web mapping developers may work around this framework with libraries such as D3 or proj4js, and by setting up bespoke base layer services. But in doing so they face a different problem: the deep dependence on the CRS index created by the European Petroleum Survey Group (EPSG). Primarily concerned with the survey and extraction of fossil fuels, the EPSG leans heavily on local or regional CRSs, largely ignoring global CRSs. Hardly any of the more than 100 map projections and coordinate systems developed since the beginning of the XX century feature in the EPSG index. Landmark projections such as the Eckert series, the Homolosine, Eumorphic, Dymaxion or the Snyder series were never included in the EPSG index. Not even the classical Mollweide projection (one of the turning points towards modern cartography) appears in the EPSG index. With a FOSS4G stapple such as MapServer, this forces the leveraging of map (re-)projections to the client, which is not always possible. Web mapping with global data thus remains a technical challenge with FOSS4G. This address reviews several techniques and work-arounds making global web mapping possible with familiar FOSS4G technologies. Starting with the appropriate configuration of CRS managing software, going through the set-up of data servers and finally providing examples with web mapping clients.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: PostgreSQL is the most advanced opensource RDBMS. As GIS folks, you most probably use it in combination with PostGIS, its Geospatial plugin. When dealing with Geospatial data, we usually focus on geometries. But most of feature attributes are text data. Of course, filtering on these text data with standard SQL capabilities is a day-to-day operation for database users. But PostgreSQL provides much more capabilities when it comes down to text data management. In this presentation, we will go through a few of them. After a quick look at standard text functions in PostgreSQL, we will discover the lesser known fuzzy matching modules : - `pg_trgm` extension allows for string searches using trigraphs to determine a similarity rank between text items - `fuzzystrmatch` extension provides fuzzy matching functions like soundex, Levenshtein, metaphone Then, we will explore *Full Text Search ( FTS )* PostgreSQL capabilities. Last but not least, we will peek inside PostgreSQL collation concept, which has nothing to do with your lunch. Collations are a powerful feature in PostgreSQL allowing to adapt the way you deal with text data according to the localization. Like trying to answer this - apparently - obvious question : is '12' before or after '2' ? And, because we can, display all of this on a map :-)

uk: вхід без авторизації

name: Manipulating text with PostgreSQL - lesser known PG jewels


keywords: foss4g2022 generaltrack Education

uk: Комп'ютерні науки

description: Open-source solutions in geoinformatics have gradually come into the focus of attention over the past decades, becoming of the most well-promising opportunities in tertiary education. It is indubitable that students have to develop their skills to find, apply and contribute to the existing open-source opportunities, besides developing skills regarding coding and programming logic.  At the Budapest University of Technology and Economics, a complex system has been developed to support students on this matter. This system is fully based on open-source software and free cloud services. Consequently, all the teaching materials have creative common licenses supported by the use of open source software.  The main entry point of the educational materials is Moodle, considered as one of the most popular learning management systems. The majority of the source codes and explanation texts/notes used for teaching are published in Jupyter notebooks, stored on personalized GitHub pages. For opening and testing the Jupyter notebooks, the students can use Google Colab.  Another challenge worth mentioning is the continuous assessment evaluation format. Moodle supports the creation of tests based upon a wide variety of question types (e.g. multiple choice, true/false, drag and drop markers, etc), which are stored in a question bank. The test is generated by randomly selecting a given number of questions; therefore, taking the test a couple of times is highly recommended. As stated by many, this way of self-studying is popular among students these days and efficient in achieving remarkable progress.  Our presentation shares either the developed system or the gained experience over the recent years.

uk: вхід без авторизації

name: A Moodle based complex system to teaching spatial data processing


uk: Комп'ютерні науки

description: Update on the status of OGC API standards and draft specifications enabling client-driven execution of processing workflows, supporting on-demand and ad-hoc selection of data and algorithms. Overview of the capabilities enabled by OGC API - Tiles, OGC API - Coverages and Processes – Part 3: Workflows and Chaining. Demonstration of both a server and a client implementing these specifications. The Workflows and Chaining draft extension specification to OGC API – Processes enables ad-hoc execution of workflows integrating processes and data available from one or more OGC API instances. The specification allows triggering processing as a result of requesting results for a specific area and resolution of interest, which provides a simple mechanism to chain geospatial data inputs and outputs. By referring to a collection of geospatial data irrespective of a particular area, resolution or date/time of interest, workflows can be defined in a generic, re-usable manner, and processing can be performed on-demand rather than (or in addition to) as a batch execution. Such on-demand processing has the advantage of optimizing the use of computing resources and speeding up the availability of the latest available data, such as for continuously captured Earth Observation satellite imagery. The initial version of the Workflows and Chaining specification was a result of a GeoConnections 2020-2021 project funded by Natural Resources Canada, which also supported the development of a unified OGC API driver in GDAL allowing to directly visualize the results of such workflows in QGIS. OGC API – Tiles is the specification succeeding to WMTS in the OGC API family, leveraging the concept of 2D Tile Matrix Sets. In addition to providing tiles of maps or imagery, Tiles can also be used to distribute raw data tiles, including coverage and vector tiles. Using tiles to deliver results and trigger execution of processing workflows can facilitate caching while allowing to efficiently select an area and resolution of interest. OGC API – Coverages is the specification suceeding to WCS in the OGC API family, and provides a simple mechanism to request an optionally down-sampled subset of a coverage. Specific fields (e.g. imagery band) can be selected as needed. The Coverages specification can also be used to request results while triggering execution of a workflow.

uk: вхід без авторизації

name: Update on Modular OGC API Workflows specifications


uk: Комп'ютерні науки

description: DistrictBuilder (districtbuilder.org) is a web-based, open-source tool for collaborative political boundary redistricting or redistribution. In order to support creating legally valid districts, DistrictBuilder allows advocates and legislators to define districts using geometries as small as a single census block, which are very numerous – a medium-sized state will have hundreds of thousands of them. Users can create districts from any combination of geometries, and we need to be able to generate statistics and dissolve them into district geometries in near real-time. By reformatting our data as TopoJSON, a file format and Node.js library for working with topological data, we are able to dissolve over half a million census blocks into legislative districts in only a few seconds! I’ll discuss how we use TopoJSON in DistrictBuilder; the issues we encountered when using it at scale in production and how we were able to overcome them; and the other tools we considered instead of TopoJSON and how they compared in terms of performance. I’ll also go over our strategy for displaying and calculating metrics in real-time in the browser, using typed arrays and web-workers in combination with Mapbox vector tiles to do real-time aggregation of statistics from hundreds of thousands of features.

uk: вхід без авторизації

name: DistrictBuilder, or how TopoJSON was the cause of and solution to all of our problems


Surveying amenities for OSM at scale

uk: Комп'ютерні науки

description: OpenStreetMap editing transitions to mobile devices. There are few editing apps, and the best ones are thematical. This year I've published "Every Door": an app specifically designed to collect hundreds of shops and amenities. I've made it with the experience of mapping in OSM, making a Telegram bot of a similar purpose, and studying geospatial UX design. I've surveyed half a thousand amenities with the bot, and even more — with this new app. In this talk we'll briefly touch on the app itself and the OSM tagging model. The main attraction would be map UX design: why you should remove the most interactivity from your maps. These are hard to use even on desktop, and a small screen provides an even bigger challenge. Can we get rid of them altogether? Let's see how working with maps can be made efficient, and how the ideas behind this app can make geodata collection apps better.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: Come have a look under the covers at the data structures that enable geospatial and multi-dimensional indexing and search at massive scale in Apache Lucene and OpenSearch. This talk will cover not only the indexing structures considered and ultimately implemented in the Apache Lucene Open Source Project but the exceptional performance improvements and centimeter spatial accuracy obtained in the latest release. As a bonus, this talk will cover new and upcoming Spatial Analysis Aggregations and Processing available in the OpenSearch Open Source project. From tessellation to multidimension encoding and block KD trees this talk will cover the algorithms and data structures written and committed to the following open source projects: Apache Lucene (specifically the release of BKD based geo indexing issues.apache.org/jira/browse/LUCENE-8396) Performance benchmarks for Lucene Spatial Indexing: home.apache.org/~mikemccand/geobench.html Finally, we will discuss the future of the project including existing and evolving support for custom coordinate reference systems and projections, spatial regression modeling and statistics, and spatial visualizations with OpenSearch Dashboards.

