The tutorials will be run during the symposium

TU 1:  Approaches for simplifying 3D data exchange between systems

This tutorial will examine a range of techniques for simplifying the problem of exchanging data between different systems using 3D information as a case in point. 3D data is of interest because different systems use quite different approaches for 3D depending on application needs, yet common semantics need to be established when assessing things like building permits.

The techniques to be explored are:

    1)  Profiling to limit scope and simplify exchange specifications

    2)  “Semantic uplift” to match different schemas to a common model

    3)  Reusable schema “Building Blocks” for common patterns such as 3d topology

The CHEK project and others will be used as case studies and tutorial participants will be introduced to open source tooling to help with these approaches.

Duration: 1.5 h

Teacher: Rob Atkinson (OGC)

Tutorial organised by ISPRS WG IV/1

TU 2:  Building an Underwater Heritage VR Experience with Unity

The Unity game engine is one of the most widely used platforms for displaying content in virtual reality thanks to its cross-platform functionality and user-friendly interface that caters to novice and veteran developers alike. In this tutorial, you’ll learn the basics of how to build a simple underwater heritage photogrammetry VR viewer in Unity that can display both surface meshes and point clouds. We’ll cover project setup and configuration, along with VR interactions and mixed reality integration. The tutorial will focus on developing for the Meta Quest virtual reality headset, but Unity’s cross-platform architecture means that the skills you learn will allow you to build experiences for other head mounted displays, as well as desktop and smartphone applications.

Presenter:  Dr Michael Ovens, HIVE, Curtin University.

TU 3: Uncovering Earth System Dynamics with multivariate EO Data and AI

Addressing global challenges such as climate change and answering complex research questions about the Earth System rely on scientific communities working across disciplinary and institutional boundaries, supported by effective access to heterogeneous multi-source Earth Observation science data, knowledge, and computing infrastructures.

DeepESDL – ESA’s Deep Earth System Data Laboratory, is a platform providing analysis-ready data cube in a powerful, virtual laboratory to the Earth Science research community. DeepESDL offers a full suite of services to facilitate data exploitation, share data and source code, and publish results. Special emphasis is put on improving the support for machine learning and artificial intelligence approaches, which includes the preparation of AI-ready datasets, providing a programming environment with relevant libraries and packages, and the resources to execute processing pipelines.

This hands-on training will introduce participants to the DeepESDL (Deep Earth System Data Lab), and will make practical use of this AI-ready, collaborative environment. The participants will be guided to explore the capabilities of the DeepESDL including the creation of data cubes from open earth observation datasets, applying various data analysis techniques and exploring AI approaches to extract information from multi-variate datasets.

For this hands-on tutorial, participants will be provided access to the DeepESDL sponsored by the European Space Agency. Pre-registration of participants is necessary.

Duration: 1.5 hours

Presenters:

TU4 - Editorial AB meeting Geospatial-Information Science

TU 5:  Advancing Air Quality Research and Public Awareness Through Innovative Geospatial Technologies

Urban and industrial regions frequently encounter stagnant air patterns caused by geographic characteristics, intensifying pollution from diverse origins. Elevated concentrations of PM, O3, NO2, and SO2 contribute to health concerns. Employing a data-driven strategy utilizing pollutant levels and meteorological and morphological factors will facilitate environmental state modeling and spatial mapping. The approach we propose integrates IoT and EO technologies, leveraging geo-intelligence and implementing XR technologies for virtual visualization. It aims to raise societal consciousness and foster a healthier community.

The tutorial is divided into two parts:

In the first part of the tutorial, innovative techniques will be demonstrated for creating open data cubes containing air quality information. These data cubes result from processing satellite-based and model-based data. To monitor air pollution and analyze exposure patterns, a combination of satellite-based, model-based, and ground sensor data will be utilized. The research emphasizes digital and open data sources for pollutants and meteorological variables, accessible programmatically with the highest space-time resolution.

In the second part, attention will turn to XR solutions, which will be unveiled following the development of meticulous spatial models derived from EO/IoT inputs regarding air quality information. This section will delve into wearable and mobile applications working in XR 3D environment, technical implementation using data interoperable and updated from GIS and the definition of rules and standard data layer to feed the application with real-time data.

Duration: 1.5 h 

Teachers: Maria Antonia Brovelli (part 1) and Eva S. Malinverni (part 2) 

TU 6:  Creating Immersive GIS Experiences with XR Technology and Real World Data

Description: Have you ever been intrigued by the possibility of developing applications that not only offer an immersive GIS experience but also enable users to navigate and interact within a virtual environment of digital twin or overlay real-world visuals with geo-spatial data through smartphone cameras in real-time? This comprehensive tutorial is designed to guide you through the process of building augmented reality (AR) and virtual reality (VR) applications by leveraging game engines alongside the ArcGIS Maps SDK for Unity or Unreal Engine.

In this tutorial, we will delve into:

     1) A quick introduction to game engine editors and the ArcGIS Maps SDK package dependency. 

