GeoMapFish status: vector tiles!

uk: Комп'ютерні науки

description: GeoMapFish is an open source WebGIS platform developed in close collaboration with a large user group. It targets a variety of uses in public administrations and private groups, including data publication, geomarketing and facility management. OpenLayers and an OGC architecture allow to use different cartographic engines (MapServer, QGIS Server). Recently new features have been added such as vector tiles integration, from raw data to visualization. In order to get rid of AngularJS dependency, a roadmap has been established for a migration to a web components architecture. Everything has been planned so that our users can continue to develop their projects during this process. K8S support is evolving with the implementation of the necessary tools for Azure environments. Highly integrated platform, large features scope, fine grained security, reporting engine, top performances and excellent quality of service are characteristics of the GeoMapFish solution. In this talk we ll present the key usages, web components migration process and latest developments, including vector tiles support.

uk: вхід без авторизації


Antonio Cerciello

type: Person

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: The Open Geospatial Consortium API family of standards (OGC API) are being developed to make it easy for anyone to provide geospatial data to the web, and are the next generation of geospatial web API standards designed with resource-oriented architecture, RESTful principles and OpenAPI. In addition, OGC APIs are being built for cloud capability and agility. pygeoapi is a Python server implementation of the OGC API suite of standards. The project emerged as part of the OGC API efforts started in 2018 and provides the capability for organizations to deploy OGC API endpoints using OpenAPI, GeoJSON, and HTML. pygeoapi is open source and released under an MIT license. pygeoapi is built on an extensible plugin framework in support of clean, adaptive data integration (called "providers''). Elasticsearch (ES) is a search engine based on the Lucene library. It provides a distributed, multitenant-capable full-text search engine with an HTTP web interface and schema-free JSON documents. The Elasticsearch data provider for pygeoapi is one of the most complete in terms of functionalities and it also includes CQL support with the CQL-JSON dialect, which allows you to take extra advantage of the ES backend. This presentation will provide an overview of OGC APIs, pygeoapi and Elasticsearch integration, and demonstrate usage in a real-world data dissemination environment.

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: Implementing OGC APIs using Elasticsearch and pygeoapi

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: Chestnut stands in Piemonte are presently suffering a severe decline due to the concurrence of climatic and silvicultural factors. A project funded by Piemonte region involving the Regional Chestnut Centre and IPLA S.p.A. started in 2018 with the aim of defining technical guidelines for proper interventions in declining stands. The present contribution deals with the activities of spatial monitoring of declining areas through satellite images interpretation and GIS analysis making use of QGIS and Grass tools. Methodological approach was based on the selection of Sentinel 2A e 2B images taken at the beginning and at the end of the summer season in 2017, 2018 e 2019 on a test area. Those images were then processed calculating some indexes with raster functions implemented in QGIS. NDWI Normalized Difference Water Index (B8-B12/B8+B12) resulted the more sensible to the presence of declining stands Accurate mapping of areas suffering different degree of damages on the whole Region was then carried out starting from a preliminary analysis of experimental parcels surveyed on the field.

uk: вхід без авторизації

name: Use of remote sensing and GIS processing for mapping Chestnut stands decline in Piemonte Region


keywords: foss4g2022 generaltrack Stateofsoftware

uk: Комп'ютерні науки

description: ETF is an open source testing framework for validating data and APIs in Spatial Data Infrastructures (SDIs). It is used by software solutions and data providers to validate the conformity of geospatial data sets, metadata and APIs. For example, ETF is the underlying framework used by the INSPIRE Reference Validator to validate INSPIRE metadata, datasets and services against the requirements of the INSPIRE Technical Guidelines. ETF is also used extensively in Germany by the Surveying Authorities of the Laender to validate their datasets. This includes Real Estate Cadastral data, Topographic data, Control Points, 3D Building Models, House Coordinates and Building Polygons. In the test environments of the German Laender, a comprehensive series of attributive, relational, geometric, and topological tests are performed on the data, in addition to interacting with APIs and checking for errors in the interface contracts. Other European Union (EU) Member States are also reusing ETF to allow their data providers to test resources against national requirements. Finally, some software tools such as GeoNetwork open source include validation based on the ETF API in their workflow. Goals in designing the ETF software were to create test reports that are user-friendly and self-explanatory as well as to be able to validate large amounts of data, which can be several hundred GB in size. In order to cover different validation tasks and present them in a unified report, the architecture is modular and different Test Engines can be used. Currently the following Test Engines are supported: SoapUI for testing web services, BaseX database for testing XML data, Team Engine to validate WFS and OGC Web APIs using the OGC CITE tests, NeoTL Engine for testing WFS, OGC Web APIs and datasets. As a horizontal and reusable tool, which could be extended to satisfy the needs of different communities and domains, ETF is currently considered as a component of the so-called Common Services Platform under the new Digital Europe Programme of the European Commission. Within this context, activities are planned in 2022 to: i) include the ETF in the OSGeo Live v.15, and ii) submit the ETF as an OSGeo Community Project. In this talk, we will introduce the ETF testing framework, the deployment scenarios and address the current and future technical developments.

uk: вхід без авторизації

name: ETF testing framework: past, present and future


uk: Комп'ютерні науки

description: For several years Gter has been involved in the development and maintenance of the webGIS related to the management of the road network of the Province of Piacenza. Recently, the client requested the integration of the images, deriving from the photographic survey of about 520 Km of routes, in the existing webGIS (an instance of Lizmap Web Client which public version can be found here catastostrade.provincia.pc.it/lizmap/lizmap/www/index.php/view/map/?repository=progettipubblici&project=catasto_strade_pub). In this case, the Public Administration needed the photographic survey in order to update a set of old images sparsely distributed along the network and to have a customized tool similar to services like Google Street View. Therefore, an integration of the Mapillary viewer in Lizmap Web Client has been proposed and developed; hence the survey was performed with a camera that uses front and back optics to have 360-degree photos. The workflow consisted of four main tasks. The first step involved the photographic survey of the road network using a GoProFusion360 mounted on a car that took photos of the surrounding environments. The next step consisted in the processing of the images, stitching the front and the back photos in order to obtain a 360-degree panoramic image. This step has been automated through the development of a Python script together with the use of the available software of the camera from the command line. About 50000 photos were uploaded on the Mapillary platform. Images have been integrated into the Lizmap Web Client webGIS through the Mapillary viewer and utilities. The integration was achieved by developing a new feature for Lizmap Web Client based on Mapillary JS, an Open Source library provided by Mapillary that helps developers interact with the Mapillary API. The final result is a tool that makes the Public Administration able to navigate and reach the photos uploaded on Mapillary directly from a window in the webGIS.

uk: вхід без авторизації

name: From photographic survey to street-level imagery integration in an OpenSource webgis: complete workflow


uk: Комп'ютерні науки

description: ECMWF is a research institute and a 24/7 operational service, producing global numerical weather predictions and other data for a broad community of users. To achieve this, the centre operates one of the largest supercomputer facilities and data archives within the meteorological community. ECMWF also operates several services for the EU Copernicus programme to provide data for Climate Change, Atmospheric monitoring and Emergency services. As part of ECMWF's Open data initiative, more and more meteorological data and web services are freely available to a wider community. ECMWF's web services include an interactive web application to explore and visualize its forecast data, a Web Map Service (WMS) server and many graphical products including geospatial weather diagrams so called Ensemble (ENS) meteograms and vertical profiles. ENS meteograms and vertical profile diagrams are among the ECMWF's most popular web products and presents ECMWF's multi-dimensional real-time ensemble forecast data for a given position globally. They are freely available through various ECMWF web services, and integrated on ECMWF's GIS based interactive web application. Datasets powering the dynamically generated diagrams are formed from a rolling archive of 10 days data, updated twice a day and each update consists of data around half a Terabyte. An upcoming update on ECMWF's forecasting system will increase the data size by a factor of 3-4 times in the near future. In addition to ECMWF's forecast data, similar services are requested as part of various Copernicus projects producing different datasets. This talk presents migrating legacy data structure used for ENS meteogram datasets to a more flexible, extensible, and high performing one fit to be used by GIS systems by using Free Open Source Software (FOSS). The new data structure uses Python ecosystem. The data preparation workflow as well as the challenges and the solutions that are taken when dealing large and frequently updated geospatial datasets are presented. Talk will also include early experiments and experiences to offer these datasets as part of OGC's Environmental Data Retrieval (EDR) API.

uk: вхід без авторизації

name: A high performing data retrieval system for large and frequently updated geospatial datasets


uk: Комп'ютерні науки

description: Since landing on Mars in February of 2021, the Mars 2020 Perseverance Rover has been exploring Jezero crater to investigate an ancient delta looking for the evidence of past microbial life and to better understand the geologic history of the region. In support of Terrain Relative Navigation (TRN), which enables the Mars 2020 spacecraft while landing to autonomously avoid hazards (e.g., rock fields, crater rims), the USGS Astrogeology Science Center generated two precision mosaics: 1) the Lander Vision System (LVS) map generated from three Context Camera (CTX) orthorectified images that was used onboard the spacecraft and was the “truth” dataset that TRN used to orient itself relative to the surface during Entry, Decent, and Landing; and 2) a High Resolution Imaging Science Experiment (HiRISE) orthomosaic which was used as the basemap onto which surface hazards were mapped. The hazard map was also onboard the spacecraft and used by TRN to help identify the final, hazard-free landing location. This talk will present the workflow used by the USGS Astrogeology Science Center to generate these critical data products including the use of FOSS4G tools like GDAL. Other open-source packages used will also be shared.