uk: вхід без авторизації

name: Geospatial Indexing with Apache Lucene and OpenSearch


uk: Комп'ютерні науки

description: DroneDB is free and open source software for geospatial data storage. It provides a novel approach to store point clouds, textured models, aerial images, orthophotos and elevation models via a dynamic filesystem index. In this talk we will present DroneDB's storage approach and how you can start using it right away. We will discuss the project's architecture and roadmap. We will also perform a showcase of the project and demonstrate its most effective use cases. We will cover how DroneDB's dynamic index can be published on the web using Registry, a cross-platform open source application which provides both a friendly user interface and a RESTful API. This enables users and GIS developers alike to access and manage the underlying data. We will showcase the ddb client, a command-line interface that enables power users to manage the index and can be used to sync, share and download remote datasets in a manner inspired by git workflows. We will show how WebODM and Registry can integrate together to create a powerful and versatile workflow for 3D reconstruction using a full opensource stack.

uk: вхід без авторизації

name: Effortless Aerial Data Management and Sharing: The DroneDB Ecosystem


uk: Комп'ютерні науки

description: It started as a way to help us publish geospatial data. It quickly morphed to something quite different. You can call it scope creep. And despite this term being close to a swear word in ICT, it turned out to be very good thing. And that's because while still serving its main purpose, which is to provide an out-of-the-box web based mapping app with all the trimmings (navigation, measure, layer control and search tools), EVRYMAP also: - Provides client-side editing tools - Provides a modular design that allows you to implement custom business logic by simply writing your own apis. EVRYMAP will consume these APIs automatically by defining them in configuration as 'modules' - Implements 1-n relationships between your spatial data and other related data. Which may come from the same or external databases - Can be run as standalone or within an iframe to spatially enable third party applications (and provides the communication mechanism) Using EVRYMAP at the core, we have also deployed a few systems in production environments as commercial apps, namely: -Landify, a mini-cadastre for organizations with a real-estate portfolio. It allows users to easily review, catalogue, and manage real estate data (land parcels and buildings). -MapTheYA, a map-based information system for the management of water networks including topology checks. -Building permits/Expropriations Management Examples of not "map-first" systems, meaning that while the bulk of their functionality are text/form based (applying for electronic copies of documents) they also include embedded maps to improve user experience. This presentation will provide a brief introduction to EVRYMAP, the way it works, how you can configure and extend its functionality and what we plan for the future. And being the new kid on the block, ask the community for input and feedback!

uk: вхід без авторизації

name: EVRYMAP - An extensible web mapping framework based on Angular, NodeJS, Leaflet and Mapserver.


MDAL: mesh data in QGIS

uk: Комп'ютерні науки

description: Mesh Abstraction Library (MDAL) has become an integral part of QGIS over the recent years. MDAL is used in QGIS to parse meteorological and hydrological data. MDAL is an open source library and recently has joined the OSGeo family as a Community project. MDAL data can be 1-dimensional, 2D or stacked 3D data. QGIS has been extended to render all those types of data in 2D and 3D map canvases. Once data are loaded in QGIS, users can easily style and explore temporal dimension of the data using QGIS generic tool. Additional plugins have been developed to leverage on mesh data in QGIS to slice and dice the mesh data. In addition to visualising the data, new tools have been developed to directly edit the unstructured mesh data in QGIS. Users can edit geometries and values of the faces and vertices of the mesh data. The built-in validation tools for mesh editing, ensure the resulting mesh is topologically correct during and after mesh editing operations.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: Tables are a great way to store data and this format is often used to make data available for the public on websites. While these tables technically meet their intended goal of sharing data, they do not make it easy to understand the spatial and temporal patterns in the data they contain. In this talk, I will demonstrate how an automated toolchain of web scraping and text processing in R, and interactive visualization in Leaflet is automated with GitHub Actions and applied to aid data interpretation and generate new insights from a daily-updated online tabular dataset using a case study of the University of California Davis’ Potential Worksite Exposure Reporting data for COVID-19. In the United States, California Assembly Bill 685 (AB685) requires employers in the state of California to notify employees of potential worksite exposures to COVID-19 to the geographic scale of individual buildings. The University of California Davis meets this requirement by listing any potential exposures on a website, giving the date reported, the dates of the potential exposure, and the building name as reported by the employee. To make a map from this data, the dates and building names had to be standardized and joined to a vector layer of campus buildings before they can be added to an interactive Leaflet map. Because the data updates daily, the whole process needed to be automated so no one had to run the scripts every day to update the map. The result is a map that gives uses a much clearer understanding of the spatial and temporal distribution of potential exposures to COVID-19 on campus.

uk: вхід без авторизації

name: Automating Generating a Web Map from Online Tabular Data: UC Davis Potential Worksite Exposure Interactive Web Map


uk: Комп'ютерні науки

description: Although integration of GRASS GIS with Python has been well supported for several years, using GRASS with computational notebooks such as Jupyter Notebooks was inconvenient up until recently. Computational notebooks allow users to share live code with in-line visualizations and narrative text, making them a powerful interactive teaching and collaboration tool for geospatial analytics. In this talk, we’ll introduce a new GRASS GIS package, grass.jupyter, that enhances the existing GRASS Python API to allow Jupyter Notebook users to easily manage GRASS data, visualize data including spatio-temporal datasets and 3D visualizations, and explore vector attributes with Pandas. We’ll demonstrate how to create interactive maps through integration with folium, a leaflet library for Python, and we’ll look at an example use case: using notebooks to teach an advanced geospatial modeling course for graduate students at NC State University. Grass.jupyter is still under active development but is available experimentally in GRASS version 8.0 and officially with GRASS version 8.2.

uk: вхід без авторизації

name: Using GRASS GIS in Jupyter Notebooks: An Introduction to grass.jupyter


uk: Комп'ютерні науки

description: Teaching GIS Through Geospatially Aware Agent-Based Modeling. AgentScriptGIS is a web-based platform that provides a geospatially aware agent-based modeling programming environment. The goal is to enable programmers to generate geo-agent-based models with minimal barriers to entry. The platform provides a programming environment that includes an agent-based modeling library (agentscript.org), a geo-aware programming context, and a map display (leafletjs.com). The platform was designed to reduce the overhead needed for programmers to begin modeling. We want to empower modelers who come from a wide array of backgrounds with the ability to write and animate geospatial models with minimal time and effort. The intended audience of this platform are users who want to explore geospatial and agent-based modeling but may have little to no experience interacting with these types of models. We use agent-based modeling as a basis for our platform since it is a popular way to teach programming and can model a wide spectrum of problems. Popularized by NetLogo and StarLogo, agent-based modeling is used in a variety of educational contexts from elementary school studies to graduate level research. To maximize deployability, our agent-based modeling library AgentScript was written in JavaScript and built to be leveraged by the web browser. GIS software is typically professional in nature and leans on being sophisticated and precise, but is often overburdened with complexity. The hobbyist GIS programmer faces a steep learning curve when starting, including choosing appropriate tools and information sources, deciding on data formats and understanding projections. Our platform intends on removing these burdens on the user by trading versatility for simplicity and ease of use. We are preparing our platform to be used initially in academia, but can see it being applied in a variety of settings. AgentScriptGIS focuses on facilitating new ways to engage students, teachers and modelers with geospatial issues. This platform provides a low barrier of entry to users and promotes the modeling of local and regional problems by leveraging real-world data and empowering low skill users with the ability to model various geospatial phenomena.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: QGIS is a freely downloadable open source GIS software suite that contains a desktop option, mobile, and web component. QGIS is free to download and use, it is released with a GPL v3 license which is a non commercial license allowing users to download and use it without concerns compared to other commercial GIS software. Up to QGIS version 3.12 there was no core support for temporal data, users were required to install a plugin called TimeManager in order to visualize temporal data inside QGIS. Through a collaboration between the Canadadian Government, Kartoza and North Road, efforts were made to add core support for temporal data inside QGIS. As a result the QGIS version 3.14 was released with a Temporal Controller feature which was now responsible for handling all the temporal layers inside QGIS. The initial role out of the Temporal Controller contained support for raster, vector and WMS-T layer providers. This session will explore how to use the QGIS Temporal Controller to do animation and visualization of the WMS-T layers, this will include how to setup a standard WMS server that will be serving time based layers. In the session we will also learn about the Temporal Controller API, how to use it through QGIS python bindings and create a simple QGIS plugin that will show the API in action.

