Join us to help put some of the world's most vulnerable places on the map. A mapathon is a mapping marathon, where we get together to contribute to OpenStreetMap - the world's free map.
No experience is necessary - just bring your laptop and we will provide the training. Learn more about crowdsourcing, open data and humanitarian response - we will also provide some tips for how to host a mapathon at your home institution.

Wed, 10 Apr, 12:45-14:00 / Room E1

The session presents the state of art information systems in oceanography (metadata, vocabularies, ISO and OGC applications, data models), interoperability (Interoperability forms, Web services, Quality of Services, Open standards), data circulation and services (quality assurance / quality control, preservation, network services) and Education in ocean science (Education and Research, Internet tools for education).
The 2019 session should provide new ideas on the interoperability issues deriving from different sources of data and new data streams.
ISO standards introduce the necessary elements in the abstract process aiming to assess ‘how’ and ‘how much’ data meets applicable regulatory requirements and aims to enhance user needs. Data management infrastructures should include an evaluation of data by assuring relevance, reliability and fitness-for-purposes / fitness-for-use, adequacy, comparability and compatibility. The session aims also to create a link to the important initiatives on ocean literacy. Presenters are strongly encouraged to demonstrate how their efforts will benefit their user communities, facilitate collaborative knowledge building, decision making and knowledge management in general, intended as a range of strategies and practices to identify, create, represent and distribute data, products and information.

The quality of predictions of weather and climate depends on both resolution and complexity of the models that are used. However, resolution and complexity are limited by the computational performance that is available on today's supercomputers. While weather and climate models run on some of the fastest supercomputers of the world, models typically fail to run close to peak performance such that there is still room for a significant speed-up if efficiency is improved. The increase in parallelisation in high performance computing and the availability of various computing platforms is imposing significant challenges for the community to find the optimal hardware/model configuration and to achieve the best performance. On the other hand, the evaluation of high resolution simulations is often tedious due to large data volumes, limited statistic that is affordable and changed model behaviour that needs to be studied (e.g. if convection or eddies are resolved explicitly or if non-hydrostatic equations need to be used).
These challenges can only be addressed appropriately in a close collaboration between Computing and Earth System Scientists. This session aims to bring together scientists who run and evaluate atmosphere and ocean models with high resolution and complexity as well as scientists who enable these models to run as efficiently as possible on existing and future high performance computing architectures (regarding both model development and model optimisation). The session will also be an opportunity for scientists from the EU projects PRIMAVERA, ESCAPE and ESiWACE as well as HighResMIP from CMIP6 to meet and interact.

V. Balaji from Princeton University will be our keynote speaker invited by the ESiWACE EU Horizon2020 COE (grant number 675191).

A wide range of processes in the earth system directly affect geodetic observations. This session invites a wide array of contributions which showcase the use of geodesy for Earth science and climate applications, providing crucial insights into the state and change of the earth system and/or understanding its processes.

Data driven quantification of water mass fluxes through boundaries of Earth’s different regions and spheres provides important insights to other geoscience communities and informs model validation and improvement. Changes in regional sea level and ocean circulation are observed by altimetry and gravimetry. Natural and anthropogenic alterations of the terrestrial water cycle lead to changes in river runoff, precipitation, evapotranspiration, and water storage which may cause surface deformation sensed by GNSS stations and InSAR measurements as well as mass/gravity changes observed by satellite/ground gravimetry. Mass changes in the ice sheets and glaciers are detectable by both geometrical and gravimetric techniques. And other novel applications of geodetic techniques are emerging in many fields.

In addition, individual sensor recordings are often affected by high-frequency variability caused by, e.g., tides in the solid Earth, oceans, and atmosphere and their corresponding crustal deformations affecting station positions; non-tidal temperature and moisture variability in the troposphere modifying microwave signal dispersion; rapid changes in the terrestrially stored water caused by hydrometeorologic extreme events; as well as swift variations in relative sea-level that are driven by mass and energy exchange of the global oceans with other components of the Earth system, which all might lead to temporal aliasing in observational records. 