uk: вхід без авторизації

name: Helping to Land a Mars Rover using FOSS4G Tools


uk: Комп'ютерні науки

description: Lizmap is an opensource server application to publish QGIS project on the web without any coding skills needed. It's using QGIS Server in the backend so users have the same rendering between their QGIS Desktop and the web version of their project. QGIS Server and Lizmap are reading QGIS project to publish layers with their legend, forms, print layout, layer relationships... Some additional Lizmap configuration can be added to have dataviz capabilities, decide or not to publish the attribute table or to configure the feature filter form. No coding skills are required, all the configuration is done using QGIS Desktop user interface. The QGIS project is adapted for web browsers and have a responsive UI. Lizmap include some Access Control List at different levels such as project, layer or even features. The goal of this presentation is to show the state of this opensource project hosted on GitHub and to explain the roadmap.

uk: вхід без авторизації

name: State of Lizmap - Past / Present / Futur


uk: Комп'ютерні науки

description: In the city of Ferrara (Italy) Dedagroup Public Services and other partners are involved in AIR-BREAK project (airbreakferrara.net/) to implement a set of geo-ICT tools for supporting an improved identification and monitoring of urban air quality. Different datasets from heterogeneous sources have been already interconnected and integrated in the Spatial Data Infrastructure of the Municipality of Ferrara, based on (geo)standard protocols for data interchange sourced by: • 173 authoritative AQ monitoring stations from 3 regional environmental agencies, ARPAE Emilia-Romagna (52), ARPA Veneto (33) and ARPA Lombardia (88), for their own whole regional areas; • 2 private AQ monitoring stations managed by private companies located in Ferrara; • 14 new AQ monitoring stations installed by Lab Service Analytica (project partner) in the territory of Ferrara For integrating and sharing dynamic hourly data about air quality and other themes, we adopted the OGC Sensor Things APIs (STA) as the reference standard protocol [1]. STA is based on the OGC/ISO 19156:2011 [2] and provides an open and unified framework to interconnect IoT sensing devices, data, and applications over the Web. It is an open standard addressing the syntactic interoperability and semantic interoperability of the Internet of Things. It complements the existing IoT networking protocols such CoAP, MQTT, HTTP, 6LowPAN. While the above-mentioned IoT networking protocols are addressing the ability for different IoT systems to exchange information, STA is addressing the ability for different IoT systems to use and understand the exchanged information. In AIR-BREAK project, FROST solution (FRaunhofer Opensource SensorThings-Server) [3] has been deployed in the GIS server farm of the Municipality of Ferrara to complement Geoserver and other technologies already providing services for viewing/accessing data based on OGC standards. Indeed, among the final objectives of the project, the implementation of a standard-based Air Quality Data Infrastructure focuses on: 1. creating a bi-lateral and cooperative communication systems between authorities and citizens about air quality and its perception; 2. defining and implementing a multi-stakeholder Data Infrastructure on Air Quality to integrate existing/heterogeneous/dynamic data from both authoritative sources and crowdsourced by citizens (Rete di Monitoraggio Ambientale Partecipativo [4]); 3. providing such dynamic air quality data to local authorities involved monitoring (i.e. Municipality of Ferrara, ARPAE, Regione Emilia-Romagna) and to citizens, through standard APIs (STA) and with open licenses through the upcoming open data portal of Ferrara (June 2022); 4. testing and validating innovative solutions for air quality monitoring using in-situ IoT sensors and satellite remote sensing (e.g. Copernicus) References: [1] en.wikipedia.org/wiki/SensorThings_API [2] iso.org/standard/32574.html [3] GitHub: FraunhoferIOSB/FROST-Server [4] rmap.cc/

uk: вхід без авторизації

name: SensorThings API in practice: the AIR-BREAK project in Ferrara


uk: Комп'ютерні науки

description: This presentation examines the global impact of COVID-19 on traffic across 40 cities in Europe, South East Asia, Australia, and North America. I analyzed monthly rush hour traffic from 2019 to 2021 with GeoPandas, leafmap, and HERE's Traffic Analytics data. In addition, I correlated traffic volume with COVID positivity, mortality, and vaccination rates to examine how these factors influence the resumption of pre-pandemic traffic patterns. Because of the volume of the traffic data (billions of records), desktop GIS software, including spatially enabled databases, could not reliably process it on a desktop computer. Online solutions, such as Google Colab, would have been a costly alternative given the amount of data. However, GeoPandas and Jupyter notebook on notebook computer was able to process the traffic data and enhance the spatial road data and support joining the result to the road network for visualization. The method for processing the data will be discussed in detail. In summary, open source tools give researcher unprecedented abilities to process large amounts of data.

uk: вхід без авторизації

name: Where Is Everyone?: The Global Impact of COVID on Road Traffic


3D Tiles Next

uk: Комп'ютерні науки

description: "3D Tiles Next" is a major update of the "3D Tiles" OGC Community Standard 1.0. 3D Tiles are designed by Cesium GS, Inc. for streaming massive heterogeneous 3D geospatial datasets. 3D Tiles Next is a set of extensions in the following areas: - direct use of glTF models - using glTF for point clouds and glTF extensions for texture compression additional 3D tiles functionality - semantic metadata stored per tileset, feature, vertex and more - implicit spatial indexes (quadtree, octtree, S2 subdivision) This presentation gives an overview of the current "3D Tiles" format and shows new features in the "3D Tiles Next" specification. It also covers other existing 3D OGC (community) standards like CityJSON or «Indexed 3D Scene (I3S)». Important further topics are : - overview of viewers for 3D Tiles on the web and in native and mobile applications using game engines - data processing tools for producing data in these formats - building a community for creating 3D tiles for GIS and OSM data

uk: вхід без авторизації


Creating vector tiles with osm2pgsql

uk: Комп'ютерні науки

description: For over a decade now osm2pgsql has been the standard tool for importing OpenStreetMap data into a PostgreSQL/PostGIS database for rendering of raster tiles and many other use cases. Thanks to several improvements in the last years centered around a flexible configuration language and new geoprocessing capabilities, osm2pgsql is now also a great base for creating a vector tile toolchain. It can easily handle imports of a small country in a few minutes as well as scale to a planet-sized database with minutely updates from OSM. The talk will introduce some of the new features that allow you to customize the database table layout and contents. It will outline the few steps needed to create your very own custom vector tiles based on OpenStreetMap data. We'll see how you can use the configuration language to clean up OSM data on import and prepare it for fast access with a vector tile server like T-Rex.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: The Open Geospatial Consortium (OGC) and the Open Source Geospatial Foundation (OSGeo) have a long and natural tradition of collaborating. In 2022, the Memorandum of Understanding between both organizations was updated - to pay tribute to ongoing and future activities. In the initial MoU (2008), OGC and OSGeo agreed to work closely to coordinate with each other’s memberships regarding new standards developments and standards changes that may be required as a result of open source programs. Another important aspect of the relationship is to keep each other well informed of the respective activities and directions. Both aspects have proven to be of great importance. One goal was and is to coordinate activities in such a way as to maximize the achievement of both organizations’ mission and goals. That includes to identify open source technologies that can be used as reference implementations for and validate compliance tests developed for OGC adopted standards. Since the first MOU, there has been an increase in OGC on developer focus and engagement of software communities and activities. Increased collaboration has also occured by way of the OGC API code sprints. In addition, key opportunities for cross pollination have evolved given shared missions (FAIR data) and the viewpoint that FOSS4G software is beneficial for all software. The development of the OGC API suite of standards is an excellent example on how the MoU works in practical terms. The OGC APIs are a family of Web APIs that have been created as extensible specifications designed as modular building blocks that enable access to spatial data that can be used in data APIs. These revolutionary APIs make location information more accessible than ever before through the use of RESTful principles, and the OpenAPI specification for describing interfaces. OGC APIs have been tested in close collaboration with the global developer and end user communities through hackathons, sprints, and workshops to provide a modern solution to tomorrow’s location sharing issues. For example, the 2021 Joint Code Sprint organized by OGC, OSGeo and the Apache Software Foundation (ASF) included open source implementations of OGC APIs - and became a standing sprint activity that was repeated in 2022. This presentation provides a deeper dive into the new Memorandum of Understanding and how both open standards and free and open source software can benefit from one another.

uk: вхід без авторизації

name: We are Open! OGC and OSGeo Collaboration


uk: Комп'ютерні науки

description: Globally, the population living in urban areas is increasing with a strong impact on land use patterns, particularly on the availability and use of green spaces. The impact of green spaces is beneficial to health, for example, by reducing mortality or improving mental health. These effects are also related to different ecosystem services provided by green spaces, such as regulating temperature, modifying air pollution and noise levels, and offering more opportunities for physical activity. GreenUr is a plugin for QGIS that aims at putting together knowledge and information on the impacts of green space on health. It is developed as a prototype representing a work in progress coordinated by the World Health Organization (WHO) to provide an educational tool to introduce the relation between green spaces, health, and well-being and raise awareness of the importance of green spaces in cities globally. The tool can also be used as ‘quickscan’ for urban spatial planners that would like to orientate on possible effects of current and new green space design. The plugin has been tested with different experts and locations, and it will be downloadable via the QGIS Plugin manager from the project website. The GreenUr tool allows the users to estimate the impacts of green spaces on health in a given population. The main questions addressed by the current version of the GreenUr prototype are the following: - How much green space is available for the population of a specific city? - Which are the pathways through which green spaces relate to health? - Where within a city are health-related benefits of green spaces the largest? - Which are hypothetically different land-use scenarios for green spaces? - What would be the magnitude of the change in health impacts if future green space would be changed in cities? All calculations performed by GreenUr are based on methodologies established by social, environmental, and epidemiological studies identified by WHO. The computational backend used is GRASS GIS and other processing methods available in QGIS. The plugin is running any common operating system and offers a demo database.

