“Build and visualize your own raster data cube”
Leandro Parente, Murat Sahin;
Workshop proposal
Raster data cube is a four-dimensional array with dimensions x (longitude / easting), y (latitude /northing), time, and bands sharing a: (1) single spatial reference system, (2) constant spatial cell size, (3) constant temporal duration, (4) temporal reference defined by a simple start and end date / time, resulting in a single attribute value for every dimension combination. Building a data cube consists basically in converting raw irregular raster data into a regular and dense structure, which may include information loss and needs to consider user definitions and application restrictions.
“Building a Digital Twin Earth for the Water Cycle: State of the Art and Challenges”
Luca Brocca;
Workshop proposal
Climate change is profoundly affecting the global water cycle, increasing the likelihood and severity of extreme water-related events. Better decision support systems are essential to accurately predict and monitor water-related environmental disasters and to manage water resources optimally. These will need to integrate advances in remote sensing, in-situ and citizen observations with high-resolution Earth system modelling, artificial intelligence, information and communication technologies and high-performance computing.
The Digital Twin of the Earth (DTE) for the water cycle is a breakthrough solution that provides digital replicas to monitor and simulate Earth processes with unprecedented spatial-temporal resolution and explicitly including the human component into the system. To get the target, advances in observation technology (satellite and in situ) and modelling are pivotal. The workshop will serve the community to assess the state of the art of these technologies and to identify challenges to be addressed in the near future.
“Distributed computing on large geodata from multiple sources using the Julia Programming language”
Gregory Duveiller, Felix Cremer, Fabian Gans;
Workshop proposal
Spatiotemporal data cubes are becoming ever more abundant and are a widely used tool in the Earth System Science community to handle geospatial raster data.
Sophisticated frameworks in high-level programming languages like R and python allow scientists to draft and run their data analysis pipelines and to scale them in HPC or cloud environments.
While many data cube frameworks can handle harmonized analysis-ready data cubes very well, we repeatedly experienced problems when running complex analyses on multi-source data that was not homogenized. The problems arise when different datasets need to be resampled on the fly to a common resolution and have non-aligning chunk boundaries, which leads to very complex and often unresolvable task graphs in frameworks like xarray+dask.
In this workshop we present the emerging ecosystem of large-scale geodata processing in the Julia programming language under the JuliaDataCubes github umbrella.
Julia is an interactive scientific programming language, designed for HPC applications with primitives for Multi-threaded and Distributed computations built into the language.
We will demonstrate an example analysis where data from different sources (global fields of daily MODIS, hourly ERA5, high-resolution land cover), summing to multiple TBs of data, can interoperate on-the-fly and scale well when run on different computing environments.
“EcoDataCube.eu: An open environmental data cube for Europe”
Martijn Witjes;
Workshop proposal
Strap yourself in and join Martijn and Luka on an Epic journey through the EcoDataCube, an analysis-ready, totally open multidimensional spatiotemporal data cube covering most of Europe! After explaining how large amounts of 30m and 10m earth observation data was aggregated, gap-filled, and used to create 20 annual land cover maps with 43 classes at 30m resolution, they will show you how to access the 200+ cloud-optimized data sets yourself with your browser, GIS, and Python code.
Any leftover time will be used to discuss why no dataset is truly analysis-ready, how no map is perfect, and a collaborative attempt to create the ultimate land cover legend.
“FAIR geospatial data: what stakeholders need and expect”
Nora Meyer zu Erpen, Nuno Queiroz Mesquita Caser de Sa;
Workshop proposal
The Open-Earth-Monitor project aims to maximize the impact and uptake of FAIR environmental data. In the framework of the stakeholder engagement strategy, an online survey on FAIR environmental data was implemented to get a comprehensive picture of whether the geospatial community is aware of FAIR data principles and what importance is attached to each principle. During the workshop, first results will be presented and discussed with stakeholders. To collect their expectations and requirements for FAIR environmental data, different perspectives from the geospatial community should be represented in order to consider divergent opinions from data users and data providers.