This session invites a wide array of contributions which showcase the use of geodesy for Earth science and climate applications. This session aims to cover innovative ways to use GRACE, GRACE-FO and other low Earth orbiters, GNSS techniques, InSAR, radar altimetry, and their combination with in-situ observations. We welcome approaches which tackle the problem of separating signals of different geophysical origin, by taking advantage of model output and/or advanced processing and estimation techniques. Since the use of geodetic techniques is not always straightforward, we encourage authors to think of creative ways to make their findings, data and software more readily accessible to other communities in hydrology, ocean, cryospheric, atmospheric and climate sciences. With author consent, highlights from the oral and poster session will be tweeted with a dedicated hashtag during the conference in order to increase the impact of the session.

The new scenario related to the global urbanization process and its impact on environmental sustainability and resilience to natural disasters, especially the ones related to the Climate Change, strongly call holistic multidisciplinary and multi-sectorial approaches for the management of urban areas and Cultural heritages.
These approach aim at providing solutions based on the integration of technologies, methodologies and best practices (remote and local monitoring, simulating and forecasting, characterizing, maintaining, restoring, etc.), with the purpose to increase the resilience of the assets, also thanks to the exploitation of dedicated ICT architectures and innovative eco-solutions and also by accounting the social and economic value of the investigated areas, especially in CH frame.
In this context, attention is also focused on the high-resolution geophysical imaging is assuming a great relevance to manage the underground and to adopt new strategies for the mitigation of geological risks.
This session represents a good forum to present, technologies best practices and share different experiences in the field of the urban areas and CH management and protection, against the multi-risk scenarios and for the different situations at European and worldwide level. Finally, great attention will be devoted to the success cases, with a specific focus on recent international projects on smart cities and Cultural heritage in Europe and other countries.

From the perspective of Earth System predictions, the use of machine learning, and in particular deep learning, is still in its infancy. There are many possible ways how machine learning could improve model quality, generate significant speed-ups for simulations or help to extract information from numerous Earth System data, in particular satellite observations. However, it has yet to be shown that machine learning can hold what it is promising for the specific needs of the application of Earth System predictions. This session aims to provide an overview how machine learning can/will be used in the future and tries to summarise the state-of-the-art in an area of research that is developing at a breathtaking pace.

Remarkable technological progress in remote sensing and geophysical surveying, together with the recent development of innovative data treatment techniques are providing new scientific opportunities to investigate landslide processes and hazards all over the world. Remote sensing and geophysics, as complementary techniques for the characterization and monitoring of landslides, offer the possibility to effectively infer and correlate an improved information of the shallow -or even deep- geological layers for the development of conceptual and numerical models of slope instabilities. Their ability to provide integrated information about geometry, rheological properties, water content, rate of deformation and time-varying changes of these parameters is ultimately controlling our capability to detect, model and predict landslide processes at different scales (from site specific to regional studies) and over multiple dimensions (2D, 3D and 4D).

This session welcomes innovative contributions and lessons learned from significant case studies using a myriad of remote sensing and geophysical techniques and algorithms, including optical and radar sensors, new satellite constellations (including the emergence of the Sentinel-1A and 1B), Remotely Piloted Aircraft Systems (RPAS) / Unmanned Aerial Vehicles (UAVs) / drones, high spatial resolution airborne LiDAR missions, terrestrial LIDAR, Structure-from-Motion (SfM) photogrammetry, time-lapse cameras, multi-temporal Synthetic Aperture Radar differential interferometry (DInSAR), GPS surveying, Seismic Reflection, Surface Waves Analysis, Geophysical Tomography (seismic and electrical), Seismic Ambient Vibrations, Acoustic Emissions, Electro-Magnetic surveys, low-cost (/cost-efficient) sensors, commercial use of small satellites, Multi-Spectral images, Real time monitoring, in-situ sensing, etc.

The session will provide an overview of the progress and new scientific approaches of Earth Observation (EO) applications, as well as of surface- and borehole-based geophysical surveying for investigating landslides. A special emphasis is expected not only on the collection but also on the interpretation and use of high spatiotemporal resolution data to characterize the main components of slope stability and dynamics, including the type of material, geometrical and mechanical properties, depth of water table, saturation conditions and ground deformation over time. The discussion of recent experiences and the use of advanced processing methods and innovative algorithms that integrate data from remote sensing and geophysics with other survey types are highly encouraged, especially with regard to their use on (rapid) mapping, characterizing, monitoring and modelling of landslide behaviour, as well as their integration on real-time Early Warning Systems and other prevention and protection initiatives. Other pioneering applications using big data treatment techniques, data-driven approaches and/or open code initiatives for investigating mass movements using the above described techniques will also be considered on this session.