uk: вхід без авторизації

name: The GreenUr project: creating an application in QGIS to manage the impacts of urban green spaces on human health


uk: Комп'ютерні науки

description: As climate change progresses, we are experiencing an increase in the frequency and severity of extreme weather events in many parts of the world. Climate models predict the frequency and severity of these weather events to continue to increase in the future as surface air temperatures rise. In 2021, the Canadian province of British Columbia (BC) experienced one of the most severe fire seasons on record which destroyed communities and ecosystems across the province. In the same year, an “atmospheric river” precipitation event led to widespread flooding causing severe damage to roads and communities across BC. There is a correlation between severe wildfires and increased runoff following precipitation events in some regions. There is a need for better prediction, monitoring, and management of fire and flood events to mitigate the damages caused by post-wildfire flooding. Remote sensing data and analysis techniques play a key role in monitoring climate-related natural disasters and helping understand and mitigate risks to communities, ecosystems, and infrastructure in areas that may be exposed to flooding. Free remote sensing datasets along with free and open source software can greatly reduce the costs and increase availability of this monitoring capability, increasing stakeholder access to geospatial intelligence. This talk presents a tool developed at Sparkgeo for automated mapping of burn severity and extent within watersheds of interest. The tool uses multi-source public remote sensing data in a cloud-based workflow, taking advantage of recent open source initiatives including the SpatioTemporal Asset Catalog (STAC). The tool can help assess flood risk from significant rainfall events and may offer essential flood mitigation and risk management knowledge. We present the tool’s deployment to map 2021 wildfires in several British Columbia watersheds.

uk: вхід без авторизації

name: A tool for mapping fire burn severity and extent in watersheds for flood risk assessment


uk: Комп'ютерні науки

description: geotiff.js is a reusable library to abstract remote (Geo)TIFF files. With it, both rich visualization frontends or statistical or data access services can be implemented, as it is possible to inspect the geospatial metadata and the full spectrum raster values of the original data, instead of only 8-bit RGB(A). Due to its file abstractions, it is possible to only read the relevant portions of a file, thus greatly reducing bandwidth and response times. This effect can be further increased when reading Cloud Optimized GeoTIFF (COG) files. The library tries to be as feature complete as possible in terms of file layout, raster cell values, RGB transformation, image data compression and metadata. This talk will detail the features of geotiff.js, as well as its most recent additions. Additionally, it will shed light on the greater ecosystem of geospatial libraries and applications where geotiff.js is embedded or building the foundation of.

uk: вхід без авторизації

name: geotiff.js - efficient GeoTIFF exploration in the browser and server


uk: Комп'ютерні науки

description: The amount of data available from drones, earth observation as well as machinery itself (i.e. telemetry data) plus the advent of cloud infrastructure has given a huge impulse to innovating the way we used to support farmers and farming in general, democratizing access to data and capabilities like never before through precision (or digital) farming solutions. Precision farming (or digital farming) has therefore become one of main use cases for GeoServer deployments over the past years and at GeoSolutions we have worked with many clients, from NGOs to large private companies (like Bayer), from startups to organizations like DLR in helping them to support their client to make sense of data and information through GeoServer and other geospatial open source technologies at scale, in the cloud. This presentation will condense 10 years of GeoSolutions in ingesting, managing and disseminate data at scale in the cloud for the precision farming industry covering items like: - Proper optimizations and organization of raster data - Proper optimizations and organization of vector data - Modeling data for performance & scalability in GeoServer and PostGIS - Deployment guidelines for performance and scaling GeoServer - Styling to create NDVI and other visualizations on the fly At the end of the presentation the attendees will be able to design and plan properly a GeoServer deployment to serve precision farming data at scale.

uk: вхід без авторизації

name: Supporting precision farming with GeoServer: past experiences and way forward


State of GeoServer 2022

uk: Комп'ютерні науки

description: GeoServer is a web service for publishing your geospatial data using industry standards for vector, raster and mapping, as well as to process data, either in batch or on the fly. GeoServer powers a number of open source projects like GeoNode and geOrchestra and it is widely used throughout the world by organizations to manage, disseminate and analyze data at scale. This presentation provides an update on our community as well as reviews of the new and noteworthy features for the latest releases. In particular, we will showcase new features landed in 2.20 and 2.21, as well as a preview of what we have in store for 2.22 (to be released in September 2022). Attend this talk for a cheerful update on what is happening with this popular OSGeo project, whether you are an expert user, a developer, or simply curious what GeoServer can do for you.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: GeoRasterLayer is a LeafletJS Plugin for visualizing GeoTIFFs. This presentation will show live demos of new features and discuss the roadmap for the next couple of years.

uk: вхід без авторизації

name: State of GeoRasterLayer: A LeafletJS Plugin for Visualizing GeoTIFFs (and soon other rasters)


uk: Комп'ютерні науки

description: I am the Founder and CTO of Blue Sky Analytics, a Climate-Tech Startup using satellite-derived climate intelligence to power financial decisions. We provide datasets through API spanning flood, drought, wildfire, heat risk for monitoring, measuring and mitigating climate risk which can be leveraged for various use-cases. In 2 years, we have analyzed TBs of data, delivered 5 datasets & built platforms for data visualisation and distribution from scratch using FOSS technology. This has been a rocket-ship of a journey, chasing our mission of building a ‘Bloomberg for environmental data’. However, the not-so-secret sauce to achieving these milestones has been FOSS. We are often asked how we procure raw geospatial data and how much we spend on it. Thanks to the abundance of open data, our data acquisition cost has been 0. Due to the generous open data policy of amazing organisations like NASA & ESA, we have been able to build a business collecting TBs of data daily & crunching them into useful insights. This helped us scale our vision to build a global environmental data stack for tracking climate change in real-time. Moreover, before this data can be applied to climate mitigation, it needs to be analysed. This is true for any big data and today, less than 1% of global data is analysed. Given that satellite data is the most significant source of tracking climate variables, it became imperative to tap this source. We discovered that the path to providing environmental datasets was by building a powerful geospatial data refinery along with SpaceTime™ (https://spacetime.blueskyhq.in/) and our dev portal (http://developer.blueskyhq.in). There was limited infrastructure available to support the delivery of geospatial datasets so we built it, leveraging open-source tools like Postgres, QGis, GDAL, k8s etc. While we have proprietary layers to our models, as a team of young developers, data scientists and designers, many self-taught, our cultural ethos stands firmly with FOSS and we plan to be a leading contributor to FOSS for climate action. The most significant step for us in that direction has been providing annual, country-wise data on biomass emissions to the Al Gore-led Climate TRACE (https://www.climatetrace.org/) inventory that can be used by the public via CC-BY-4.0 framework. As our business expands, we aim to open-source tools & innovations we have internally developed while building our infrastructure and have started that journey with the Raster Playground. (play.blueskyhq.in) Climate change is the most pressing challenge of our times, throwing at us various questions that need to be answered. This is not possible without data. Data helps us understand the problem and quantify the risk to various assets. Open source tools and data have made it possible for 20-year-old data scientists to access sophisticated satellite data to understand the changing planet and answer these questions. BSA is a testament to the fact that fighting climate change is not possible without FOSS.

uk: вхід без авторизації

name: Building the Bloomberg for Climate Data with FOSS


uk: Комп'ютерні науки

description: Cloud computing is revolutionizing the way companies develop, deploy and operate software and GeoSpatial software is no exception. With benefits of cloud based deployments range from cost savings to simplified management, flexibility, lower downtime and scalability of dynamic environments it is easy to understand why more and more companies are migrating their on premise systems to the cloud but cloud based setups have their own set of hurdles and challenges. The migration of the series itself can be challenging. Monitoring, debugging and scaling of applications are very much different than what you are used to. In this presentation we will share with you the lessons we have learned at GeoSolutions to tackle these problems and share some common patterns for the migration of on premise GeoServer clusters to the cloud. We'll share with you tips on: - best practices to migrate your existing GeoServer cluster to the cloud - insights on your geoserver cluster using centralized logging and Monitor plugin - avoid common bottlenecks to best set up a distributed scalable GeoServer cluster - work containers and container orchestrators like Kubernetes

uk: вхід без авторизації

name: Deploying and operating GeoServer: a DevOps perspective


uk: Комп'ютерні науки

description: The Scientific and Technical Center for Building (CSTB) built the first French database of buildings and houses to address climate change challenge, helping knowledge and decision making for massive retrofit. The pipeline factory intersects massive datasets (21 Millions buildings, ＞400 descriptors) and keeps adding new predictions and external datasets all the time. It allows to run analyses and predictions for all the climate change related indicators, such as housing price and energetic performance relation, heat wave impact, solar potential, etc.. While the first versions where a direct image of the classical datascientist’s approach -ie a massive dataframe driven by massive yaml config files and cryptic meta-templated scripts– ease of use and access performance soon became a limiting factor. This is a major concern since this dataset will be one long term foundation of derived information systems. Between brute force approach based on scaling resources up, and the old fashioned « data diet » normalization and optimization process, the truth is not easy to find. Abusing from cartoonish humor, this talk will try to explore the benefits of normalizing back hugely redundant geographic datasets and making public interfaces (public SQL model, API’s, vector tiles, OGC API’s) so that both end users can analyze efficiently this dataset, and the data manager team can rely on more stability using those good old’ database constraints.

uk: вхід без авторизації

name: How to deal with a massive geographic database when surrounded by datascientists?