Furthermore, the participants will get informed about the FAIR principles and further principles within the open data movement such as CARE (CARE Principles for Indigenous Data Governance) and TRUST (TRUST Principles for digital repositories). The CARE Principles go beyond FAIR to consider and protect the rights and interests of indigenous people and for this reason is also of great importance in the geospatial data context. The TRUST principles introduce a framework to develop best practices for digital repositories to provide access to resources and enable users to rely and manage the respective data. Thus, many of these principles are relevant for the ten GEO Data Management Principles (GEO DMP). The GEO DMP were specifically designed for geospatial and environmental data. They define the data management requirements to facilitate and share Open Data promptly and at minimum cost. Good data management implies a number of activities to ensure that data are discoverable and accessible, understandable, usable and maintained.
“GEO Knowledge Hub to preserve and share EO applications: Introduction and practice”
Paola De Salvo, Felipe Carlos;
Workshop proposal
Earth Observation (EO) applications enable decision-makers, researchers, and specialists to understand the phenomena of our planet, allowing global changes to be made from local actions taken by the public and private sectors. With the dissemination and use of Open Data practices, the EO applications have been enhanced, allowing numerous works to be developed, ranging from the analysis of anthropic actions on inland waters to the temporal analysis of land use and land cover changes. These advances and improvements in EO applications have made their development complex, requiring several materials to be used together with the data to compose the results. Consequently, organizing, sharing, and preserving these applications and the knowledge within them to enable reproduction and replication has become a challenge. Often these activities require specific expertise from researchers and specialists and technical infrastructure.
The Group on Earth Observations (GEO) and its community promote Open Data practices, being responsible for defining guidelines and developing the Global Earth Observation System of Systems (GEOSS) that enhances access to EO data. Recently, GEO started the development of a new component of the GEOSS ecosystem, the GEO Knowledge Hub (GKH), to foster the reproduction and replication of EO applications. Created based on the GEO Data Sharing Principles and the GEO Data Management Principles, the GKH allows users to share their EO applications and the underlying resources (e.g., processing scripts, datasets, and description notes), enabling people to understand, reproduce and replicate the shared EO application. In the GKH, the resources of an application can have files (e.g., satellite imagery datasets, in-situ data files) and metadata (e.g., title, authors, spatial location). Furthermore, each resource can be associated with an individual persistent identifier (DOI) created by the GKH, enhancing dissemination and citation.
Applications shared on the GKH can be found and used, making their knowledge accessible. For this, the GKH provides high-level features for organizing the application materials and facilitating their sharing. In addition, the GKH has a powerful search engine that enables textual, thematic (e.g., Sustainable Development Goal-oriented search), and spatial-temporal searches. In addition to share and search capabilities, the GKH provides features that facilitate community engagement, such as discussion sections (Real-time Q&A) and a feedback system. All these features are accessible through high-level web interfaces and Rest APIs, allowing the integration of various tools to use the digital repository.
The GKH is already being used to share and preserve many EO applications. For example, several GEO Work Programme Activities store their applications in the GKH (e.g., GEOGLAM, GEOVENER, Digital Earth Africa, and many others). These and other use cases have shown positive results, indicating that the GKH can assist in organizing, sharing, and preserving the knowledge generated in EO applications. Therefore, in this workshop, we will introduce the main concepts of the GKH, guidelines, and practices in how users can use it to share and preserve EO applications.
“Global Land use and Land Cover monitoring: From Data to Impact”
Lindsey Sloat;
Keynote lecture
Global land use and land cover monitoring is crucial for understanding and addressing the impacts of land use change on the environment and society. The World Resources Institute’s Land and Carbon Lab is dedicated to advancing this field through the development of cutting-edge monitoring tools, technologies, and partnerships. In this presentation, we will showcase and review available products for global land use and land cover monitoring and highlight the ways in which these products are being leveraged to drive positive change. We will explore the challenges of aligning Earth Observation data with policy, including spatial and temporal challenges as well as challenges aligning land use definitions to land cover monitoring products. The presentation will conclude with a discussion of the future directions for this exciting field, and the opportunities to enhance its impact and value to stakeholders.