We invited prof. Denis Jongmans (Isterre, Université Grenoble Alpes, France), as guest speaker for the session.

From the real-time integration of multi-parametric observations is expected the major contribution to the development of operational t-DASH systems suitable for supporting decision makers with continuously updated seismic hazard scenarios. A very preliminary step in this direction is the identification of those parameters (seismological, chemical, physical, biological, etc.) whose space-time dynamics and/or anomalous variability can be, to some extent, associated with the complex process of preparation of major earthquakes.
This session wants then to encourage studies devoted to demonstrate the added value of the introduction of specific, observations and/or data analysis methods within the t-DASH and StEF perspectives. Therefore studies based on long-term data analyses, including different conditions of seismic activity, are particularly encouraged. Similarly welcome will be the presentation of infrastructures devoted to maintain and further develop our present observational capabilities of earthquake related phenomena also contributing in this way to build a global multi-parametric Earthquakes Observing System (EQuOS) to complement the existing GEOSS initiative.
To this aim this session is not addressed just to seismology and natural hazards scientists but also to geologist, atmospheric sciences and electromagnetism researchers, whose collaboration is particular important for fully understand mechanisms of earthquake preparation and their possible relation with other measurable quantities. For this reason all contributions devoted to the description of genetic models of earthquake’s precursory phenomena are equally welcome. Every 2 years selected papers presented in thsi session will be proposed for publication in a dedicated Special Issue of an international (ISI) scientific journal.

In recent years an increasing number of research projects focused on natural hazards (NH) and climate change impacts, providing a variety of information to end user or to scientists working on related topics.

The session aims at promoting new and innovative studies, experiences and models to improve risk management and communication about natural hazards to different end users.

End users such as decision and policy makers or the general public, need information to be easy and quickly interpretable, properly contextualized, and therefore specifically tailored to their needs. On the other hand, scientists coming from different disciplines related to natural hazards and climate change (e.g., economists, sociologists), need more complete dataset to be integrated in their analysis. By facilitating data access and evaluation, as well as promoting open access to create a level playing field for non-funded scientists, data can be more readily used for scientific discovery and societal benefits. However, the new scientific advancements are not only represented by big/comprehensive dataset, geo-information and earth-observation architectures and services or new IT communication technologies (location-based tools, games, virtual and augmented reality technologies, and so on), but also by methods in order to communicate risk uncertainty as well as associated spatio-temporal dynamic and involve stakeholders in risk management processes.

However, data and approaches are often fragmented across literature and among geospatial/natural hazard communities, with an evident lack of coherence. Furthermore, there is not a unique approach of communicating information to the different audiences. Rather, several interdisciplinary techniques and efforts can be applied in order to simplify access, evaluation, and exploration to data.

This session encourages critical reflection on natural risk mitigation and communication practices and provides an opportunity for geoscience communicators to share best methods and tools in this field. Contributions – especially from Early Career Scientists – are solicited that address these issues, and which have a clear objective and research methodology. Case studies, and other experiences are also welcome as long as they are rigorously presented and evaluated.

New and innovative abstract contributions are particularly welcomed and their authors will be invited to submit the full paper on a special issue on an related-topics Journal.

In cooperation with NhET (Natural hazard Early career scientists Team).

The session aims to collect original or review contributions on the use of data from Low-Earth-Orbiting (LEO) satellites making measurements in the thermosphere-ionosphere to investigate ionospheric anomalies related to space weather, geophysical and artificial sources. In fact, data from LEO satellites can provide a global view of near-Earth space variability and are complementary to ground-based observations, which have limited global coverage. The AMPERE project and integration of the Swarm data into ESA’s Space Weather program are current examples of this. The availability of thermosphere and ionosphere data from the DEMETER satellite and the new operative CSES mission demonstrates that also satellites that have not been specifically designed for space weather studies can provide important contributions to this field. On the other hand, there are evidences that earthquakes can generate electromagnetic anomalies into the near Earth space. A multi-instrumental approach, by using ground observations (magnetometers, magnetotelluric stations, GNSS receivers, etc.) and LEO satellites (DEMETER, Swarm, CSES, etc.) measurements can help in clarifying the missing scientific knowledge of the lithosphere-atmosphere-ionosphere coupling (LAIC) mechanisms before, during and after large earthquakes. We also solicit contributions on studies about other phenomena, such as tropospheric and anthropogenic electromagnetic emissions, that influence the near-Earth electromagnetic and plasma environment on all relevant topics including data processing, data-assimilation in models, space weather case studies, superimposed epoch analyses, etc.