uk: вхід без авторизації

name: QGIS Temporal Controller with WMS-T layers


uk: Комп'ютерні науки

description: MapComponents is a new component framework to quickly and easily build dynamic geospatial web apps. It includes React front-end components for all kinds of projects, from small apps with a narrow and specific focus up to complex geospatial suites for the web. Server-side components are also planned to aid the development of flexible backend services. MapComponents - is a modular framework to create tailored geospatial web apps built upon modern webbrowser technology - can be used to visualise and analyse geo data - can be used for desktop and mobile applications (online and offline; progressive web apps (PWA)) - provides independent components which can be combined into full-fledged geospatial web applications (e.g. dashboards, WebGIS, ...) - provides a catalog of components and example applications - uses a flexible core which theoretically supports any kind of mapping library (currently supported are MapLibre, Mapbox GL JS and OpenLayers) - is easily integrated into existing stacks - makes it easy to rapidly design and deploy a map centric web app MapComponents is developed by WhereGroup GmbH and is available under the MIT license. mapcomponents.org/ We will present the project, with its current state and goals, and will show practical examples.

uk: вхід без авторизації

name: MapComponents, a new component framework for developing web map applications


State of GRASS GIS 2022

uk: Комп'ютерні науки

description: The new GRASS GIS version 8.2 is a special edition including all new features developed during Google Summer of Code 2021. One of the enhancements is the parallelization of several raster modules by means of OpenMP, an implementation of multithreading to speed up massive data processing. Another exciting new feature is much improved, the Jupyter notebook support. Here, a new python package (grass.jupyter) is available which allows to interactively visualise maps and time series given the integration with folium (github.com/python-visualization/folium). The graphical user interface in version 8.0 introduced faster and more streamlined startup without a need for a welcome screen. For even more convenience, version 8.2 adds an experimental single window layout with familiar look-and-feel. Related to raster data, a new metadata class called semantic labels can now be added to raster maps. Examples of semantic labels are aerial or satellite spectral bands, dataset names in remote sensing products (ndvi, evi, lst, etc), or any custom names. At community level, we have developed a student grant program and, thanks to the move to GitHub, we have welcomed numerous new contributors.

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uk: Комп'ютерні науки

description: The presentation aims to provide attendees with enough information to master GeoServer styling documents and most of GeoServer extensions to generate appealing, informative, readable maps that can be quickly rendered on screen. Examples will be provided from GeoSolutions training material (docs.geoserver.geo-solutions.it/edu/en/), as well as from the OSM data directory (github.com/geosolutions-it/osm-styles) we shared with the community. Several topics will be covered, providing examples in CSS and SLD, including: - Mastering common symbolization, filtering, multi-scale styling. - Using GeoServer extensions to build common hatch patterns, line styling beyond the basics, cased lines, controlling symbols along a line and the way they repeat. - Leveraging TTF symbol fonts and SVGs to generate good looking point thematic maps. - Using the full power of GeoServer label lay-outing tools to build pleasant, informative maps on both point, polygon and line layers, including adding road plates around labels, leverage the labeling subsystem conflict resolution engine to avoid overlaps in stand alone point symbology. - Dynamically transform data during rendering to get more explicative maps without the need to pre-process a large amount of views. - Generating styles with external tools.

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name: Creating Maps in GeoServer using CSS and SLD


uk: Комп'ютерні науки

description: MobiDataLab is the EU-funded lab for prototyping new mobility data sharing solutions. Our aim is to foster data sharing in the transport sector, providing mobility organising authorities with recommendations on how to improve the value of their data, contributing to the development of open tools in the cloud, and organising hackathons aiming to find innovative solutions to concrete mobility problems. The project consists of following main pillars: 1. Open Knowledge Base ... a portal about open mobility data which provides informations about about practices and solutions related to legal and regulatory (s.a. licenses), governance, data privacy, technical standards (for data interoperability and accessibility), and challenges for actors in the mobility domain. 2. Transport Cloud ... a cloud-based prototype platform for sharing mobility data. It facilitate users by several tool components to find, use and interact with mobility data in an open, interoperable and privacy-preserving way. 3. Living and Virtual Labs ... are the environments for the project to interact with the reference group (mobility data providers and users), b2b and endusers (s.a. data innovators, solution providers and further stakeholders in the mobility domain) to get feedback on challenges and missing pieces in the mobility data and services assets. A set of mobility use-cases, set-up by the project stakeholders and the reference group will help to trigger practical execution, innovation, and further ideas within the labs. 4. Socio-economic impact ... identifies the the current best practices in data sharing, analyses the market potential and elaborates new data sharing services and business models on that. With the heterogeneous experts project group, we are facing the challenge of mobility data sharing from different perspectives - research, privacy, data, mobility solutions, open data, services, ... . A close work with a large reference group (which is representing several mobility data providers - e.g. from the public and private sector and actors, s.a. start-up communities) and the implementation of virtual and living labs allows to get early real world feedback and help to identify challenges in interoperability and missing standards as well as findable and available data, conflicting licenses, accessibility and usability of data and services. Since the project started in February 2022, we will present the mid-term achievments and provide an outlook on the second part of the project. Further information on the project is available via mobidatalab.eu MobiDataLab is funded by the EU under the H2020 Research and Innovation Programme (grant agreement No 101006879).

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name: MobiDataLab - Labs for prototyping future mobility data sharing solutions


uk: Комп'ютерні науки

description: Over the last 35 years, the IPLA has collected data on soils, both soil samples and cartographic data, to create a database (physical and digital) that represents knowledge for all stakeholders, public and private, of the composition and state of soils. Piedmontese. in the last 25 years the SIP (Pedological Information System) has been changed several times, to meet the new needs in terms of data collection but above all to update it to the new FOSS technologies. in fact, in the last 5 years we have gone from non-connected proprietary systems (DB FoxPro and Esri geoDB personal) to a single integrated system with FOSS tools: PostgreSQL / PostGIS and QGIS. An information system has therefore been created that allows technicians on the one hand to be able to collect the field data by inserting them, with a web interface in the database, and to be able to see in real time, the cartographic themes in QGIS, based on the data.just inserted and taking advantage of the geographical component of the database. Also the implementation of the survey points can be done, using in this case internal functions of the DB, both in alphanumeric way and in QGIS in a geographic way, with real-time modification of the points based on the coordinates entered by one of the two tools. And new implementations for field survey (QFiled) are under development, for the survey of the points and their visualization on the DB in real time. The pedological observations are characterized by different levels of information among which more than 5000 soil profiles are the basic and fundamental data, subdivided into field data (descriptions and photos) and analytical data (physical-chemical determinations in laboratory). The elaboration of these data provides the main structure of the Pedological Information System, that is the description of more than 1200 Soil Types, used to build up the characterization of 7000 Geographical Units.