“In-situ Citizen Science Data for Training and Validation of the OEMC Monitors and other EO Mapping Models”
Milutin Milenkovic, Johannes Reiche;
Workshop proposal
This workshop will show the current tools we have available at IIASA to generate reference data for training and validation to be used in ML models and to assess the accuracy and performance of the output products the different OEMC monitors are going to generate. We show how, on the one hand, these tools can be used by experts, as well as, the crowd or citizens. The tools being presented will be geo-wiki, picture pile as well as a newly developed google streetview in-situ tool. Examples of how these tools can be used for monitoring drivers of deforestation, improving forest management information as well as crop type mapping. Examples from previous projects and applications will be shown. We furthermore demo two deep dives on how citizen contributions in particular picture pile can help to collect reference data for the crop monitor. Some examples from an existing ESA project Crowd2Train will be featured. We furthermore show how potentially the near real-time forest disturbance monitor (RADD Alerts) can be used in combination with picture pile to, on the one hand, increase the confidence in those alerts and, on the other hand, how such approaches can potentially help to raise awareness about deforestation issues for the wider public.
“Let's co-create the Green Deal Data Space”
Joan Maso, Quentin Groom;
Workshop proposal
The Green Deal Data Space (GDDS) will interconnect current fragmented and dispersed data from various ecosystems, both from the private and public sectors to facilitate evidence-based decisions and expand the capacity to understand and tackle environmental challenges, for example, for monitoring and reaching environmental objectives in biodiversity, resilience to climate change, circular economy and zero pollution strategies.
This workshop will be partaken by projects EuroGEO Action Group for the Green Deal Data Space in their quest to push the boundaries of data provision, and ensure a FAIR and TRUSTworthy data is available for building a more sustainable future. Some outcomes of the workshop may contribute to the new adhoc ISO TC211 working group on data spaces. Within this Workshop, the following projects will present their current approaches towards enabling the GDDS:
AD4GD: The aim is Integrate standard data sources (e.g. Insitu, RS, CitSci, IoT, AI) in the GDDS, improve semantic interperability, and demonstrate with concrete examples that climate change zero pollution, biodiversity general problems can be solved.
FAIRiCUBE: The core objective is to enable players from beyond classic Earth Observation domains to provide, access, process, and share gridded data and algorithms in a FAIR and TRUSTable manner. We are creating the FAIRiCUBE HUB, a crosscutting platform and framework for data ingestion, provision, analysis, processing, and dissemination, to unleash the potential of environmental, biodiversity and climate data through dedicated European data spaces.
USAGE (Urban Data Space for Green Deal) will provide solutions for making city-level data (Earth Observation, Internet of Things, authoritative and crowdsourced data) available, based on FAIR principles: innovative governance mechanisms, standard-based structures and services, AI-based tools, semantics-based solutions, and data analytics. It will provide decision makers with effective, interoperable tools to address environmental and climate changes-related challenges.
B³ - Global biodiversity is changing under multiple pressures including climate change, invasive species and land-use change. Yet biodiversity data are complex and heterogeneous, making it difficult to understand what is happening fast enough for decision makers to react with evidence-based policies. To solve this B³ will create Open workflows in a cloud computing environment to rapidly and repeatedly generate policy relevant indicators and models of biodiversity change.
GREAT: Funded by the Digital Europe program, aims to establish the Green Deal Data Space Foundation and its Community of Practice which builds on both the European Green Deal and the EU’s Strategy for Data. The project will deliver a roadmap for implementing and deploying the Green Deal Data Space, an infrastructure that will allow data providers and initiatives to openly share their data to tackle climate change in a multidisciplinary manner.