With the impressive theoretical progress of last decades, the global tectonics is about to reach a state that is quite unique not only for geology but for any descriptive domain of knowledge. This is the state of so high elaboration and maturity that a theory may be subject, like some theories of physics, chemistry, algebra and geometry, to the most rigorous inspection ever suggested in the science – the inspection for being formal sensu mathematical logic. Still, to bring the global tectonics to this state, quite a work remains to be done. This is an exciting cross-disciplinary work of knowledge engineers and geologists that would result in a quite new level of understanding the Earth and new quality of scientific collaboration on it.
However, being so different from all the fields that underwent such “high formalization” so far, the tectonics needs special formal treatment, which, in turn, requires special logico-mathematical formalism complementary to the traditional predicate logic. Thus the scope of this session appears highly cross-disciplinary, claiming for a joint intellectual journey of field geologists, experimentalists and modelers, IT specialists and computer scientists, logicians and mathematicians.

Increase in the amount of high quality seismic data and advances in high-performance computing in recent years have been transformative to explore Earth’s interior at all scales through seismic modelling, both in theory and practice. The goal of this session is to bring seismologists and computational scientists together to discuss recent advances and future directions in innovative forward & inverse modelling techniques, HPC systems & computational tools as well as the related theory and scientific outcomes.

We encourage contributions in the field of theoretical and computational seismology highlighting, but not limited to;

- advancements in numerical solvers and techniques,
- seismic codes on emerging CPU/GPU architectures
- full-waveform inversion from local to global scales,
- Bayesian inverse problems,
- machine learning algorithms for seismic problems,
- big data (seismic & computational) problems,
- large-scale workflows on HPC systems and their automatization,
- optimization strategies,
- uncertainty analysis for large-scale imaging,
- seismological results of HPC applications from passive (earthquakes and noise) and active seismic sources,
- visualization (parallel, VR platforms, etc. ).

Ensuring long-term water sustainability for increasing human populations is a common goal for water resource managers. Measuring evapotranspiration (ET) at watershed or river-reach scales, upland or urban areas is required to estimate how much water can be apportioned for human needs while maintaining healthy vegetation and habitat for wildlife.
Consequently, much research has been devoted to this topic. However although there have been many advances in meteorological equipment and observations, more universal recognition of the impact of climate and land cover changes on evaporation and hydrology, and the increased accessibility of many parts of the world, evaporation from much of the globe remains elusive to quantify. This is particularly true in areas with few meteorological observations, in regions where precipitation is particularly hard to predict such as in arid and semi-arid or mountain environments. ET measurements are often made on local scales, but scaling up has been problematic due to spatial and temporal variability.
There are challenges associated with handling temporal variability over complex agro-climatic regions and in places with strong effects of unpredictable climate oscillations. For instance, crop/plant coefficients vary seasonally, particularly for riparian, upland vegetation, and urban greenery; traditional approaches of ET estimation commonly neglect the heterogeneity of microclimate, density, species, and phenology that have often led to gross overestimates of plant water use.
In this session, we want to focus on quantifying evapotranspiration dynamics in diverse climates and environments as a tool for improving hydrologic assessments and predictions at a catchment scale. Remote sensing products in many cases are the only spatially distributed information available to account for seasonal climate and vegetation variability and are thus extremely valuable data sources for ET estimation on larger scales.
We invite researchers to contribute theoretical and empirical ET model applications for a variety of dryland vegetation associations and other sensitive environments. We welcome studies that estimate ET using both prognostic and diagnostic approaches from process-based models that rely on the integration of precipitation and soil-vegetation dynamics to a more direct estimation of ET using e.g. remote sensing based data streams. Applications in drought-prone forests, rangelands, mountain and urban areas at a range of spatial and temporal scales are encouraged.