name: Open Source Geospatial Foundation (OSGeo)


uk: Комп'ютерні науки

description: Vector tiles are changing the way we create maps. Client-side rendering offers endless possibilities to the cartographer and has introduced new map design tools and techniques. Let’s explore an innovative approach to modern cartography based on simplicity and a comprehensive vector tiles schema. After a short introduction or useful reminder to vector tiles, take a tour of their graphic capabilities through a series of original map design compositions. A variety of cartographic examples will be illustrated during this talk, with a particular focus on map display and performance. Rendering issues and technical limitations will also be put in perspective with pragmatic solutions or design alternatives. Get an overview of best practices for vector tiles cartography and learn about simple open-source recipes, towards advanced combinations of fills, patterns, fonts, and symbols. Selected layer parameters and style expressions will be discussed in a visual way and explained with basic syntax that you can take away.

uk: вхід без авторизації

name: Vector tiles cartography tips and tricks


uk: Комп'ютерні науки

description: In this presentation, we show how GeoServer-Cloud has matured into a production ready, cloud-native micro-services application. It has already been successfully deployed in production for three major organizations in their respective kubernetes environments. GeoServer-Cloud is a spring-boot/spring-cloud based micro services application built on top of GeoServer. The main goal of this implementation is to have an effective and easy way to scale the different services horizontally, splitting GeoServer geospatial services and API offerings into individually deployable components. All the services communicate with each other via a messaging queue. There’s no wait-time between configuration changes and their reflection across all services in the cluster, nor the need to reload the applications. The last year has not only been spent hardening the code, but also a lot of emphasis has been put on the deployment procedures. In this presentation we will explain how to deploy GeoServer-Cloud in a kubernetes environment. We will showcase the official helm chart that can be used to install it everywhere. GeoServer-Cloud allows per-service auto scaling and server resource dimensioning, hence optimizing each service based on its performance characteristics. We will discuss how to achieve good load balancing based on service metrics.

uk: вхід без авторизації

name: GeoServer-cloud: Cloud Native GeoServer in production environments


uk: Комп'ютерні науки

description: The National Land Survey (NLS) of Finland decided in the fall of 2020 to develop a national topographic data production system based on open source technologies and especially on QGIS client. Since then, many significant steps have been taken for us to be able to implement the MVP of the application for the mappers of the NLS at the start of 2024. Later on, we are planning to replace our digital elevation model production system with similar technologies which would enable us to replace the current mapping system by 2026. In this presentation I will talk about our system's architecture, the tools we are developing and furthermore, some insights that we have learned during this project. The application's architecture is based heavily on Postgres, where we run the main database from which the national topographic maps are made. The operators can access the main database via Job management-plugin and modify the database objects on the client (QGIS). These modifications (inserts, updates, deletes) are saved in the operators' work database, from which they can register these changes to the main database. Our first challenge was to design how more than 150 operators of the NLS are able to work using the same main database. We decided to use the client-web service architecture. The benefit of that is that we can use QGIS as such as it is and we can build all of the functions required for job management into the backend application. The job management plugin communicates with the web service and the conflicts between the different work databases are handled by a separate tool. With the tool, an operator can solve conflicts that are created by another operator editing the same objects. Currently, we are integrating stereo compilation with QGIS, which will enable the operators to measure objects from 3D aerial stereoscopic photos. The next steps are to develop comprehensive tools for quality assurance and to improve basic QGIS tools for selecting, editing and digitizing objects. The problem is that we have over a hundred different layers, therefore the default way to choose the layer is not sufficient for the operator. We also want to develop tools for real time quality checking so that the mapper would immediately know if a quality error occurs, making the general workflow smoother. Although some of the components are custom-made, our purpose is to publish those components that we recognize to be useful for other QGIS users. In addition, we have seen the value of multiple premade plugins to which we are planning to contribute as well. As a whole, NLS is currently looking for new ways to be a part of the open-source community.

uk: вхід без авторизації

name: Developing a topographic data production system based on open source


QGIS & PostGIS : Tips & Tricks

uk: Комп'ютерні науки

description: QGIS and PostGIS are now renown as one of the best combination to setup a GIS application. The support of PostGreSQL and PostGIS in QGIS have grown very mature and offers great features to deal with your database stored geographic data. It allows to create powerful business application easily without any advanced programming language skills, only plain SQL and a well configured QGIS. This presentation will showcase some of the interesting features you should be aware of in order to build the perfect GIS user application. I'll explain how to: - Properly configure relations between layers/tables, - Enable transactions (and whether or not you should do it), - Communicate from PostGreSQL to QGIS using notifications, - Deal with triggers using data dependencies, - Store your QGIS project and style information in a PostGIS database, - Output your processing result directly to your database, - Manage your database directly from the browser. These will be some of the key features that will be demonstrated along with a given use case.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: Over the past several decades a significant number of geospatial datasets have been published on the Web. Many of those datasets were published through implementations of classic OGC Web Service standards. As time has gone past, the architecture of web applications has evolved, propelled by new Web and Internet standards. This evolution of web application architecture has led to a revolution in how geospatial datasets are published on the Web. To ensure that the revolution in geospatial data publication has interoperability at its core, the Open Geospatial Consortium (OGC) has developed a series of Web Application Programming Interface (API) standards. The OGC API suite of standards is a family of specifications that have been designed as modular building blocks that spatially enable Web APIs that offer access to spatial data and implementations of geospatial algorithms. These revolutionary APIs make location information more accessible than ever before through the use of the OpenAPI specification for describing interfaces. The use of the OpenAPI specification means that implementations of OGC API Standards can describe themselves to levels of detail previously unachievable through the classic OGC Web Service standards. Such an ability to self-describe is significant because it has enabled software developers from a variety of disciplines to implement OGC API Standards to address the needs of their communities. This presentation will provide an overview of the background, current status, and future plans for the development of OGC API Standards. The presentation will describe plans for the development of resources that improve the ability of developers to implement OGC API Standards. The presentation will also present a selection of case studies of open source software that has been implemented or enhanced during OGC Innovation activities such as testbeds, hackathons, and sprints (including the 2022 Joint Code Sprint organised by OGC, OSGeo and the Apache Software Foundation (ASF)).

uk: вхід без авторизації

name: OGC API Standards: Past, Present, and Towards an Exciting Future


keywords: foss4g2022 generaltrack OpenData

uk: Комп'ютерні науки

description: Hey everyone, my name is Saheel Ahmed. I work as a senior data scientist at Blue Sky Analytics. We are a climate tech startup primarily focused on creating environmental datasets for better monitoring and climate risk assessment for various stakeholders across the globe. To achieve this, we are leveraging the potential of geospatial analytics by creating a catalogue of comprehensive and accurate climate data to drive sustainable decision-making. And all this is only possible because of the open-source tools & knowledge made publicly by the good folks organising the event. Greenhouse gas (GHG) emissions from biomass burning (which includes the combustion of forests, savannas, and croplands) play an important role in regional air quality, global climate change, and human health. In the year 2021, all the continents except Antarctica witnessed major wildfires. These enormous blazes some the size of a small country aren’t just destroying native forests and vulnerable animal species. They’re also releasing billions of tons of greenhouse gases into the atmosphere, potentially accelerating global warming and leading to even more fires. Accurate assessment of biomass burning emissions is paramount to understanding and modelling global climate change. By combining open-source tools with geospatial data, we present a global dataset that estimates the total GHG emissions due to biomass burning globally. We achieved this by linking satellite-based fire observations, aerosol optical depth (AOD), and vegetation type (based on land cover classification) to directly estimate how much carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) were emitted from each fire. We conducted further analysis of estimated emissions by comparing our estimates with existing datasets from NASA's global fire emissions database and ESA's Copernicus global fire assimilation system. Overall, our estimates agree well against both of these sources with an R2 score of 0.91, 0.71, and MAE score of 9, 14 MtCO2e/yr against GFEDv4.1s and GFASv1.2 respectively across 245 nations between 2015-2020. The dataset includes country-level estimates of gross GHG emissions across different vegetation types such as forest, cropland, shrubland, and grassland for the last 5 years. The dataset is currently a work in progress as we aim to add more features such as covering other landcover types, ground truth alternatives. The dataset and its documentation are available at https://github.com/blueskyanalytics/get-started. The dataset is also our contribution to the global coalition Climate Trace (climatetrace.org/), an independent group for monitoring & publishing GHG emissions across different sectors.

uk: вхід без авторизації

name: Use of open source tools to estimate global GHG emissions.


uk: Комп'ютерні науки

description: The Mapping Service at the Center for Urban Research at the City University of New York (CUNY) Graduate Center engages with foundations, government agencies, businesses, nonprofits, and academics to use spatial information and analysis to develop research projects. Our most recent set of web maps focus on the decennial redistricting process in the United States. Redistricting is often a complex and complicated process. Delays in publishing data from the 2020 Census due to COVID-19 shortened the time frame for redrawing legislative lines in many states. Given the often rushed nature of redistricting it was crucial to provide fair district advocates, journalists, and lawmakers with accurate maps and data shortly after the proposed districts became publicly available. In previous projects, we relied on proprietary back-end stacks using ArcGIS, Microsoft SQL, and the .NET framework. These products afforded a viable but inflexible solution to our GIS needs. The online mapping platform for ArcGIS is not as elegant as its open source counterparts, Microsoft SQL did not provide a solution for directly serving vector tiles, and each upgrade of Windows, IIS, and Visual Studio presented unique challenges. Last year we implemented a new back-end stack to connect our spatial databases to our web sites using FOSS solutions: QGIS, PostGres with PostGIS, Mapbox, and Nodejs. The result is a free, fully customizable solution that is easy to update, maintain, and migrate. We are currently using it in about a dozen applications to serve vector tiles and query demographic and other data. With our new workflow we were able to quickly upload dozens of map proposals, calculate metrics to analyze the potential impacts of each one, and present them on our website within hours of the data being made available to us.