The Open Earth Monitor Consortium is working to contribute infrastructure to the GDDS.
“Machine Learning tools and systems support for EO data processing and applications”
Stathes Hadjiefthymiades;
Workshop proposal
this workshop focuses on modern architectures built around cloud computing intended for the processing of EO data and facilitation of relevant applications. among the tools discussed are machine learning enabled modules that support data classification, annotation and compression. Such tools combined with data fusion and semantic information processing transform EO primitive data into meaning rich data sets that directly match application (vertical) requirements. this suite of tools is analytically presented and discussed in details throughout the workshop.
“Open Earth Observation - Shaping the future by understanding the past”
Dr. Julia Wagemann;
Keynote lecture
The era of open Earth Observation (EO) data started 2008 when the United States Geological Survey (USGS) made the Landsat archive available free-of-charge. Since then, the amount of open EO data has increased exponentially, also due to Copernicus, the European Union’s Earth Observation programme. The current wealth of open EO data available is unprecedented. This leads to the current situation that a considerable fraction of the open EO data produced and disseminated on a daily basis is not used as users cannot access, process and analyse the data. Questions on how EO data can be utilised to better support the Green New Deal and related communities, such as Renewable Energies, lead the discussion now and will do so in the coming years. A better understanding of the needs and requirements of different users (from EO data users to policy- and decision-makers) will be vital in shaping the future of open EO data.
“To create the future, we must understand the past” is a famous quote stated by astrophysicist Dr. Carl Sagan. Hence, in this keynote talk, I would like to take the audience on a time travel through the era of open EO data. We will take the perspective of an EO data user and first identify key milestones and developments since 2008 before we draw a more detailed picture of what it is like at the moment to discover, access, process and retrieve knowledge from open EO data. After we shed a light on the past and the present, time travel continues to the year 2030 and together with the audience, I’d like to develop a wish list on how open EO data shall be of value for different stakeholders in the future and extract the key requirements that are needed to achieve this.
“OpenEO in action. Learn how to get started with openEO via the Web Editor, Python and R.”
Peter Zellner, Michele Claus;
Workshop proposal
openEO develops an open API to connect R, Python, JavaScript and other clients to big Earth observation cloud back-ends in a simple and unified way.
openEO Platform implements the openEO API in an federated cloud platform. Hence, it allows to process a wide variety of earth observation datasets in the cloud.
Users interact with the API through clients. This demonstration shows the usage and capabilities of the main clients: The Web Editor, the Python Client and the R-Client.
The Web Editor is a webtool to interactively build processing chains by connecting the openEO processes visually. This is the most intuitive way to get in touch with openEO Platform.
The Python Client and the R-Client are the openEO Platform entry point for programmers. The are available via Comprehensive R Archive Network (CRAN). They facilitate the interaction with the openEO API within the respective programming languages and integrate the advantages of the available geospatial packages and typical IDEs.
The classroom training teaches users how to accomplish their first a round trip through a typical openEO Platform workflow: login to openEO Platform, data and process discovery, process graph building adapted to common use cases, processing of data and the visualization of results
By combining the approaches of the visually interactive Web Editor and the programming based clients users are introduced stepwise to the concepts of openEO Platform and will gradually understand the logic behind openEO.
“OpenLandMap: Global ARCO environmental layers”
Tom Hengl (OpenGeoHub);
Workshop proposal
OpenLandMap is a not-for-profit open data system providing data and services to help produce and share the most up-to-date, fully documented (potentially to the level of fully reproducibility) data sets on the actual and potential status of multiple environmental variables. The layers include soil properties/classes, relief, geology, land cover/use/degradation, climate, current and potential vegetation, through a simple web-mapping interface allowing for interactive queries and overlays. This is a genuine Open Land Data and Services system where anyone can contribute and share global maps and make them accessible to hundreds of thousands of researchers and businesses. We currently host about 15TB of data including 1 km daily and monthly climatic products (min, max temperature and precipitation), map of potential natural vegetation, 250 m MODIS terra products, 100 m land cover and land use maps and soil properties, 30 m land cover maps and digital terrain parameters. We are inspired by de-centralized open source projects such as Mastodon, OpenStreetMap, and OSGeo projects including the R project for statistical computing.