Global losses due to natural hazards have shown an increasing trend over the last decades, which is expected to continue due to growing exposure in disaster-prone areas and the effects of climate change. In response, recent years have seen greater worldwide commitment to reducing disaster risk. Working towards this end requires the implementation of increasingly effective disaster risk management (DRM) strategies. These must necessarily be supported by reliable estimates of risk and loss before, during, and after a disaster. In this context, innovation plays a key role.
This session aims to provide a forum to the scientific, public and private discourse on the challenges to innovate DRM. We welcome submissions on the development and application of groundbreaking technologies, big data, and innovative modeling and visualization approaches for disaster risk assessment and DRM decision-making. This includes the quantification and mapping of natural hazard risks and their components (i.e. hazard, exposure, and vulnerability), as well as the forecasting of hazard and impacts prior to a disaster event, or as it is unfolding (in real- or near real-time). We are particularly interested in contributions covering one or more of the following thematic areas in the context of disaster risk assessment and reduction: artificial intelligence and machine learning, big data, remote sensing, social media, volunteered geographic information (VGI), mobile applications, crowdsourcing, internet of things (IoT), and blockchain. We also welcome submissions exploring how these or other innovations can support real-world DRM strategies and translate into improved DRM decisions.

The application of Earth Observation (EO) datasets for Sustainable Development is a fast-growing field. EO technologies and innovations are constantly evolving, and contributing to the delivery of sustainable, economic and societal benefit to developing countries, helping them meet their Sustainable Development Goals. There is great potential to build on the unique strengths that the space sector has in terms of services and technology to deliver sustainable development objectives, especially in data-sparse regions of the globe, and realising this potential is crucial. The scientific and socio-economic benefits from remote sensing data applications are limitless. Especially in developing nations, where there is a need to bridge the gap between existing technologies and operational applications, EO technology can help enhance the capability to monitor the Earth’s vital resources, and to support the planning, design, operation, and management processes of various sectors.

This session invites submissions from researchers and practitioners, whose work with EO technologies provides the information needed to confront key sustainable development challenges, spanning a whole range of themes such as: disaster response and early warning systems, water resources, agriculture, air and water quality, deforestation, land-use change, urban development, renewable energy and health.

Satellite data provides information on the marine environment that can be used for many applications – from water quality and early warning systems, to climate change studies and marine spatial planning. The most modern generation of satellites offer improvements in spatial and temporal resolution as well as a constantly evolving suite of products.

Data from the European Union Copernicus programme is open and free for everyone to use however they wish - whether from academic, governance, or commercial backgrounds. The programme has an operational focus, with satellite constellations offering continuity of service for the foreseeable future. There is also a growing availability of open source tools that can be used to work with this data.

This short course is an opportunity to learn about the data available from the Copernicus Sentinel 3 satellite, and then, with support from marine Earth Observation experts, to develop your own workflows for using data from the EUMETSAT Copernicus Marine Data Stream and Copernicus Marine Environment Monitoring Service. The sessions will be interactive, using the WeKEO DIAS hosted processing, Sentinel Applications Platform (SNAP) software, and Python programming. No experience is necessary as various exercises will be provided for a wide range of skill levels and applications, however participants should bring their own laptops and be prepared to install open source software in advance.

The ENES Climate Analytics Service (ECAS) is a new service from the EOSCHUB project. It enables scientific end-users to perform data analysis experiments on large volumes of climate data, by exploiting a PID-enabled, server-side, and parallel approach.
It aims at providing a paradigm shift for the ENES community with a strong focus on data intensive analysis, provenance management, and server-side approaches as opposed to the current ones mostly client-based, sequential and with limited/missing end-to-end analytics workflow/provenance capabilities.

This short course is divided into a teaching as well as a hands on training part and includes:
- presentation(s) on the theoretical and technical background of ECAS. This covers the data cube concept and its operations (eg.: subset extraction, reduction, aggregation). Furthermore, we provide an introduction to the Ophidia framework, which is the components of ECAS for processing multidimensional data.
- tutorials and training materials. Participants will have the opportunity to dive into the ECAS software stack and learn how to manipulate multidimensional data through real world use cases from the climate domain.