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name: Pedological Information System of Piedmont Region in Italy


keywords: foss4g2022 generaltrack OpenData

uk: Комп'ютерні науки

description: Geofolio is a project aiming to make environmental data understandable and accessible for everyone. Geodata is notoriously difficult to use for non-experts. It often gets hidden away in confusing data portals, and at least some GIS expertise is a common prerequisite to find and download data, extract your area of interest and to do some simple analysis. Geofolio lowers these adoption thresholds by letting users draw an area of interest, and then a factsheet with text summaries, maps, and charts is generated automatically from various open access geodatasets. The factsheets contain information on various environmental themes such as topography, land use, hydrology, climate, and agriculture. Users can download the source data, thereby providing an easy step up for further investigation and learning using open source GIS applications such as QGIS. Geofolio makes extensive use of open source software for geospatial applications. The front-end and factsheets use the Leaflet mapping library, and the back-end and processing framework depends on GDAL and Shapely. Geodata is stored for analysis and visualization using PostGIS and Cloud-Optimized GeoTIFF files. The actual data processing takes place "on-the-fly" using GDAL-enabled AWS Lambda functions.

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name: Geofolio: Making Environmental Data Understandable and Accessible for Everyone


OSGeoLive project report

uk: Комп'ютерні науки

description: OSGeoLive is a self-contained bootable DVD, USB thumb drive or Virtual Machine based on Lubuntu, that allows you to try a wide variety of open source geospatial software without installing anything. It is composed entirely of free software, allowing it to be freely distributed, duplicated and passed around. It provides pre-configured applications for a range of geospatial use cases, including storage, publishing, viewing, analysis and manipulation of data. It also contains sample datasets and documentation. OSGeoLive is an OSGeo project used in several workshops at FOSS4Gs around the world. The OSGeoLive project has consistently and sustainably been attracting contributions from ~ 50 projects for over a decade. Why has it been successful? What has attracted hundreds of diverse people to contribute to this project? How are technology changes affecting OSGeoLive, and by extension, the greater OSGeo ecosystem? Where is OSGeoLive heading and what are the challenges and opportunities for the future? How is the project steering committee operating? In this presentation we will cover current roadmap, opportunities and challenges, and why people are using OSGeoLive.

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name: Open Source Geospatial Foundation (OSGeo)


Usage and contribution of FOSS at GISCO

uk: Комп'ютерні науки

description: GISCO, the ‘Geographical Information System of the COmmission’, is a permanent service of Eurostat that fulfils the requirements of both Eurostat and the European Commission for geographic information and related services at European Union (EU), Member State and regional levels. These services are also provided to European citizens at large. GISCO’s goal is to promote and stimulate the use of geographic information within the European Statistical System and the European Commission. One of the main lessons learned over the last years is not only to provide ‘conventional’ GIS datasets, but add a variety of distribution channels like Application Programming Interfaces (APIs), Linked Open Data (LOD) plus Human Friendly Interfaces on top. API’s for example simplify software development and innovation by enabling applications to exchange data and functionality easily and securely into a digital ecosystem. Additionally, the implementation of API’s contributes to: a) an open government approach to modernise public administration b) a modernised use of the European Interoperability framework or c) the application of the Once Only Principle. The talk will describe some of GISCOs API’s supporting European Institutions in their daily work as well as the public. For that, we are using FOSS tools in production environments. Besides, GISCO team members develop or contribute to a wide variety of software tools (e.g. eurostat-map.js, gridviz, IMAGE tool, diff and generalization tool) which will be presented for further use by the FOSS4G community.

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uk: Комп'ютерні науки

description: A demonstration of how to deploy a mobile data capture platform in an enterprise setting. In this example an environmental survey has been developed for a large organisation with a team of surveyors. Consideration is made to authentication, version control and synchronisation to an enterprise spatial database for wider consumption. QGIS is used to define base mapping, context layers and the data capture layers for the mobile application. In this project it is demonstrated how QGIS can be used to define survey forms to reduce input error. In this case a tree survey layer has been defined that adheres to the Individual Tree Standard from the UK’s Forest Research, the Open University and Treework Environmental Practice. The QGIS project is then deployed to a dockerised Mergin service. Authenticated access is then granted to users of Lutra Consulting’s Input Android application. Field collected data can be created and synchronised with the Mergin service. Version control & merging allows multiple users to make asynchronous changes with the ability to rollback if required. The Mergin service internal database is synchronised with an enterprise PostGIS database to allow other users to access and edit data via desktop. Media captured in the survey such as images is extracted through Mergin’s API and made available together with the survey data through a web GIS interface.

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name: From the field to the desk - end to end mobile data capture in an enterprise environment.


uk: Комп'ютерні науки

description: Aside from many new features, GRASS GIS 8 brings an improved graphical user interface focused on better user experience. Based on a broad community discussion involving several surveys and test sessions, we developed a new startup mechanism helping the users understand the data hierarchy and guiding them in their first steps. In addition, our surveys helped to identify a number of opportunities for improvements, including a need for a Single-Window mode that could fully replace the traditional Multi-Window GUI that has been in GRASS since the first GUI version in 1999. Therefore, during the GSoC 2021 project, the first steps towards the Single-Window GUI were established, eventually leading to the friedlier GRASS GUI in version 8.2. Come and listen to the presentation describing how a community-driven approach helped to steer the development direction of the GRASS graphical user interface to satisfy both GIS beginners and advanced users. You can also look forward to the brand-new screenshots of the GUI in version 8.2 that might eventually inspire you to try GRASS on your own.

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name: Redesigning GRASS GIS graphical user interface in a community-driven way


uk: Комп'ютерні науки

description: The use of remote sensing data operating in different observation domains is an undeniable asset for the realization of quality land cover products. Indeed, satellites allow to cover large areas of interest in a regular way with a durable quality. Satellite data can be of different but often complementary natures, which makes it possible to broaden the possible fields of application (water management, snow cover, crop yield, urbanization, etc.). In addition to these new data, there are recent technological developments (or old but now usable due to the evolution of computing capacities, such as the use of neural networks), and means of service provision and dissemination that allow these applications to be carried out over a longer period of time (long time series that are computed more rapidly) and in a larger space at different scales, sometimes simultaneously (stationary, local, national, continental, global scale). iota2, developed by CESBIO and CNES with the support of CS GROUP, is a response to the growing demand for the creation of an Open Source tool, allowing the production of land cover maps at a national scale that is sufficiently generic to be adapted to the different objectives of users. In addition, this project ensures the production of an annual land use map of metropolitan France [REF doi.org/10.3390/rs9010095], with a satisfactory level of quality, thus proving its operational capacities. iota2 integrates several families of supervised algorithms used for the production of land use maps. Supervised algorithms (e.g., Random Forests or Support Vector Machine) that process pixels that can be parameterised by the users through a simple configuration file. iota2 also offers the user the option of using a deep learning model. In addition to the pixel approaches, contextual approaches are also proposed, with Autocontext [1] and OBIA (Object Based Image Analysis). Autocontext, based on RF, takes into account the context of a pixel in a window around its position. The OBIA approach exploits an input segmentation to classify objects directly. In addition to the supervised classification approaches, iota2 is also able to produce indicator maps (biophysical variables) either by supervised regression or by using user-provided processors, diversifying the possibilities of using iota2. One major interest in iota2 is it's ablility to deal with a huge amount a data, for instance the OSO product (theia.cnes.fr/atdistrib/rocket/#/collections/OSO/2327b748-a82c-5933-afb0-087bbfeff4cd) is generated using a stack of all available Sentinel-2 data over the France without any landscape discontinuity due to the Sentinel-2 grid. Another point of interest is its capability to produce a landcover map everywhere a Sentinel-2 data and a groundtruth are available (ie : agritrop.cirad.fr/597991/1/Rapport_Intercomparaison_iota2Moringa.pdf). 1. Derksen, D., Inglada, J., & Michel, J. (2020). Geometry aware evaluation of handcrafted superpixel-based features and convolutional neural networks for land cover mapping using satellite imagery. Remote Sensing, 12(3), 513.