uk: вхід без авторизації

name: Open Back-End for Vector Tile Based Web Apps


uk: Комп'ютерні науки

description: pgRouting not only allows to get routes for any kind of transportation, from 0 wheels to 18 wheeler. A road is closed? Calculate how can traffic be diverted. Don't get a result? Check if your graph is connected. Need to deliver to several clients? Traveling Salesperson problem helps to determine the route. Find out what is planned for version 4.0 that is a work in progress. Learn about the spin off for vehicle routing problems. pgRouting extends the PostGIS / PostgreSQL geospatial database to provide geospatial routing functionality. Advantages of the database routing approach are: - Data and attributes can be modified by many clients, like QGIS through JDBC, ODBC, or directly using Pl/pgSQL. The clients can either be PCs or mobile devices. - Data changes can be reflected instantaneously through the routing engine. - The “cost” parameter can be dynamically calculated through SQL and its value can come from multiple fields or tables.

uk: вхід без авторизації

name: Are you lost? Get pgRouting to find your way


uk: Комп'ютерні науки

description: The amount of data we have to process and publish keeps growing every day, fortunately, the infrastructure, technologies, and methodologies to handle such streams of data keep improving and maturing. GeoServer is a web service for publishing your geospatial data using industry standards for vector, raster, and mapping. It powers a number of open source projects like GeoNode and geOrchestra and it is widely used throughout the world by organizations to manage and disseminate data at scale. We integrated GeoServer with some well-known big data technologies like Kafka and Databricks, and deployed the systems in Azure cloud, to handle use cases that required near-realtime displaying of the latest received data on a map as well background batch processing of historical data. This presentation will describe the architecture put in place, and the challenges that GeoSolutions had to overcome to publish big data through GeoServer OGC services (WMS, WFS, and WPS), finding the correct balance that maximized ingestion performance and visualization performance. We had to integrate with a streaming processing platform that took care of most of the processing and storing of the data in an Azure data lake that allows GeoServer to efficiently query for the latest available features, respecting all the authorization policies that were put in place. A few custom GeoServer extensions were implemented to handle the authorization complexity, the advanced styling needs, and big data integration needs.

uk: вхід без авторизації

name: Processing and publishing big data with GeoServer and Azure in the cloud


uk: Комп'ютерні науки

description: The Re3gistry is an open source software for creating, managing and sharing reference codes in a consistent way. Released under the European Union Public License (EUPL) v.1.2, it is a key component ensuring interoperability in data infrastructures. The Re3gistry supports organizations in managing and updating “reference codes” through unique identifiers. Reference codes can be used for example to define sets of permissible values for a data field or to provide a reference or context for the data being exchanged. Examples are enumerations, controlled vocabularies, taxonomies, thesauri or simply ‘lists of things’. The Re3gistry provides a means to assign identifiers to such items and their labels, definitions and descriptions in different languages. It provides a user-friendly interface where labels and descriptions for reference codes can be easily browsed by humans and retrieved by machines, including the possibility of downloading them in different formats and exploiting the information using a REST API. The European Commission’s Joint Research Centre (JRC) started the development of the Re3gistry in 2014 to satisfy the interoperability requirements set by the INSPIRE Directive. In 2020, considering the high reusability of the tool beyond INSPIRE, the JRC released the code as open source. So far, the development of the Re3gistry has been supported by the European Commission under the interoperability actions ARE3NA and ELISE and, more recently, by the National Land Survey of Finland. In 2021, a second version of the Re3gistry software was released. This version v2.0, complemented by subsequent minor releases, introduced several new features such as a management interface to add and modify the status of items, and the capability to trace the full lifecycle of items following the workflow defined by ISO 19135 standard. The current stable release is v.2.3.0 released in March 2022. The INSPIRE registry (inspire.ec.europa.eu/registry) is currently the most popular implementation of the Re3gistry software. It is the central point of access to (currently) more than 7000 reference codes, available in 23 languages and several formats (HTML, ISO 19135 XML, JSON, RDF/XML, Re3gistry XML, CSV), grouped into different centrally managed INSPIRE registers. The content of these registers is based on the INSPIRE Directive, Implementing Rules and Technical Guidelines (as illustration, used to reference INSPIRE themes, code lists and application schemas). The Re3gistry is currently used by many organizations across European countries (Austria, Finland, France, Italy, Slovakia, Spain, The Netherlands and North Macedonia), different EU-funded projects and private organizations even outside Europe. Since 2021, the Re3gistry v.2.x is included in the OSGeo Live to facilitate discovery and use by the open source geospatial community. In 2022 the software will be also submitted as an OSGeo Community Project. Summing up, the Re3gistry is more relevant than ever to ensure semantical and organisational interoperability across any kind of systems, including Spatial Data Infrastructures (SDIs).

uk: вхід без авторизації

name: Re3gistry: Your interoperable open source tool for managing and sharing reference codes


GeoServer Feature Frenzy

uk: Комп'ютерні науки

description: GeoServer is a web service for publishing your geospatial data using industry standards for vector, raster and mapping. It powers a number of open source projects like GeoNode and geOrchestra and it is widely used throughout the world by organizations to manage and disseminate data at scale. What can you do with GeoServer? This visual guide introduces some of the best features of GeoServer, to help you publish geospatial data and make it look great! GeoServer has grown into an amazing, capable and diverse program - attend this presentation for: - A whirl-wind tour of GeoServer and everything it can do today; - A visual guide to some of the best features of GeoServer; - Our favourite tricks we are proud of! New to GeoServer - attend this talk and prioritize what you want to look into first. Expert users - attend this talk and see what tricks and optimizations you have been missing out on.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: QGIS releases three new versions per year and each spring a new long-term release (LTR) is designated. Each version comes with a long list of new features. This rapid development pace can be difficult to keep up with, and many new features go unnoticed. This presentation will give a visual overview of some of the best new features released over the last calendar year. This will be a mixture of important/popular features along with those which are easily overlooked or missed. Each highlighted feature will not simply be described, but will be demonstrated with real data. The version number for each feature will also be provided. This will let you know which new features are included in the LTR. If you want to learn about the current capabilities of QGIS this talk is for you! Potential topics include: Annotation layers * GUI enhancements * New Expressions * Point cloud support * Print layout enhancements * New renderers and symbology improvements * Mesh data algorithms * 3D * Editing

uk: вхід без авторизації

name: QGIS Feature Frenzy - What's New in the Last Year?


OSGeo AGM

uk: Комп'ютерні науки

description: The OSGeo Annual General Meeting

uk: вхід без авторизації


State of Bridge for QGIS

uk: Комп'ютерні науки

description: GeoCat Bridge for QGIS is a Python plugin that enables users to publish map layers as OGC data services (WM(T)S/WFS/WCS) to GeoServer or MapServer. It can also publish layer metadata to the GeoNetwork spatial catalog (CSW), linking service to metadata and vice versa, so that users can easily bind to a service from a catalog search result or find the relevant metadata for an exposed dataset. Bridge can also export metadata, symbology and geodata to local files, so you can modify them and/or upload them manually. Since its first official release at the FOSS4G in Bucharest (2019), GeoCat has been gradually improving the plugin. One of the most requested and anticipated changes to Bridge for 2022 relates to GeoServer workspace publication. The next upcoming major release involves some major UX changes, which will allow more control over a workspace. For example, users can soon add (or overwrite) single layers to an existing workspace, whereas in older versions all workspace data was removed prior to publication. We would like to take the opportunity to discuss the upcoming release, highlighting this and other new features and improvements.

uk: вхід без авторизації


20 Years of QGIS [community]

uk: Комп'ютерні науки

description: QGIS turned twenty this year. The first lines of code were written in mid-February of 2002 and the first time the code compiled and ran, it could do one thing: Connect to a PostGIS database and draw a vector layer. Quoting Gary Sherman - "The mythical man of QGIS that no one has ever met": This was the humble beginning of one of the most popular open-source GIS applications. GRASS GIS is of course the granddaddy of open source GIS, but the 20th birthday of QGIS is a testament to its longevity and commitment of all those who have made it what it is today. In this talk I'll share a walkthrough of the most game-changing features and events that shaped QGIS and its community in the past 20 years making it one of the top ten most important C++ open-source projects [1] and an overall amazing project to represent :) [1] phoronix.com/scan.php?page=news_item&px=OpenSSF-Criticality-Score

uk: вхід без авторизації


uk: Комп'ютерні науки

description: Climate change is here. heating, construction, cooling is estimated to contribute to 30% of the C02 emissions for France. And yet, we don't really have a database of those buildings. We have footprints by the French National Geographic institute, tax raising datasets on cadastral parcels, many derived datasets for energy consumption, performance certificates, but all of them are far away from a usable and centralized reference dataset. The national adress geolocation (BAN) project unlocked the key pivot database between all them. The Scientific and Technical Center for Building (CSTB) a public industrial and commercial company, decided to dedicated efforts to build a permanent reference dataset, and push it as an open database. The full stack is using open source technologies (Pandas / GeoPandas, to PostGIS, Apache Spark, MLflow, QGIS, MapLibre ...), and with massive datasets (21 Millions buildings, ＞400 descriptors). It allows to run analyses and predictions for all the climate change related indicators, such as housing price and energetic performance relation, heat wave impact, solar potential, etc.. As the first versions are now published, the next challenges are : - make the data easier to reuse - Push toward a official common identifier of each building, housing and parcels, through the BatID project and Etalab open government initiatives - Enrich the dataset with new statistics and predictions twice a year - Consolidate its economic rationales to make this viable on the long run This talk will also show cool dataviz and geoviz stuff for geonerds audience :)

uk: вхід без авторизації

name: Building a common building's(!) open dataset using FOSS4G, open data and open governement.