     2) An exploration of exemplary projects available in GitHub's public repositories which can be used to boot strap application creation.

     3) The step-by-step creation of AR applications compatible with both iOS and Android smartphones, bringing geo-spatial data to life right before your eyes.

    4) The development process for VR applications that can be deployed on desktops and experienced through VR headsets, offering a fully immersive geo-spatial experience.

    5) A demonstration of select projects to showcase the potential and impact of integrating GIS with XR technology.

Join us to unlock the potential of cutting-edge technology in creating immersive, interactive maps and environments that bridge the gap between the digital and the physical worlds.

Presenter: Dr Morakot Pilouk, 

TU 7: Collecting data in the field with free & open source geospatial tools: QGIS, QField, and Mergin Maps

In recent years, not one, but two excellent QGIS-based mobile apps for field geospatial data collection have gained a large following: QField and Mergin Maps. Both apps are free & open source and can function entirely offline, with cloud-based utilities for syncing field data to a central location.

In this tutorial, we'll:

    1） walk through the process for setting up a data collection project in QGIS, with offline base maps, the ability to capture photos, and field-friendly data capture forms with dropdown lists, constraints, and real-time data validation

   2） get some fresh air, taking our project into the field with a brief walk around Esplanade Park in Fremantle

   3） return to our home base, where we'll sync our field data on a cloud platform

Participants are asked to bring a laptop with a recent version of QGIS, and a mobile device with either QField or Mergin Maps installed. We'll get in touch in advance to provide further details.

Presenters: Grant Boxer, John Duncan, John Bryant (FOSS4G Perth)

Duration: 3h or 2.5h (TBD)

TU 8:  AI for Geospatial Science

Motivation:

In recent years, Artificial Intelligence (AI) has attracted more and more attentions from the communities of Geospatial Science, particularly after the advent of Deep Learning technology. On the topic of AI for Geospatial Science, a number of special issues have been published and special workshops has been held, various new terminologies have been created such as GeoAI, GeospatialAI, MapAI, AI Cartography and AI GIS.

On 30 Nov 2022, OpenAI has launched ChatGPT, which has impressive abilities of language understanding, reasoning and expression, as well as considerable knowledge. On 14 March 2023, OpenAI has launched GPT-4, which is a large multimodal model that “exhibits human-level performance on various professional and academic benchmarks”, marking a breakthrough in artificial intelligence. Such technologies have also been applied in geospatial science, resulting in GeoGPT, MapGPT and Image GPT. 

As GPT-4 is moving towards artificial general intelligence (AGI), it will have great impact on geospatial science. It is therefore appropriate to have a tutorial to discuss the relevant issues, such as

    1) AI-empowered spatial data handling,

    2) AI-empowered spatial representation and visual understanding,

    3) AI-empowered spatial cognition and spatial reasoning,

    4) AI-empowered spatial information service,

    5) AI-empowered modeling of dynamic spatial systems,

    6) Hybrid computing theory and methods for AI in Geospatial Science,

    7) How GPT will shape the discipline of geospatial science;

    8) Research agenda for GPT-empowered Geospatial Science.

Chair: Prof. Zhilin Li, Southwest Jiaotong University, China

TU 9:  3D spatial modeling and intelligence for scene-realistic analysis and digital twin

Motivation:

This tutorial will examine a range of techniques for solving the problem of 3D modeling and reconstruction in digital twins using geospatial information, analytics and intelligence with following goals:

    1) To enhance the understanding and application of spatial modeling and digital twin methodologies in scene-realistic 3D analysis among researchers, experts, and industrial professionals.

    2) To offer a platform for the exchange of innovative ideas and the latest research outcomes in the field of spatial modeling, 3D analysis, and digital twin technologies.

    3) To foster advancements in technological tools and methodologies leveraged in spatial modeling and digital twins, stimulating future cutting-edge research and development.

    4) To encourage collaboration between academic, governmental, and industrial entities, thereby driving innovation and practical applications within the field.

    5) To stimulate meaningful dialogue around the challenges, opportunities, and future directions of spatial modeling and digital twin implementations across diverse sectors.

The topics to be explored are:

    1) "Enhancing Spatial Intelligence: The Future of 3D Analysis": Exploring advancements in spatial modeling tools and techniques for improved scene-realistic 3D analysis.

    2) "Digital Twin Technology - Bridging the Gap Between Virtual and Physical Worlds": Discussing the evolution, applications, and future of digital twins in diverse fields.

    3) "The Synergy of Spatial Modeling and Digital Twins": Examining the benefits, challenges, and best practices of integrating spatial modeling with digital twin technologies.

    4) "Spatial Intelligence in Real-World Applications": Highlighting exciting case studies where meticulous spatial modeling and digital twins have made significant impacts.

    5) "The Role of Artificial Intelligence in Spatial 3D Modeling and Analysis": Analyzing the transformative impact of AI on spatial modeling, scene-realistic 3D analysis, and the development of digital twins.

Duration: half day 

Chair: Prof. Bisheng Yang, Wuhan University, China