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name: IOTA2: large scale land cover mapping operational chain


uk: Комп'ютерні науки

description: Published in 2007, the INSPIRE Directive has established a pan-European Spatial Data Infrastructure (SDI) to support European Union (EU) policies related to or having an impact on the environment. The Directive requires Member States public organisations to make geospatial datasets in scope (i.e. belonging to 34 cross-sector categories known as data themes) interoperable, discoverable and accessible through view and download services. Fifteen years after the entry into force of the Directive, we assess the state of play, reflect on the lessons learned and, leveraging on these while also considering the current policy and technological context, elaborate a vision for the future evolution. Through its Geoportal, which regularly harvests the EU Member States national catalogues, the INSPIRE infrastructure currently provides access to approximately 90 thousand datasets. The amount and update of those datasets is steadily increasing as is the fraction of datasets whose metadata, data models and view/download services are compliant to the legal requirements of the Directive. The INSPIRE infrastructure is currently based on three so-called central components, which in turn are implementations of reusable and mature open source software solutions: the INSPIRE Reference Validator makes use of the ETF testing framework, the INSPIRE Registry is based on the Re3gistry software (included in the OSGeo Live since 2021) and the INSPIRE Geoportal is currently being migrated to GeoNetwork . INSPIRE has also played a key standardisation role in Europe by fully promoting and relying on open standards, mainly by ISO and OGC. Finally, an active and engaged community of stakeholders, meeting at the annual INSPIRE Conference and other related ad-hoc events, has highly favoured the policy and technological development. Despite many pros, lessons learned from INSPIRE also show some cons. These include e.g. overspecification in legislation (often leading to extensions to existing standards) which still limit implementation, and the lack of a common approach to data licensing. In addition, the current technological landscape is very different from the one from the INSPIRE dawn. New data sources (Internet of Things, citizen-generated and Earth Observation data, research data and data owned by businesses), new agile standards (e.g. OGC APIs for data sharing and modern standards for data encoding) and novel architectures (cloud, edge and fog computing) are creating an opportunity that INSPIRE shall leverage to remain relevant and fit-for-purpose. In parallel, driven by the recent European Strategy for Data, the current European policy context and related legislative instruments are strongly pushing for an increased, better and fairer use of all available data for the benefit of European economy and society. Within this context, the talk will illustrate our vision to streamline and simplify the technological and organisational structure of INSPIRE towards a data-driven and self-sustainable ecosystem. We will mainly reflect on the key role played by open source software, open standards and open licenses, and on the need to redefine the governance of the infrastructure through the increasing involvement of open source communities, including OSGeo as a strategic partner.

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name: A vision for INSPIRE: from a traditional SDI to a self-sustainable data ecosystem


uk: Комп'ютерні науки

description: OpenStreetMap (OSM) Galaxy is a project that the HOT Tech Team launched in mid-April 2021 to optimise and improve availability and accessibility of OSM Data outputs for different user groups within the ecosystem. Through this project, we strive to address all the OSM data needs under one umbrella and ensure OSM data is available, accessible and ready to use for all kinds of users. We are trying to solve the high dependency on different data sources and uncontrolled platforms while focusing on fast queries and process optimisation by accessing data from HOT administered and controlled environment. As a one-liner, the vision for OSM Galaxy is to provide a single platform to address all OSM Data Needs. In OSM context, a data need is a broad term covering a variety of topics: Raw data exports Analysing completeness of Data Checking the data quality in your neighbourhood Understanding your contribution to a mapathon, to name a few Through this project we strive to: Bring together all the data needs under one umbrella Ensure OSM data is available, accessible and ready to use for all kinds of users

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name: Introduction to Spatial Data Outputs Platform - OpenStreetMap Galaxy


uk: Комп'ютерні науки

description: Maplandscape is a stack of open-source geospatial applications designed to enable mapping of agricultural landscapes and farm systems. It supports large team in-the-field mobile data collection, provides tools for data syncing and management, and easy visualisation and querying of spatial information for decision making and reporting. The workflow has been developed and deployed in Tonga through a collaboration between universities in Australia and the South Pacific, and Tonga’s Ministry of Agriculture, Food, Forests and Fisheries (MAFF). Maplandscape is currently being used in Tonga to map crop, livestock, agroforestry systems, and farm management practices; over 11,000 farms and four island groups have been mapped so far. This information has been used to inform agricultural planning and resource allocation, disaster response, land utilisation assessment, tracking land use changes, and monitoring of the condition of key commercial crops. The Maplandscape workflow is based on QField for in-the-field data collection and QFieldCloud for data syncing, storage, and user authentication and management. Using QField mobile GIS, key agricultural landscape features (e.g. crop parcels, paddocks, fallow land) can be spatially mapped, and rich attribute information can be captured through various widgets and flexible and complex form logic, with support of reference geospatial layers. Three cloud-based applications have been developed that build on top of the QFieldCloud API to provide geospatial data visualisation and analytics tools. These applications provide differing and complementary functionalities, and facilitate quick analysis, publishing, and reporting of data collected using QField and stored using QFieldCloud. The apps are built using Shiny, Leaflet, ggplot, and DataTables software, and are deployed using ShinyProxy and docker containers in swarm mode. These applications use the QFieldCloud API to authenticate users and retrieve data and an R package has been developed to handle this interaction within Shiny apps. The goal of these applications is to speed up the process of data collected using QField informing agricultural monitoring, planning, and decision making activities. A summary of these geospatial data visualisation and analytics applications is provided below. maplandscape-view is a web app that allows users to query and view spatial data on interactive maps and data tables and generate reports comprising cartographic outputs, charts, and summary tables directly from QFieldCloud data. maplandscape is a web app that allows users to specify and apply custom geospatial data querying, analysis, and visualisation tasks to their QFieldCloud data in a web browser and with a simple UI interface. This application enables users without a GIS background to extract information from, and analyse, rich datasets collected in-the-field using QField; for example, agricultural officials in Tonga used this application to generate village- and district-level crop area summary tables for their annual report. Finally, maplandscape-admin provides tools for users to manage their QFieldCloud projects and accounts.

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name: Maplandscape - an open-source geospatial workflow for agricultural landscape monitoring


uk: Комп'ютерні науки

description: Today Protected Areas only partly cover important sites for biodiversity and are not yet fully ecologically representative and effectively or equitably managed. Improvement of the existing networks and further expansion of conservation areas will therefore require well-defined baselines that are comparable across countries for actions prioritisation. In recent years the availability of new earth observation imagery and advances in analysis and processing have significantly improved our capabilities in terms of mapping and monitoring biodiversity variables and ecosystem services. This event will introduce the Biodiversity Analyst, a web GIS tool, developed by the European Commission - Joint Research Centre, for identifying areas of potentially high conservation value based on the available datasets such as species distribution, ecosystems services and natural state. The aim of the Biodiversity Analyst is to provide decision-makers with means to visualise and interact with the above datasets which are considered key for biodiversity conservation while allowing them at the same time to test different weighting schemes in terms of prioritisation to identify so-called "biodiversity hot-spots".

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name: Identifying new conservation areas: a web multi-criteria approach using Earth Observation and other spatial information


uk: Комп'ютерні науки

description: The new Road Traffic Act of Finland (effective since 2020) requires the road management authorities to provide information about the existing road signs, along with other similar infrastructure such as traffic lights and road paintings, to Traficom, the Finnish Transport Infrastructure Agency. The data is stored in Digiroad, the national database of open street and road data, also hosted by Traficom. To help the different actors in public sector and elsewhere fulfill this legal obligation, as well as providing tools for infrastructure management and maintenance more generally, FOSS4G software can play an important role. In this talk, we present results from our recent project related to this effort. In the project, we developed a traffic sign inventory process using QField mobile data collection app and studied its suitability for the task. There was a pre-existing conceptual data model for the road signs from Traficom, which was used as the basis for the physical PostGIS database implementation. In addition, the data collection workflow was designed to make the data collection as efficient as possible. This included configuring the data input forms and the traffic sign visualizations in the related QGIS project file, as well as other aspects of usability of the app, such as further development of the geocoding functionality. The process was then tested out in the field and improved upon in cooperation with employees from a few different-sized municipalities around Finland. The finished project report, along with the files needed to set up the data collection project are freely available in the Github repository of the project: github.com/finnishtransportagency/digiroad-QField

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name: Using QField to manage traffic sign inventory