uk: Комп'ютерні науки

description: RapiD is an advanced Open Source map editor for OpenStreetMap built by the MapWithAI team at Meta. RapiD makes it simple to work with openly licensed geodata and AI-detected road, building, and landform features. For years the RapiD editor was based on a SVG rendering engine built with D3.js. As our users map the world in increasing levels of detail, and as more open data sources become available, our rendering tech has struggled to keep up with the massive amounts of data that we’re asking it to display in a browser-based JavaScript application. Our team recently converted this legacy rendering engine to instead use WebGL technology by leveraging the popular Open Source PixiJS game engine. The conversion from SVG to WebGL yielded a considerable performance boost, and the new WebGL-based renderer is up to the task of working with massive world-scale datasets and handling the increasing data density of OpenStreetMap. In this talk we share our progress on bringing new datasets into RapiD, tell the story of how we built a modern map editor on top of an Open Source game engine, and share our roadmap for the future of mapping.

uk: вхід без авторизації

name: Speeding up the RapiD map editor with WebGL and PixiJS


uk: Комп'ютерні науки

description: You would like many people from your team or crowdsourcing to fill data in your geodatabase. One way to do that is to make appealing, easy to use and well-constructed forms avoiding wrong inputs. Also, you do not want people to give up filling because the form is too long while in the same time you could automatically fill some entries based on others. With QGIS Desktop, it is possible to make great maps but also advanced forms by using expressions to control field visibility, default values, proposed values, constraints and more. It is very powerful but now how to share those forms to anybody whatever their device or operating system? Could it be possible to share a link for people to open and fill those forms in their web browser? Let’s see how you can get most of these features for your forms in web browsers thanks to QGIS Server and Lizmap.

uk: вхід без авторизації

name: Advanced QGIS forms into the web with Lizmap


TiTiler: Not just a tile server

uk: Комп'ютерні науки

description: During the last 2 years we've been working on TiTiler (developmentseed.org/titiler/), a dynamic raster tile server. Built on top GDAL/Rasterio, TiTiler is written in python and use FastAPI (fastapi.tiangolo.com) framework. TiTiler is an application that let you create raster tiles dynamically from raster datasets (e.g Cloud Optimized GeoTIFF) but also from Spatial Temporal Asset Catalog (STAC) or Mosaic (using MosaicJSON). It is also a set of python modules which can be used independently to create custom services. During this talk we'll explain the concept of dynamic tiling, what is TiTiler (and the libraries powering it), how it works and more important how users can customize and built their own dynamic tile server. We will also present project like TiTiler-PgSTAC which enables the creation of Mosaic tiles dynamically from a Spatial Temporal Asset Catalog (STAC) database, or eoAPI which is a full Earth Observation data service combining STAC database, STAC-FastAPI and a TiTiler in one easily deployable project.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: Orfeo ToolBox (OTB) is an open-source project for state-of-the-art remote sensing, made for large-scale image processing. It is written in C++ and a Python interface is available. However, the use of plain OTB in Python requires a lot of code; more than what a Python user is used to! pyotb aims at making the use of Orfeo ToolBox easy in Python. In this talk, discover: - how to run any application of OTB in just one line of code - how to build complex processing chains containing several applications in an intuitive way. - how to interact easily with NumPy and Tensorflow. - some pythonic features made for user convenience. - some functions written to mimic the behavior of some well-known NumPy functions: `pyotb.where`, `pyotb.clip`, `pyotb.all`, `pyotb.any`... and counting! OTB has an amazing pool of applications and can run on all types of computers: from resource limited laptops to high performance clusters. With pyotb, unleash the power of OTB in Python! We will make you love the way you can use OTB in Python. You can find more info on the project on the pyotb repository: gitlab.orfeo-toolbox.org/nicolasnn/pyotb

uk: вхід без авторизації

name: Pyotb: a pythonic extension of Orfeo ToolBox


uk: Комп'ютерні науки

description: TOSCA, also known as Toolkit for Open and Sustainable City planning and Analysis, was implemented by the Digital City Science group at Hafencity University Hamburg (HCU) as a joint venture with the German Association for International Cooperation (GIZ). The project – which has won the Hamburg Open Science Award in year 2020 –works very closely together with academic and local governments in India and Ecuador in order to develop use cases in the context of urban upgrading, disaster prevention, and participatory planning. The WebGIS application uses modern state-of-the art technologies like Docker, View.js, PyWPS, GrassGIS and Geoserver. The source code of the open source solution is hosted on Git repo. Moreover, user and admin manuals plus several step-by-step video tutorials were uploaded on the Vimeo video portal. In terms of analysis functionalities, TOSCA is equipped with buffer area, time map (service area analysis), query module (filter by categorical and numeric attributes) and volcanic eruption scenario analysis (equivalent with intersect: select features by geolocation). This project has been successfully implemented in India and Ecuador since October 2019. It supports investigations not only in regards to Indian slum upgrading issues, but also volcanic disaster mapping challenges in Ecuador. Further applications of TOSCA in Palestine has been kick-start in May this year. TOSCA can be deployed on multi-touch table or on virtual machine - through cloud hosting, and is designed for usage by non-GIS specialists. It targets diverse user groups ranging from local citizen to experts, the former implying participatory workshops and the later focusing on urban scenarios decision-making processes. Vimeo Tutorial Site: vimeo.com/user127753830 In order to promote the TOSCA Toolkit further, we encourage developers co-work with us to further develop on modules of the Toolkit.

uk: вхід без авторизації

name: TOSCA – A Novel GIS-Toolkit in Support of Sustainable Urban Development


uk: Комп'ютерні науки

description: ZOO-Project is a WPS (Web Processing Service) platform which is implemented as an Open Source project and following the OGC standards, it was released under an MIT/X-11 style license and is currently in incubation at OSGeo. It provides a WPS compliant developer-friendly framework to easily create and chain WPS Web services. This presentation gives a brief overview of the platform and summarizes new capabilities and enhancement available in the new version. A brief summary of the Open Source project history with its direct link with FOSS4G will be presented. The new release comes up with a brand new ZOO-Kernel Fast Process Manager and, with the approved standard OGC API - Processes part 1: core. The new functionalities and concepts available in the latest release will be presented and described, also highlight their interests for applications developers and users. Apart from that, various use of OSGeo software, such as GDAL, GEOS, PostGIS, pgRouting, GRASS, OTB, SAGA-GIS, as WPS services through the ZOO-Project will be presented. Then, the ongoing developments and future innovations will be explored.

uk: вхід без авторизації

name: ZOO-Project: News about the Open WPS Platform


uk: Комп'ютерні науки

description: Vector tile map is now industry standard and general-purpose schema is available on OpenMapTiles project. But if the features that people focus on in your own country are different from the default schema? We developed styles to cover and highlight Japanese authentic geographic attributes such as railways, hot springs, and religious facilities with an improved OpenMapTiles schema. The styles are available on MapTiler Cloud as MIERUNE styles globally. In the process, we developed some useful tools for vector tile styling. One is a style-competing tool that makes it cartographers easy to compare two versions of styles interactively. Another is a kind of style management tool using git that visualizes diff of style.json and takes screenshots automatically. Structured approaches of planning and implementation of vector tile styling are not much shared. In this talk, we will speak about how to enrich the styles for your own country and enhance the styling process for vector tile cartographers.

uk: вхід без авторизації

name: Enrich styles and enhance styling process with OpenMapTiles

name: Open Source Geospatial Foundation (OSGeo)


uk: Комп'ютерні науки

description: The Re:Earth project grew from the idea of, "What would be possible if anyone, anywhere could access the digital Earth's potential?". To make this a reality, we knew Re:Earth needed to be a no-code solution. But more than that, we needed to make sure hardware and OS requirements wouldn't get in the way, which is why Re:Earth is a fully web-based application. _*Re:Earth allows you to manage, edit, compute and visualize a multitude of geographic information including 3D data with no coding required.*_ We knew projects as well as data would need to be shareable so we have both project publishing and data exporting. Publishing a project is easy and gives users the chance to opt-in or out of SEO, change their URL and setup publishing to their own domain. Exporting data is easy and supports many of the most common file formats seen in GIS. It is also the first WebGIS to feature a plug-in system that runs in the browser. Today, we are focused on solving a problem people face in maintaining, organizing, and managing a wide variety of data, by developing Re:Earth into a general-purpose data management system that can handle all types of data, and one that can be integrated with the user's existing systems. Our desire has always been to open Re:Earth to the OSS community, to build a global community around the vision of Re:Earth, and to provide and disseminate the value we create with our contributors to the wider society. The first step to making this happen was Resium, a popular OSS package that allows developers to use Cesium with React. With Resium we have been able to write Re:Earth's codebase with React and Typescript on the front end. As the main backend language we chose Go. By using these modern languages we have kept Re:Earth highly maintainable and scalable and hope that other developers will find contributing to it easy.

uk: вхід без авторизації

name: Vision and Challenge of Re:Earth - an open source WebGIS platform using Cesium