“Predicting the future Earth under climate scenarios: an R tutorial”
Carmelo Bonannella;
Workshop proposal
The presenters will demonstrate how to use available future projections of climatic data across different climate change scenarios to forecast how Earth's surface will look in the future. The presentation will be equally balanced between theory and practice: the theoretical part will provide an overview of the <u>Coupled Model Intercomparison Project</u>, focusing on the models produced for IPCC AR5, and of spatiotemporal modeling of vegetation. The practical part will explain how to combine Earth Observation data and machine learning to produce maps of the <u>major biomes</u> for the future and how their distribution is expected to change according to the different climate change scenarios.
“Reproducible and Reusable Remote Sensing Workflows”
Edzer Pebesma;
Workshop proposal
Reproducibility and Reusability of workflows are increasingly important topics in Remote Sensing research when moving towards FAIR and open data science. This workshop discusses the current status quo, and how we can improve this with future activities.
“The ESA Green Transition Information Factories – using Earth Observation and cloud-based analytics to address the Green Transition information needs.”
Patrick Griffiths;
Keynote lecture
In response to the global climate and sustainability crisis, many countries have expressed ambitions goals in terms of carbon neutrality and a green economy. In this context, the European Green Deal comprises several policy elements aimed to achieve carbon neutrality by 2050.
ESA is initiating various efforts to leverage on space technologies and data and support various Green Deal ambitions. The ESA Space for Green Future (S4GF) Accelerator will explore new mechanisms to promote the use of space technologies and advanced modelling approaches for scenario investigations on the Green Transition of economy and society.
A central element of the S4GF accelerator are the Green Transition Information Factories (GTIF). GTIF takes advantage of Earth Observation (EO) capabilities, geospatial and digital platform technologies, as well as cutting edge analytics to generate actionable knowledge and decision support in the context of the Green Transition.
A first national scale GTIF demonstrator has now been developed for Austria.
It addressed the information needs and national priorities for the Green Deal in Austria. This is facilitated through a bottom-up consultation and co-creation process with various national stakeholders and expert entities. These requirements are matched with various EO industry teams that
The current GTIF demonstrator for Austria (GTIF-AT) builds on top of federated European cloud services, providing efficient access to key EO data repositories and rich interdisciplinary datasets. GTIF-AT initially addresses five Green Transition domains: (1) Energy Transition, (2) Mobility Transition, (3) Sustainable Cities, (4) Carbon Accounting and (5) EO Adaptation Services.
For each of these domains, scientific narratives are provided and elaborated using scrollytelling technologies. The GTIF interactive explore tools allow various users to explore the domains and subdomains in more detail to investigate better understand the challenges, complexities, and underlying socio-economic and environmental conflicts. The GTIF interactive explore tools combine domain specific scientific results with intuitive Graphical User Interfaces and modern frontend technologies. In the GTIF Energy Transition domain, users can interactively investigate the suitability of locations at 10m resolution for the expansion of renewable (wind or solar) energy production. The tools also allow investigating the underlying conflicts e.g., with existing land uses or biodiversity constraints. Satellite based altimetry is used to dynamically monitor the water levels in hydro energy reservoirs to infer the related energy storage potentials. In the sustainable cities’ domain, users can investigate the photovoltaic installments on rooftops and assess the suitability in terms of roof geometry and expected energy yields.