10 years in Georepublic and OSGeo

uk: Комп'ютерні науки

description: Taro Matsuzawa has been working for Georepublic for 10 years now. He has had experience in many open source communities since his student days, but had not yet joined the OSGeo community until he joined Georepublic. He is now a FOSS4G specialist and has presented at FOSS4G conferences in Japan. For a ten years he has been a committer for OpenMapTiles and several OpenSource projects, and has contributed more than 20 projects to Japanese companies and municipalities. In this issue, he would like to share some of the insights he has gained from his work and the OSS community. I will mainly talk about the basics and applications of Game Tile[1] technology, a small-scale map solution using pgRouting[2], and Python3 support for the ckanext-spatial plugin[3]. 1. leafletjs.com/SlavaUkraini/examples/crs-simple/crs-simple.html 2. pgrouting.org/ 3. github.com/ckan/ckanext-spatial/pull/249

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uk: Комп'ютерні науки

description: The European Flood Awareness System and the Global Flood Awareness System (EFAS and GloFAS), are the two Early Warning Service for floods part of the Copernicus Emergency Management Service (CEMS), operated by the EU Joint Research Centre (JRC). EFAS and GloFAS aims to complement national and regional service by providing medium-range flood forecasts and hydrological outlooks for large, transboundary rivers. Data and products are accessible to eligible users through the Climate Data Store and dedicated web interfaces. ECMWF, having the role of the computational centre within CEMS, is responsible for running the forecasts and the post-processing, on top of co-developing and hosting the EFAS and GloFAS information systems. These two information systems consist on back-end/front-end web services based on OGC standards and open-source software. As it is often the case, a web-based mapviewer allows to display different layers, produced by a WMS back-end. These layers are the graphical representation of the output of the hydrological models and meteorological observations, like flood probability, soil moisture, return period, observed precipitation etc. For most layers a new forecast is produced every 12 hours for EFAS and every 24 hours for GloFAS. Unlike many similar services, however, the aim of EFAS and GloFAS is not only to offer the latest forecasts or the latest observations but also to browse through data from previous days, so that older forecasts can be compared with actual observed events. This inherently means supporting the time dimension within the WMS standard, and managing large quantity of data that accumulates every day. In the case of EFAS, for example, an additional 1.5 Gb of data is produced twice a day. It also means handling the inevitable changes in data formats and structures that arise as the service grows and new features are added, without breaking backward compatibility. New layers are added, old layers are removed, changes in the geographical domain or the projection for a certain layer must be supported from a certain date onward, etc. Not to mention increasing the number of forecast cycles from one per day to two or more. To make matters worse, data access must be restricted on both front-end and back-end based on a matrix of user privileges, requested product and requested date. For example some layers are offered to all users with no time restrictions, while others are restricted to some users for the latest 30 days, and freely accessible to all users for dates older than 30 days ago. In this talk we describe the challenges of developing and operating an authentication-aware web service heavily based on large geospatial datasets with a strong diachronic component.

uk: вхід без авторизації

name: 10 years of open-source software in emergency management: the case of the European Flood Awareness Service


Early use of FOSS4G in a space start up

uk: Комп'ютерні науки

description: As a small but scaling new space company, Satellite Vu relies heavily on open source tooling for our image production pipeline, as well as storing our image assets and conducting experiments using thermal data sources. The company prides itself on being early adopters of emerging technologies, particularly as standardization of satellite imagery access and reproducible science are at the core of what we stand for. In this talk, we’ll give an overview of the main projects we lean on for all of data engineering, data science and thermal science as well as outline the vision for Satellite Vu’s evolving role within the open source community. Specific tools we’ll comment on our use include: 1. STAC, and the related stac-fastapi, for storing and serving image collections 2. rioxarray and stackstac for scaling our use of both internal and external cloud native imagery datastores 3. The pangeo stack for running experiments and scaling data processing 4. pygeoapi, as a vector data server I’ll introduce the Satellite Vu public STAC, and talk through how we’re using FOSS4G tools to shorten the development time of new products as well as prepare for the first satellite launch in Q1 2023.

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The Carto 2 Project

uk: Комп'ютерні науки

description: The Carto 2 project is part of the Geo-IDE program of the Ministries of Ecology and Agriculture in France. The objective of Geo-IDE is to provide stakeholders in the ministries with common data and tools in the field of geographic information. Since 2019, the Ministry of the Ecology and Camptocamp have been collaborating to create a new module, Carto2, that would allow data administrators to compose, publish and consult maps online and other users to search, consult or download published maps at the same time. Carto2 also had to offer a more modern and ergonomic platform, as well as possibilities to evolve the module and its functionalities in order to better meet the needs and expectations of the decentralized services. The project is developed using free solutions such as Geoserver, QGIS Server and Openlayers. This is an example of the development of a large departmental spatial data infrastructure used by about 150 services in France. We will present the software architecture and the strategies put in place to develop Carto 2 and we will describe the technical challenges we have faced during the development.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: The Orfeo ToolBox is used as development framework for satellite image processing over large dataset in several operational projects. Indeed, its image processing functionalities (multithreading, streaming, ram configuration) allow to process big images quite fast. The operational processing chains use OTB from the Python API and C++ API. Among the optical chain processing using OTB, we can list: MAJA, WASP, BIOPHY and IOTA2. MAJA (Maccs-Atcor Joint Algorithm) is an atmospheric correction and cloud screening software, based on multi temporal and multi-spectral processing. This chain uses L1C products to generate high quality L2A surface reflectance time series for Landsat8, Venus, and Sentinel 2 missions, it is mainly used by THEIA distribution center. The core algorithms of Maja are based on the Orfeo Toolbox. To process a product, the chain uses aerosol contents, cloud and shadow detection and various atmospheric effects to estimate accurate surface reflectance values. The main problem of the L2A products is the presence of clouds in time series which is why WASP was created. Indeed WASP (Weighted Average Synthesis Processor) delivers L3 products which provide monthly syntheses of cloud-free reflectance for Sentinel2 and Venus L2A products distributed by THEIA. This processor mainly includes a directional correction to normalize data and a weighted average of surface reflectance. Two other operational chains which uses OTB are BIOPHY - the goal of this processing chain is to create L2A products containing biophysical variables (FAPAR, FCOVER, LAI) related to the presence of vegetation in the image over a year – and IOTA2 - a soil occupation processor over a year of Sentinel1 and Sentinel2 data, the algorithms use the classification toolbox provided by OTB to process large areas, to determine the areas covered by buildings. OrfeoToolBox is also used for radar processing chain, like diapOTB or S1Tiling. S1TIling is a generic processing chain for Sentinel-1 time series developed with open-source software. Its main goal is to produce time series of Analysis ready data S1 images for large areas. The algorithms are using the SAR processing toolbox from OTB to take profit of its in-memory pipelining capabilities. DiapOTB is a differential SAR interferometry processing. It uses two SAR images of the same portion of the Earth’s surface taken at different time as input and aims to analyze potential events (earthquake, destruction …) by highlighting differences between SAR images. To conclude, OTB is the central framework for a large scale of operational chains in remote sensing. Its genericity permits to cover a lot of use cases in one single tool. Note that it is also distributed in other projects like WorldCereal, SNAP, AI4GEO as toolbox or RUS as training and formation aim.

uk: вхід без авторизації

name: OTB integration in operational processing chains


uk: Комп'ютерні науки

description: MapStore is an open source product developed for creating, saving and sharing in a simple and intuitive way maps, dashboards, charts and geostories directly online in your browser. You can use MapStore as a product to deploy simple geoportals by using the standard functionalities it provides but you can also use MapStore as a framework to develop sophisticated web gis portals by reusing and extending its core building blocks. MapStore is also integrated inside geOrchestra as well as GeoNode open source project. The presentation will focus on the use of MapStore as web gis framework to create a modular, reproducible, simple yet powerful dashboard to visualize crime data (but in reality many different types of location based data) leveraging on GeoServer and PostGIS advanced functionalities. We will describe the main steps for creating such an infrastructure leveraging on the MapStore components and framework then we will cover how the existing dashboard template can be configured to work with your own data sources (eventually touching the needed processing steps for the data itself) including GeoServer and PostGIS advanced functionalities. We will eventually discuss further improvements and new features to evolve the current capabilities to capture new and emerging requirements. The goal of this presentation is twofold, on one side we are addressing developers in order to show them advanced usage of MapStore to develop compelling applications on the other side we will be addressing power users and system administrators willing to deploy the Crime Mapping dashboard to make their own data available without writing code.