State of MapServer 2022

uk: Комп'ютерні науки

description: MapServer is one of the founding OSGeo projects, and is used for publishing spatial data and interactive mapping applications to the web [1]. This talk provides an overview of new developments for existing users, and to show the potential of MapServer for those yet to try the software. We'll review migrating to the new MapServer 8.0 release [2], using the new OGC API, highlighting lesser-known features, optimizing performance, and reporting news from the MapServer ecosystem. MapScript [3], a scripting interface to MapServer provided in several languages such as Python, PHP, and C#, will also be covered. This talk will give an overview of current and planned development for MapServer and its related project MapCache, a tile server that speeds up access to map layers [4]. Finally, we'll look at how to become involved in the MapServer community both as a user and as a developer. [1] mapserver.org/ [2] github.com/mapserver/mapserver/wiki/MapServer-8.0-Release-Plan [3] mapserver.org/mapscript/index.html [4] mapserver.org/mapcache/

uk: вхід без авторизації


uk: Комп'ютерні науки

description: Our digital maps are not always up to date with the real world. New road constructions and road blockages could reduce the accuracy of the map data. In a logistics company like Gojek that serves millions of users per day in South East Asia, the core undertaking revolves around routing and ETAs. Any inaccurate local map data can lead to a direct negative impact on business metrics. So how do we ensure that map inconsistencies are detected and fixed promptly to minimise interference of our services? When manual detection is labor intensive and not scalable to millions of road networks in vast regions, how can we effectively automate this at scale? This talk is a story of how we, at Gojek, built a pipeline that uses bad customer experience as the trigger to identify potentially faulty data in OpenStreetMap. Our solution makes use of noisy GPS traces and Overpass, an open source tool, to automate this detection. This solution enabled us to identify 100s of potential issues per day, categorise them, associate business impact to each map issue and allow our map analysts to fix them seamlessly.

uk: вхід без авторизації

name: Use of FOSS4G at Gojek to automate map error detection at scale


uk: Комп'ютерні науки

description: In recent years, several Python packages (e.g. xarray, rasterio) have evolved around more basic software libraries such as netCDF4 or GDAL for accessing geospatial data. These packages allow to work with all kind of data formats (e.g. GeoTIFF, NetCDF, ZARR) providing the data in array format (NumPy, xarray) and constitute a fundamental part of any scientific analysis or operational task. However, they do not offer full flexibility when working with Earth Observation (EO) datasets. The multidimensional complexity of EO data (i.e. space, time, bands) is often resolved by distributing dimensions across many files and thus not always easy to access. An important step forward to streamline EO data access has been the Open Data Cube (ODC) toolbox, which utilizes predefined dataset configurations and file-based indices stored in a database. With this setup, ODC enables an easy and uniform access to multidimensional geospatial datasets. Still, users are often confronted with a great variety of data formats, and files being distributed over different systems. This can pose a hurdle when working with ODC, especially if one wants to process a new stack of geospatial data, where the extra overhead of a database can stall swift progress. In order to close this gap, the yeoda (''your earth observation data access'') Python software package aims to resolve this shortcoming by offering a similar interface as ODC, but allowing to interact with geospatial data on a lower level. It relies on two other Python software packages developed by TU Wien: geospade (definition of geospatial properties of a dataset, e.g. geometries), and veranda (read/write access to a variety of raster and vector data formats, e.g. GeoTIFF). This modular setup ensures a clear separation of concerns, specifically between geospatial operations and I/O tasks, yielding a homogenized interface independent from the actual data format. For example, geospatial operations based on tiled EO raster datasets can be easily performed across tile or file boundaries. Data access is then realised in veranda, which combines geometric properties with I/O objects listed in a table. On top of geospade and veranda, yeoda acts as a communication layer between files stored on the file system and data objects by adding additional dimensions to the data table, such as common metadata or file name entries. Thus, one can filter multiple files by their attributes (e.g. time, bands, variable names, satellite platform) before accessing the data. Hence, yeoda guarantees the necessary freedom to apply arbitrary algorithms on manifold data formats, while simultaneously supporting scalability by means of parallelised I/O operations. Despite ODC's tremendous value for accessing EO datasets through large scale operational services, yeoda introduces a new level of data interaction making it an indispensable tool for the EO user community. When taking a look on recent advancements in interoperable cloud-based processing via the openEO API, yeoda could be utilized as a slim back-end library to lower the hurdle of sharing new EO datasets and to foster scientific exchange.

uk: вхід без авторизації

name: yeoda: your earth observation data access


uk: Комп'ютерні науки

description: The Data Operations Systems and Analytics team at NYC DOT’s primary mission is to support the data analysis and data product needs relating to transportation safety for the Agency. The team’s work producing safety analysis for projects and programs typically involves merging data from a variety of sources with collision data, asset data, and/or program data. The bulk of the analysis is performed in PostgreSQL databases all with a geospatial component. The work necessitates ingesting input data from other databases, csv/excel files, and various geospatial data formats. It is critical that the analysis be documented and repeatable. Moving data around, getting external data into the database, transforming it, geocoding it etc., previously occupied the bulk of the team’s time before, reducing capacity for the actual analysis. Additionally the volume of one-off and exploratory analyses resulted in a cluttered database environment with multiple versions of datasets with unclear lineage and state of completeness. Modeled on the infrastructure as code idea, we began building a python library that would allow us to preserve the entire analysis workflow from data ingestion to analysis and to output generation in a single python file or Jupyter notebook. The library began as a way to reduce the friction and standardize the process of ingesting external data into the various database environments utilized. It has since grown into the primary method to facilitate reproducible data analysis processes that includes the data ingestion, transformation, analysis, and output generation. The library includes basic database connections, and facilitates quick and easy import and export from flat files, geospatial data files, and other databases. It provides both inferred and defined schemas, to allow both quick exploration and more thoroughly defined data pipeline processes. The library includes standardization of column naming, comments, and permissions. There are built in database cleaning processes, geocoding processes, and we have started building simple geospatial data display functions for exploratory analysis. The code is heavily reliant on numpy, pandas, GDAL/ogr2ogr, pyodbc, psycopg2, shapely, and basic sql and python. The library is not an ORM, but occupies a similar role, but geared towards analytic workflows. The talk will discuss how the library has evolved over time, the functionality and use cases in the team’s daily workflows as well as where we would like to extend the functionality and open it up for contributions. While the library is not currently open source, we are actively working on creating an open version and migrating to Python 3.x. This library has greatly improved the speed and simplicity of conducting exploratory analysis and enhanced the quality and completeness of the documentation of our more substantial data analytics and research. The library should be of interest and utility for anyone working with data without the support of a dedicated data engineering team to facilitate the collection of multiple datasets from a variety of formats, as well as anyone looking to standardize their data analysis workflows from beginning to end.

uk: вхід без авторизації

name: Building a data analytics library in Python


uk: Комп'ютерні науки

description: Mapping is time-consuming and requires a high volume of a workforce when it comes to keep maps up to date periodically. This brings the need of finding alternative approaches to keep maps up to date. Mobile mapping is the process of collecting geospatial data from a mobile vehicle using a 360º camera, laser scanner, GPS/IMU positioning system, and other sensors. Many devices now include a geotag for every photo captured, and GPS accuracy can have major effects on the quality of street-level imagery and derived data. Join us in an exploration of the different accuracy levels of GPS-enabled cameras, where we will take a look at how different devices compare, and what varied levels of GPS accuracy look like both for image location and for data extracted using computer vision and structure from motion. Understanding the differences between devices is an important step in planning street-level imagery capture, as it will align your expectations with the advantages and limitations of the hardware you use. We tested various devices and will share the results of our investigation, with the aim of equipping you to capture street-level imagery with the tools and methods that fit your needs.

uk: вхід без авторизації

name: The most accurate cameras to generate map data from street-level imagery


uk: Комп'ютерні науки

description: We present _dask-geomodeling_: an open source Python library for stream processing of GIS raster and vector data. The core idea is that data is only processed when required, thereby avoiding unnecessary computations. While setting up a dask-geomodeling computation, there is instant feedback of the result. This results in a fast feedback loop in the (geo) data scientist’s’ work. Big datasets can be processed by parallelizing multiple data queries, both on a single machine or on a distributed system. ### Abstract In geographical information systems (GIS), we often deal with data pipelines to derive map layers from various datasets. For instance, a water depth map is computed by subtracting the digital elevation map (DEM) from a water level map. These procedures are often done using open source products such as PostGIS and QGIS. However, for medium to large datasets (＞ 10 GB) the extent of these analyses are costly due to memory restrictions and computational cost. As a rule, these issues are tackled by manually cutting the dataset into smaller parts. However, this is a tedious and time-consuming task. In case one needs to this regularly, this is not feasible. We present the open source Python library _dask-geomodeling_ [1] to solve this issue. Instead of a script, dask-geomodeling requires a so-called “graph”, which is the definition of all operations that are required to compute the derived dataset. This graph is generated by plain Python code, for instance: ``` plus_one = RasterFileSource('path/to/tiff') + 1 ``` Note that these operations are lazy: there is no actual computation done and therefore the above line executes fast. Only when actual data is requested: ``` plus_one.get_data( bbox=(155000, 463000, 156000, 464000), projection='epsg:28992', width=1000, height=1000 ) ``` An array containing the data is computed. No need to load the whole TIFF-file in memory if you only use a small part! The computation occurs in two steps. First, a computational graph is generated containing the required functions. While generating the computational graph, the operations may be chunked into smaller parts. Second, this graph is evaluated by _dask_ [2], using any scheduler (single thread, multithreading, multiprocessing, distributed) that is provided dask. This library is open source under the name “dask-geomodeling” and is distributed on Github, PyPI, and Anaconda. A hosted cloud version is also available under the name Lizard Geoblocks [3]. Currently, we have implemented a range of operations for rasters, vectors, and combinations. The community is welcome to use our library, benefit from it, and expand it!