This short course is open to everyone interested in processing multidimensional data. ECAS is server-based, thus all required software and tools are already available on our sites. Participants do not need to install any software stack on their laptop. All they need is a browser to access the ECAS portal. Only a prior registration is required and it is straightforward by following these links: https://ecaslab.dkrz.de/registerproc.html or https://ophidialab.cmcc.it/web/registration.html

During this short course, the participants will learn:
- what the data cube concept is and how is manipulated with ECAS/Ophidia
- how to perform analysis on multidimensional data
- how to publish, access and share data and workflows with ECAS
- how to implement/deploy their own scientific workflows

R is probably the most important statistical computing language in academia. With more than 10,000 packages it has been extended in many directions, including a huge support for geospatial data (see https://cran.r-project.org/web/views/Spatial.html and Bivand, Pebesma, and Gómez-Rubio 2013). R’s flexibility and statistical capabilities have made it attractive for people working in Earth, planetary and space sciences and a need for geographic data science.

This course will introduce the audience to R’s geographical capabilities, building on the book Geocomputation with R (https://geocompr.robinlovelace.net/) by the workshop authors (Lovelace, Nowosad, and Muenchow 2018). It will cover four topics and provide a solid foundation for attendees to apply R to a range of geographic data:

1. R’s implementation of the two most important spatial data models - vector (Pebesma 2018) and raster (Hijmans 2017).
2. Spatial data visualization with R.
3. Bridges to dedicated GIS software such as QGIS.
4. Statistical learning with geographic data.

Understanding data models is vital for working with geographic data in R. Maps, based on the data, can display complex information in a beautiful way while allowing for first inferences about spatial relationships and patterns. R has already become a Geographic Information System (GIS) (Bivand, Pebesma, and Gómez-Rubio 2013) - a system for the analysis, manipulation and visualization of geographic data (Longley et al. 2015). However, R was not designed as a GIS, and therefore computing large amounts of geographic data in R can be cumbersome. Even more important, R is missing hundreds of geoalgorithms which are readily available in common Desktop GIS. To deal with these shortcomings R packages have been developed allowing R to interface with GIS software. As an example, we will introduce the RQGIS package (Muenchow, Schratz, and Brenning 2017) for this purpose but also comment on other R-GIS bridges such as RSAGA (Brenning, Bangs, and Becker 2018) and rgrass7 (Bivand 2017). We will use RQGIS to compute terrain attributes (catchment area, catchment slope, SAGA wetness index, etc.) which we will subsequently use to model and predict spatially landslide susceptibility with the help of statistical learning techniques such as GLMs, GAMs and random forests (James et al. 2013). Hence, we show by example how to combine the best of two worlds: the geoprocessing power of a GIS and the (geo-)statistical data science power of R. The short course will consist of a mixture of presentations, live code demos and short interactive exercises if time allows.

Learning objectives
By the end of this workshop, the participants should:

- Know how to handle the two spatial data models (vector and raster) in R.
- Import/export different geographic data formats.
- Know the importance of coordinate reference systems.
- Be able to visualize geographic data in a compelling fashion.
- Know about geospatial software interfaces and how they are integrated with R (GEOS, GDAL, QGIS, GRASS, SAGA).
- Know about the specific challenges when modeling geographic data.

Software requirements
1. Latest version of R and RStudio
2. R packages: sf, raster, RQGIS, RSAGA, spData, tmap, tidyverse, mlr
3. QGIS (including SAGA and GRASS), please follow our installation guide (http://jannes-m.github.io/RQGIS/articles/install_guide.html) to make sure that RQGIS can work with QGIS

References
Bivand, Roger. 2017. Rgrass7: Interface Between GRASS 7 Geographical Information System and R. https://CRAN.R-project.org/package=rgrass7.

Bivand, Roger S., Edzer Pebesma, and Virgilio Gómez-Rubio. 2013. Applied Spatial Data Analysis with R. 2nd ed. New York: Springer.

Brenning, Alexander, Donovan Bangs, and Marc Becker. 2018. RSAGA: SAGA Geoprocessing and Terrain Analysis. https://CRAN.R-project.org/package=RSAGA.

Hijmans, Robert J. 2017. Raster: Geographic Data Analysis and Modeling. https://CRAN.R-project.org/package=raster.

James, Gareth, Daniela Witten, Trevor Hastie, and Robert Tibshirani, eds. 2013. An Introduction to Statistical Learning: With Applications in R. Springer Texts in Statistics 103. New York: Springer.