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name: Developing with MapStore; creating a custom dashboard to map crime data


uk: Комп'ютерні науки

description: Migration of the current tools that maintain the Cadastre of Mexico City to Open Source and free licensing technologies. The objective of the project was the development of a plugin in QGIS that optimizes the functionalities of the licensed software and allows the maintenance and management of cadastral data. Stages of the development process: a. Requirements analysis: Based on the information provided by the client, the feasibility of integrating the database engine, the API of workflow services with the transactional systems of the municipality is evaluated. b. Definition and implementation of PostGIS and QGIS: together with the client, for the integration of the tools and subsequent development. c. Design of Python and QT tools: carry out the design and development of plugin components in QGIS. d. Design of Postgres security interfaces: coordination with the permissions, automation routines with the plugin components. e. Development of functional tools from Bentley to QGIS: development of the previously detailed functionalities in the analysis and design stages of the project in order to replace the existing functionalities, accompanied by redesign. f. Test and implementation in Quality Assurance (QA) environment g. Training and technology transfer. h. Documentation of all strage of the process of the project, in order to carry out the complete transfer to our client.

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name: Development of plugins in QGIS for the management of the Multipurpose Cadastre in the Government of Mexico City


FOSS4G in the Solar System

uk: Комп'ютерні науки

description: It is well-known that Free Open Source Software is part of Space and Planetary Exploration, and the latest generation of rovers and drones on Mars embed FOSS components and frameworks. But what about Free Open Source for Geospatial software and data access and availability? We will travel the timeline of planetary cartography, from the first steps of remote and direct observation of the bodies of our Solar System to the era when Geographic Information Systems spread in Planetary Science and FOSS4G starts to play an essential role in studies and missions to environments beyond planet Earth.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: Since entering into force in May 2007, the Directive 2007/2/EC of the European Parliament and of the Council establishing Infrastructure for Spatial Information in Europe (INSPIRE directive) has been playing very important role in building spatial information infrastructures – both pan-European and at national level. Technical specifications and guidelines describe the key components of data content and of implementation of web services. However, each country decides individually how technically it will implement these requirements, what architecture and software it will choose to use. The roadmap of directive implementation has reached the last milestone in 21/10/2020 – all spatial data sets had to be provided to the INSPIRE geoportal (inspire-geoportal.ec.europa.eu/). Now is the best time to share the experience how Lithuania started INSPIRE implementation path using commercial software but successfully ended with using only FOSS4G. Implementation of INSPIRE directive in Lithuania is centralized and state enterprise GIS-Centras is responsible for technical work. INSPIRE directive was implemented in 2 stages. The first stage started back in 2012 and it was dedicated to cover data sets from Annex I and Annex II (only orthophoto imagery). Back then the INSPIRE directive implementation was a new and little-known technical challenge. The decision to call a tender and use the commercial software for which there were not many viable alternatives at the time seemed quite logical. The second stage of INSPIRE directive implementation started in 2018 and ended up in 2021. This stage was dedicated to cover data sets from Annex III and part of Annex II. Instead of just calling a tender to implement the requirements with commercial software we already had we decided to implement everything by ourselves and change the commercial software to FOSS4G. At the end of the project, we have not only prepared and published all the datasets and services, but also had a team of in-house specialists who were able to work with the FOSS4G. Even the results from the first stage was quickly changed to FOSS4G in order to unify the implementation architecture. We have set three goals for the transition from commercial software to FOSS4G: 1. Create a system that we can administer and develop ourselves; 2. Create infrastructure that is cost-effective in the long run; 3. Automate the workflow as much as possible. In this presentation we will share our experience of transition from commercial software to FOSS4G both from technological and company/team perspectives. We will present the technological architecture we use to implement INSPIRE requirements. It consist of PostGIS, Geoserver, QGIS, Hale studio, GDAL and Geonetwork. Finally we will explain what we have learn as a company and GIS specialists during the transition process.

uk: вхід без авторизації

name: Implementation of INSPIRE in Lithuania: experience with the transition to FOSS4G


uk: Комп'ютерні науки

description: The European Centre for Medium-Range Weather Forecasts (ECMWF) is an independent intergovernmental organisation which is producing and disseminating numerical weather and environmental predictions to its users in national meteorological services as well as commercial customers. As of recently, ECMWF started the move towards serving data to users beyond operational forecasters in Member states and commercial customers for a charge, by adopting an open data policy which will be implemented in phases from 2020 to 2025. The first phase included opening hundreds of web forecast charts (https://apps.ecmwf.int/webapps/opencharts) and making archived data available under a Creative Commons (CC BY 4.0) open licence in 2020. The next step was in January 2022 when the production of open subset of real time medium range forecast (ecmwf.int/en/forecasts/datasets/open-data) began. This phased move towards free and open data aims to support creativity and innovation in the field of scientific research as well as weather applications. It also represents a step towards more reproducible open science. However this can not be achieved by only opening the real time data. The users need to be able to find and easily use the data and integrate it into their own research work or application workflows. Reliable access to the data is achieved by making it available both through ECMWF https service and via the Microsoft Azure cloud, where the archived data is kept as well. In order for the data to be more FAIR (Findable, Accessible, Interoperable and Reusable), additional development work is being done. This work includes the design of an API (github.com/ecmwf/ecmwf-opendata) to easily download the geospatial data, and the development of open source Python libraries to process (github.com/ecmwf/ecmwf-data) and visualise (github.com/ecmwf/magpye) it. These open source libraries make use of open geospatial software, such as proj to deal with different projections. To present these new tools and help users understand how to retrieve and process ECMWF data, a set of Jupyter notebooks (github.com/ecmwf/notebook-examples/tree/master/opencharts) was created, each of them reproducing one open weather forecast chart from the downloading the data to the visualisation. This talk will give a short overview of which data is available in the open data set, and will then focus on the software and Jupyter notebooks development.

uk: вхід без авторизації

name: Towards open and accessible weather forecast data


uk: Комп'ютерні науки

description: The NexSIS project aims to create a digital rescue platform providing all civil protection actors in France with a complete set of cloud operational services. Open Source GIS solutions were chosen for this national project with strong technical requirements. This has a direct impact on the way data will be exploited. Each Fire Department will have to adapt and create data that will be directly used by the NexSIS software (areas that require special equipment or specialized teams for example). Currently in France each fire department has a budget depending on the size / number of people in the department. This budget is used to buy new fire extinguishers, computers, but also to hire new people, etc... Most departments currently use many different proprietary softwares for all GIS aspects. Historically, each department has made their own choices on what software they use. This talk will show how we are helping fire brigades to make the switch to Open Source without losing any functionalities and without any extra work load. Using the power of both QGIS and PostgreSQL, we will show how these tools can be used to share and publish common workflows (qgis expressions, model builders) that are often used in fire emergencies, build a common atlas (report module), edit spatial data (forms, and constraints) and so forth.

uk: вхід без авторизації

name: Favoring Opensource Technologies for French Fire Brigades


uk: Комп'ютерні науки

description: The presentation will provide a comprehensive introduction to GeoServer's own authentication and authorization subsystems. The authentication part will cover the various supported authentication protocols (e.g. basic/digest authentication, CAS, OAuth2) and identity providers (such as local config files, database tables and LDAP servers). It will explain how to combine various authentication mechanisms in a single comprehensive authentication tool, as well as providing examples of custom authentication plugins for GeoServer, integrating it in a home-grown security architecture. We’ll then move on to authorization, describing the GeoServer pluggable authorization mechanism, and comparing it with proxy based solution. We will explain the default service and data security system, reviewing its benefits and limitations. Finally we’ll explore the advanced authorization provider, GeoFence. The different levels of integration with GeoServer will be presented, from the simple and seamless direct integration to the more sophisticated external setup. Finally we’ll explore GeoFence’s complex authorization rules using: - The current user and its roles. - The OGC services, workspaces, layers, layer groups. - CQL read and write filters. - Attribute selection. - Cropping raster and vector data to areas of interest.