uk: вхід без авторизації

name: Agile Geo-Analytics: Stream processing of raster- and vector data with dask-geomodeling


uk: Комп'ютерні науки

description: The shift to using vector rendering has enabled maps to take a leap forward compared to using raster data. It is now possible to offer a much richer experience by performing styling, processing and filtering directly in the client. Coupled with tiled rendering, it is now feasible to work with huge datasets directly in the web browser. This presentation will look at how applications can be built using the open source deck.gl library, with a focus on displaying vector tilesets, styling and filtering data on the client, with acceleration provided by the GPU. We will look at how deck.gl elegantly works with vector tiles and show how maps and visualisations can be styled using a few lines of code. We will also explore tools provided by the CARTO platform, which bring these features to those without programming experience, via a web-app. A brand new feature of deck.gl will be presented: the MaskExtension is a powerful tool that allows one dataset to act as a geospatial mask for another. For example this can be used to let the user select features on a map using a lasso tool, or to select map features based on a geospatial bound. All at 60fps on the client.

uk: вхід без авторизації

name: Fast rendering from vector tiles in deck.gl


uk: Комп'ютерні науки

description: The FunctionalScope software builds on the concept of the CityScope, developed by the MIT Media Lab City Science Group. The FunctionalScope supports urban planners in the functional planning phase of new neighborhoods, the phase in which a competition design proposal is refined in preparation for creating a binding land use plan (Bebauungsplan).  The tool offers a 3D view of the new urban design, vector(ized) data of the architectural designs, embedded into a MapLibre based application in the browser. Several near-to-realtime APIs offer the opportunity to evaluate a neighborhood’s design performance in terms of pedestrian flows, wind-comfort and traffic noise. Each simulation allows the user to set custom scenario criteria to enable to, for example, assess different policy and design strategies for the neighborhood such as pedestrian access to private land, speed limits on city streets, or simulate wind-comfort in for various wind conditions. In addition to the web-interface for detailed planning stages, we have developed a tangible table, which allows users to iteratively generate new spatial configurations using 3D-printed buildings. Simulations are run for the designs created on the table, too. The entire stack is built on open-source software. We have used this tool in cooperation with the City of Hamburg (HafenCity GmbH) during the planning process of a new waterfront-neighborhood, Grasbrook. The FunctionalScope is designed to in a generic manner and twill be used in the planning of at least one new neighborhood-scale urban development project in Hamburg. This talk will present the tech stack behind the tool: starting from the translation of architectural into geospatial data (geojson), covering the 3D neighborhood visualization in MapLibre and presenting our open-source near-to-realtime simulation APIs. Moreover, the technology behind the tangible planning table, based on an infrared camera, ArUco markers and Unity will be explained. The talk concludes with lessons learned when developing and applying such an innovative tool to support a new neighborhood-scale development project.

uk: вхід без авторизації

name: FunctionalScope - Interactive real-time simulation tool for neighborhood planning


uk: Комп'ютерні науки

description: ## The Problem Let's assume you have an attribute-focused table, but you would still like to see a thumbnail of the associated geometry. Or more generally: How to dynamically render polygon geometries in a HTML page without any mapping library. *Enter ST_AsSVG (PostGIS function)!* ## Context Last year I showed how we display geo data in our webapps using vector tiles (ST_AsMVT) (YouTube: watch?v=s_dWBOiuFiY&t=139s). This year I will explain how we apply ST_AsSVG of PostGIS on database records to *create beautiful geo-infographics* in pure HTML. The result is a geo-visualization similar to this one: Comparison maps of Australian Cities (Size, Population) (imgur.com/OQClpbc). The trickiest part will be the sizing of the SVG objects (viewport vs. viewBox (webdesign.tutsplus.com/tutorials/svg-viewport-and-viewbox-for-beginners--cms-30844)). ## Content The talk will contain some theory on SVG. It will then show basic setups for FastAPI, SQLModel, Jinja2 and, of course, PostGIS. All code will be made available via GitHub. ## Aim After the talk you will master sizing of SVG and be capable of creating your own dynamic geo-infographics directly from data stored in your PostGIS database.

uk: вхід без авторизації

name: Geo-Infographics created dynamically from PostGIS using ST_AsSVG


uk: Комп'ютерні науки

description: Farmers and herders in the West African Sahel are critically vulnerable to climate shocks and need access to climate information to secure their livelihoods. Herders use data on pasture and water availability to move their livestock and farmers need weather predictions to plan their planting. While satellite imagery has made much of this information readily accessible to the spatial community, few channels exist to transmit this information to herding communities. As a result, climate data has become more powerful than ever before, yet mostly inaccessible to those who depend on this information for their livelihoods. This talk goes over the lessons of a programme that seeks to bridge this gap. GARBAL is a call center that uses Copernicus Earth Observation imagery and field data to provide farmers & herders with information on pasture, water and markets in Mali, Niger and Burkina Faso. GARBAL was first developed in 2015 and this talk will provide lessons from several years of practice. The GARBAL interface is built on mapserver and uses automated scripts to download and treat imagery from Sentinel 2 and Meteosat which then display information on pasture conditions and water availability. Field data is routed through a network of local data collectors who provide weekly updates on livestock conditions and market prices. In addition to an interactive map, the interface provides user-friendly textual outputs that summarize all the layers for any area of interest on the map, which allows call center agents to quickly provide data to callers. The talk will share lessons from the technical and programmatic aspects of the project. The technical side will go over the architecture of the data treatment, demo the interface, talk about successes and failures and show how you can play with the data yourself. The programmatic side focuses more on how the user needs evolved over the years, techniques for translating GIS data into information useful to farmers and herders, operating in areas of active conflict and how EO data fits into existing centuries-old traditional data collection systems in the Sahel.

uk: вхід без авторизації

name: Sharing EO data with farmers and herders in the West African Sahel: Lessons from the GARBAL program


uk: Комп'ютерні науки

description: GeoServer is a well-established multiplatform, open-source geospatial server providing a variety of OGC services, including WMS (view services), WFS and WCS (download services) as well as WPS (spatial data processing services). Among the open-source GIS web servers, GeoServer is well known for the ease of setup, the web console helping the administrator to configure data and services, the variety of OGC services available out of the box, as well as the rich set of data sources that it can connect to (open source, such as PostGIS as well as proprietaries, such as ArcSDE, Oracle or ECW rasters). GeoServer also provides several OGC APIs, including the OGC API - Features which recently attracted the interest of the INSPIRE community. As far as the INSPIRE scenario is concerned GeoServer has extensive support for implementing view and download services thanks to its core capabilities but also to a number of free and open-source extensions; undoubtedly the most well-known (and dreaded) extension is App-Schema which can be used to publish complex data models (with nested properties and multiple-cardinality relationships) and implement sophisticated download services for vector data. Based on the feedback of App-Schema users collected over the years, a new generation of open-source mapping extensions have been implemented in GeoServer: Smart Data Loader and Features Templating, these extensions are built on top of App-Schema and ease the mapping of the data models by allowing us to act directly on the domain model and target output schema using a what you see is what you get approach. This presentation will introduce the new GeoServer Smart Data Loader and Features Templating extensions, covering in detail ongoing and planned work on GeoServer. We will also provide an overview about how those extensions are serving as a foundation for new approaches to publishing complex data: publishing data models directly from MongoDB, embracing the NoSQL nature of it, and supporting new output formats like JSON-LD which allows us to embed well-known semantics in our data. Eventually, real-world use-cases from the organizations that have selected GeoServer and GeoSolutions to support their use cases will be introduced to provide the attendees with references and lessons learned that could put them on the right path when adopting GeoServer.

uk: вхід без авторизації

name: Publishing INSPIRE datasets in GeoServer made easy with Smart Data Loader and Features Templating


uk: Комп'ютерні науки

description: Although GRASS GIS has been used for big data processing for a while now, you may think that some esoteric knowledge is needed to take full advantage of its computational power. The purpose of this talk is to demonstrate simple ways to parallelize your computations in GRASS GIS, that are applicable whether you are working on your laptop or HPC. I will give an overview of the state of parallelization of individual tools, show benchmarks, and introduce you to other GRASS GIS parallelization tricks. I will use examples relevant to land change modeling and share our experience with simulating urban growth at 30m pixel across the contiguous United States (16 billion cells) using FUTURES simulation implemented in r.futures addon. This talk is for all levels of expertise, although basic Python or GRASS GIS knowledge will be advantageous. GRASS GIS is a well established, all-in-one geospatial number cruncher with Python interface, command line, and GUI, with new major version 8.0 released in spring 2022. FUTURES is an open source urban growth model specifically designed to capture the spatial structure of development. It can accommodate the input of a variety of datasets with different spatial extents and can be coupled to other models. FUTURES is implemented in r.futures GRASS GIS addon.

uk: вхід без авторизації

name: Tips for parallelization in GRASS GIS in the context of land change modeling


QGIS Data Versioning with Kart

uk: Комп'ютерні науки

description: Maybe you've heard of Kart (kartproject.org), the great new geodata versioning tool from the team at Koordinates? But did you know that Kart also has a QGIS plugin so you can do _real_ data versioning without needing to leave QGIS? In just 5 minutes we'll demonstrate how to import data into a new Kart repository, make and review some changes, merge a branch, and push everything to a remote server. All from QGIS! — We’re drowning in data, but the geospatial world lags badly behind in versioning tools compared to our software counterparts. Kart (https://kartproject.org) is solving this with a practical open tool for versioning datasets, enabling you to work more efficiently and collaborate better. Kart allows you to quickly and easily manage history, branches, data schemas, and synchronisation for large & small datasets between different working copy formats, operating systems, and software ecosystems. Modern version control unlocks efficient collaboration, both within teams and across organisations meaning everyone stays on the same page, you can review and trace changes easily: ultimately using your time more efficiently.

uk: вхід без авторизації