Longley, Paul, Michael Goodchild, David Maguire, and David Rhind. 2015. Geographic Information Science & Systems. Fourth edition. Hoboken, NJ: Wiley.

Lovelace, Robin, Jakub Nowosad, and Jannes Muenchow. 2018. Geocomputation with R. The R Series. CRC Press.

Muenchow, Jannes, Patrick Schratz, and Alexander Brenning. 2017. “RQGIS: Integrating R with QGIS for Statistical Geocomputing.” The R Journal 9 (2): 409–28.

Pebesma, Edzer. 2018. “Simple Features for R: Standardized Support for Spatial Vector Data.” The R Journal. https://journal.r-project.org/archive/2018/RJ-2018-009/index.html.

Nowadays, researchers have to tailor their models, data and results into systems which can be used by non-experts, such as policy makers, stakeholders, farmers and the many professionals in need of clear answers to land management questions.

One way ahead to bridge the gap between R&D and real-life applications is the development of decision support systems (DSS) on top of geospatial cyberinfrastructures (GCI) that can handle end-user requests in real time with all the complexity being transparent to the user.

The short course will cover some developments carried out within the EU H2020 LandSupport Project. The implementation of an indicator of land-take is showed, both presenting how to deal with the technical steps on a more general level and proposing hands-on sessions on the implementation of specific components of the whole land-take workflow.

First an introduction is presented, covering a general overview about the GCI and the requirements of pipelines.
A brief description of the main tasks follows:

• Big spatio-temporal raster data are managed by means of rasdaman. Here a workflow is presented showcasing how to import and query multi-band Sentinel-2 data based on the OGC Big Data Standards.
• Cloud masking and filtering. Copernicus Sentinel-2 data are processed to obtain bottom of the atmosphere, cloud free, reflectance data. A theoretical and a hands-on session in R will be presented.
• Classification. A spectral-temporal datacube of Sentinel-2 data are used to get a binary map of imperviousness (1: urban pixel, 0: non-urban pixel). At least one classification model will be presented with hands-on in R and/or MatLab.
• Land-take. An algorithm to calculate land-take using a low-level programming language is showed, with more advanced insights about the opportunity to face GPU calculations.

Altogether, we motivate how the LandSupport approach aims at providing decision support based on multi-source spatiotemporal data in a user-centric manner.
Ample time will be available for answering questions and discussion.

Earth systems science is fundamentally cross-disciplinary, and increasingly this requires sharing and exchange of geoscientific information across discipline boundaries. This information can be both rich and complex, and content is not always readily interpretable by either humans or machines. Difficulties arise through differing exchange formats, lack of common semantics, divergent access mechanisms, etc.

Recent developments in distributed, service-oriented, information systems using web-based (W3C, ISO, OGC) standards are leading to advances in data interoperability. At the same time, work is underway to understand how meaning may be represented using ontologies and other semantic mechanisms, and how this can be shared with other scientists.

This session aims to explore developments in interoperable data sharing, and the representation of semantic meaning to enable interpretation of geoscientific information. Topics may include, but are not limited to:
- standards-based information modelling
- interoperable data sharing
- use of metadata
- knowledge representation
- use of semantics in an interoperability context
- application of semantics to discovery and analysis
- metadata and collaboration

The term Data Cube as it relates to Big Earth Data has recently gained a lot of attention. The Data Cube concept promises to tackle some of the challenges associated with serving and consuming large volumes of environmental data. Data Cubes offer a more on-demand and analysis-ready access to n-dimensional data, that can be accessed along any dimension (space, time, spectrum), allowing for efficient trim or slice operations. The Data Cube concept makes large volumes of environmental and geospatial data more manageable and thus, increases the general uptake of Big Earth Data.

Even though the Data Cube concept is not new, the application to Big Earth Data entails quite a few challenges: interoperability between different data providers, combining data from different domains with domain-specific formats, different spatial and temporal resolutions and different coordinate systems. The success of Data Cubes for Big Earth Data relies on the cooperation of Data Cube technology providers, data users and large data organisations in the future. A better understanding of the challenges large data organisations face and the needs data users have is helpful for the adoption of existing technologies as well as for future development of Data Cube technologies.