uk: вхід без авторизації

name: Mastering Security with GeoServer and GeoFence


uk: Комп'ютерні науки

description: Orfeo Toolbox (OTB) is a free and open-source remote sensing software. It is available on multiple platforms, Linux, Windows and MacOs, and was developed primarily by CNES (French Space Agency) and CS Group in the frame of the development of the ORFEO program (French and Italian support program for Pleiades and Cosmo-Skymed). OTB can process large images thanks to its built-in streaming and multithreading mechanisms. Its data processing schema is primarily based on ITK pipelines, and uses GDAL dependency to read and write raster and vector data. Many formats are supported by the library (at least those supported by GDAL) as CosmoSkyMed, Formosat, Ikonos, Pleiades, QuickBird, Radarsat 2, Sentinel 1, Spot5, Spot 6/7, TerraSarX or WorldView 2. OTB provides a lot of applications to process optical and SAR products: ortho-rectification, calibration, pansharpening, classification, large-scale segmentation and more. The library is written in C++ but all the applications can also be accessed from Python, command line launcher, QGIS and Monterverdi, a powerful satellite image visualization tool bundled in the OTB packages capable of manipulating large images efficiently. The library also facilitates external contributions thanks to the remote module functionality: users can add new applications without modifying the core of the library. If this new remote module is relevant, it could be added as an official remote module, like DiapOTB (differential SAR interferometric processing chain) and OTBTensorflow (multi-purpose deep learning framework, targeting remote sensing images processing). Moreover, several operational image processing chains are based on OTB: their algorithms use the framework of OTB Applications while the orchestration is written in python. Some of the chains are also open source: Let It Snow (Snow cover detection), iota2 (Large Scale Land Surface Classification), WASP (Multitemp images fusion), S1Tiling (Sentinel-1 calibration and MAJA (Maccs-Atcor Joint Algorithm). The Orfeo Toolbox is also a part of the Sentinel 2 ground segment, being integrated in the S2 Instrument Processing Facility (IPF) module where it is used for radiometric corrections and resampling. In the latest releases (from 7.x to 8.0), several features have been added as new SAR sensor models and new applications, and the OSSIM dependency - used for geometric sensor modelling and metadata parsing – has been removed in favor of functionalities available in GDAL. The aim of the presentation is to present the major features of OTB, the latest updates, the future features and architecture of the library and how OTB is used at CNES and CS Group to process data from scientific and developer points of view.

uk: вхід без авторизації

name: Orfeo ToolBox: open source processing of remote sensing images

name: Open Source Geospatial Foundation (OSGeo)


uk: Комп'ютерні науки

description: The open standards, open source geospatial and open science communities still have a very limited answer to the question how researchers active in applied domains such as agriculture, ecology, hydrology, oceanography or land use planning can benefit from the large amounts of open Earth Observation (EO) data currently available. Solutions are very much tied to platforms operated and controlled by big tech (Earth Engine, Planetary Computer), particular programming languages, software stacks and/or file formats (xarray, Pangeo, ODC, GeoPySpark/GeoTrellis). The openEO initiative provides an API and a set of processes that separate the “what” from the “how”: users specify what they want to compute, and back-end processing engines decide how to do this. The openEO API is OpenAPI compliant, and has client interfaces for Python, R, and JavaScript, and in addition graphical user interfaces running in the browser or in QGIS. The underlying data model is that of a data cube view: image collections or vector data may be stored as they are, but are analysed as if they were laid out as a raster or vector data cube, e.g. for raster with dimensions x, y, band and time, or for vector with dimensions geometry, band and time. Because openEO assumes that imagery is described as STAC collections and the implementation is composed of open source components, it is relatively easy to set it up and compute on infrastructure where imagery is available through a STAC interface. Having a single interface to carry out computations on back-ends with different architecture makes it possible to compare results across implementations, to verify that EO processing is reproducible. So far, over 100 processes have been defined, and user-defined functions written in Python or R extend this ad infinitum. openEO was initially developed during a H2020 project (2017-2020). It is currently continued with ESA funding that has resulted in the “openEO Platform”, an implementation run by VITO and EODC where the general public can use the openEO interface for large scale computations. Several upcoming Horizon Europe projects will further support continued development of the API and openEO software ecosystem of clients and back-ends. Since the initiative is designed to be an open science, all users and developers are invited to engage. We will present the current state of the openEO ecosystem and give an outlook to forthcoming developments.

uk: вхід без авторизації

name: openEO: Open Science for Earth Observation Research


uk: Комп'ютерні науки

description: The UK national walking organisation, Ramblers, are working to improve the public rights of way network, and in particular improve access to it for people who are less advantaged, and may not have access to vehicles. The research project described in this talk undertook an analysis of the national paths network using publicly available data supplied by hundreds of individual local authorities across the UK. This was done by setting up a series of models in the QGIS Graphical Modeler to generate six key indicators aggregated to census area level, including distance to nearest continuous path from each small area unit of population, length of available path within a series of buffers, and access to paths of specific types – for example those passing through protected or designated areas. The talk will look at some of the challenges of the project, including scaling the modeller to work with millions of path features and tens of thousands of point locations, and building processes to combine path segments and then disaggregate them to an appropriate level. The main goal of the project was to inform and support specific policy proposals, but it is also intended that the QGIS models should be passed on to Ramblers and used in the longer term, to monitor the impact of changes to the paths network and of population patterns over time, and also to support analysis of how additions to the network, for example by the inclusion of historic paths which are not yet official rights of way, could improve access. The intention is that these models could be run on smaller areas, and on hypothetical paths networks, to help build a case for extensions and rationalisation of the paths network at both national and local levels. Use of the Graphical Modeler rather than scripts or database processing will make it easier for Ramblers staff to run the models themselves in the future using inputs of their choice.

uk: вхід без авторизації

name: Analysing access to UK public rights of way with the QGIS Graphical Modeler


uk: Комп'ютерні науки

description: Spoiler alert, I believe the answer to the question posed in the title is a firm “no”. As such, this presentation will describe why a healthy commerce ecosystem is an essential component of the broader FOSS4G community. The presentation will describe several commerce models that both support open source initiatives and generate work and revenue for businesses. The commerce models presented will be complimented by real world examples of these models in action. The presentation will also describe the trend of large companies open sourcing some of the tools that they use to run their business and/or that support their products. The presentation will also describe the business importance of open source frameworks for both the broader Javascript development space (e.g., React, Angular, etc.) and the more specialized geospatial development arena (e.g., Deck.gl, etc.). Finally, while making money is appropriate within open source communities, it is always important that businesses contribute back to the open source ecosystem and best practices for being a good open source citizen will be discussed.

uk: вхід без авторизації

name: Is it wrong to make money with FOSS4G technology?


uk: Комп'ютерні науки

description: *"Géocommun"* `[ʒeokɔmɛ̃]` : is it the latest buzzword in France or a large movement towards more openness in the geospatial realm ? The French National Geographical Institute (IGNF) recently started communicating its vision towards the development of Geo-commons. This sounds like a strategical change in the way the institute apprehends geo-data and geo-software production. In this presentation, we first try to give a definition of what a "geocommon" is. Then we review the initiatives currently being deployed by various actors in France to transform this word into a reality. We study the roots of these actions and their links to opendata, opensource and opengov movements. We also try to provide a mindmap of involved actors, and how they interact together : administrations, data-oriented communities or software-oriented communities. Then we anticipate the impact on free and opensource software for geomatics, and how it could affect technologies and communities in this area.

uk: вхід без авторизації

name: Geo-commons in France : review of current initiatives