GTIF enables users to inform themselves and interactively investigate the challenges and opportunities related to the Green Transition ambitions. This enables e.g. citizens to engage in the discussion process for the renewable energy expansion or support energy start-ups to develop new services. The GTIF development follows an open science and open-source approach and several new GTIF instances are planned for the next years, addressing the Green Deal information needs and accelerating the Green Transition. This presentation will showcase some of the GTIF interactive explore tools and provide an outlook on future efforts.
“Tools for Long Time-Series Processing For Alpine Environments Monitoring”
Daniele Marinelli, Davide Andreatta;
Workshop proposal
In recent years, several new satellite constellations have been put into service. This, together with the new policies for open data distribution, dramatically increased the availability of time-series with high temporal resolution.
The new widespread availability of high temporal resolution imagery has led to paradigm shift from change detection techniques where pairs of images are compared searching for abrupt changes (e.g. forest fires, forest cuts), to methods capable of tracking changes continuously in time. In particular, time-series allows for the monitoring of subtle and gradual changes for which the definition of a pre and post event date is not straightforward (e.g., vegetation stress caused by drought, bark beetle outbreaks) and anthropogenic processes happening at a finer timescale (e.g. mowing events).
Such data availability, together with increasing ease of access to both offline computing power and to cloud based computing platforms and new tools for data processing, is leading to the development of a wide variety of applications for near real-time monitoring using Earth Observation (EO) data intended to be used in decision making processes (e.g., forest management) by stakeholders such as government agencies. In this context, we present monitoring tools, implemented on the Google Earth Engine platform, that exploit spaceborne EO data to support decision making in Alpine environments affected by two threats connected to global change: pests outbreaks and land use intensification.
After the Vaia storm in 2018, bark beetle outbreaks have become more frequent in the Alps with estimates, at the end of 2022, of 8000 hectares infested by the pests only in the Trento province. Such phenomena must be monitored by detecting both past and new outbreaks. This is critical for the definition of recovery strategies for the affected areas and mitigation strategies to limit the spread of new outbreaks. The developed tool analyzes long Sentinel-2 time-series for bark beetle outbreaks mapping, generating a product that identifies the area hit by an attack and the first year and month of the detection. By processing new images as they are acquired, it performs a near real-time monitoring highlighting new attacks as soon as they are visible from the satellite data. This tool is currently being used by the Forest Service of the Province of Trento that is providing the generated products to the local stations.
The second tool we present uses vegetation indices time-series derived from Sentinel-2 imagery to estimate grassland mowing frequency. Grasslands in Europe are facing management intensification in accessible areas and abandonment in marginal ones, with significant consequences not only for grassland productivity, but also for fodder quality, nitrogen leaching, animal and plant diversity and grassland recreational value. For these reasons the availability of grassland mowing frequency data can contribute to the development of more targeted conservation and management measures. The model is now being used in several research and management contexts, including CAP subsidies conditionality monitoring and habitat suitability for ground nesting endangered bird identification.
“Using spatial data to build a nested climate accounting network”
Joaquin van Peborgh;
Workshop proposal
The OpenClimate Network is an open source nested accounting platform allows users to navigate emissions inventories and climate pledges of different actors at every level, aggregating data from various public sources for countries, regions, cities and companies. Through this aggregation, it enables the comparison of how different data sources report emissions of certain actors, by harmonizing the way data is reported and identifying the different methodologies used.
Additionally, by nesting actors into their respective jurisdictions it facilitates the comparison between the pledges these actors have committed to, and to see if they are aligned towards the same climate targets, and how these compare to the goals of the Paris Agreement.
By aggregating data and exploring it in this nested manner, it also allows for the effective identification of data gaps for these actors, suggesting where efforts are needed to identify existing data sources or help produce new inventories. When data gaps are identified, the platform also prompts users to contribute data based on the open and standardized data model used to aggregate emissions and pledges data.
Spatial data can be a key component in tackling double counting, building subnational emissions inventories and accounting for corporate emissions.