This session aims to establish a dialogue between Data Cube technology providers, data users and large data organisations. A particular focus will be set on technical Data Cube solutions from current initiatives, on challenges large data organisations face and the requirements data users need in order to benefit most from Data Cube services.

This session aims to bring together researchers working with big data sets generated from monitoring networks, extensive observational campaigns and detailed modeling efforts across various fields of geosciences. Topics of this session will include the identification and handling of specific problems arising from the need to analyze such large-scale data sets, together with methodological approaches towards semi or fully automated inference of relevant patterns in time and space aided by computer science-inspired techniques. Among others, this session shall address approaches from the following fields:
• Dimensionality and complexity of big data sets
• Data mining in Earth sciences
• Machine learning, including deep learning and other advanced approaches
• Visualization and visual analytics of big data
• Informatics and data science
• Emerging big data paradigms, such as datacubes

Instrumentation and measurement technologies are currently playing a key role in the monitoring, assessment and protection of environmental resources. Climate study related experiments and observational stations are getting bigger and the number of sensors and instruments involved is growing very fast. This session deals with measurement techniques and sensing methods for the observation of environmental systems, focusing on climate and water. We welcome contributions about advancements on field measurement approaches, development of new sensing techniques, low cost sensor systems and whole environmental sensor networks, including remote observation techniques.
Studies about signal and data processing techniques targeted to event detection and the integration between sensor networks and large data systems are also very encouraged. This session is open for all works about an existing system, planning a completely new network, upgrading an existing system, improving streaming data management, and archiving data.

The last decade has seen rapid growth in the number of online data sets, tools, and research infrastructures many of which are coordinated by separate communities in the Earth, space, and environmental sciences. Notable efforts include GEO, EPOS, ENVRI, ESGF, ESIP, CUHASI, AuScope, EDI, EarthCube, OneGeology, ODIP, IGSN, DataOne and many more. In Europe, many of these activities are now connected to upcoming European Open Science Cloud (EOSC) initiative.
There are common technological, policy, and science challenges that each is trying solve, often in isolation. Although standards, vocabularies, formats, etc are cohesive within each community, there are sufficient differences that make it hard to integrate data across them and beyond to other disciplines. Similar barriers exists from different policies regarding licenses, access, citation and publishing practices. The time is ripe to synchronise efforts to create globally connected networks of Earth, Space and Environmental Science data, information systems, software and researchers to create a ‘cloud’ of networked infrastructures.
Papers are solicited from those building community specific systems or from those trying to resolve the challenges of internationally linking multiple communities to create networked environments for developing common global solutions for more efficient and effective use of limited, available funding.

Digital data, software and samples are key inputs that underpin research and ultimately scholarly publications, and there are increasing expectations from policy makers and funders that they will be Open and FAIR (Findable, Accessible, Interoperable, Reusable). Open, accessible, high-quality data, software and samples are critical to ensure the integrity of published research and to facilitate reuse of these inputs in future scientific efforts.

Currently, most research inputs have limited accessibility and persistence. Many journals accept data and software as part of supplementary information with little documentation; some journals accept contacting the author for access with few successful requests; and many samples underpinning key research papers are inaccessible and not well described. Given the diverse requirements of the Solid Earth and Environmental community, most repositories struggle to make artifacts of research and communications Open and FAIR.

An inclusive, integrated approach to Open and FAIR is now required from data/sample/software repositories, whilst publishers and funders need to provide consistent policies, standards and guidelines: the research community could also better share tools and techniques. This session solicits papers from repositories, publishers, funders, researchers, policy makers and anyone who is trying to establish components of an integrated, Open and FAIR research ecosystem.

A significant and daunting challenge for science data and service centers and repositories is to establish trustworthiness and fitness for purpose, i.e., suitability, at the level of individual data products and services. Having content-rich, interoperable and discoverable quality descriptive information will help organizations address this challenge. The scalability of curating such information, either as metadata records or as documents, has considerable challenges of its own. This session invites presentations on approaches, frameworks, workflows, best practices, tools, etc., that are under development or being implemented towards systematically evaluating quality attributes of individual data products and services, and automatically generating content-rich quality descriptive information that is interoperable and discoverable. All types of data, all perspectives of data and information quality, and all aspects of product and service quality attributes are welcome.

The evolution of data acquisition systems has enabled increasing data quality and the volume of information to be analyzed, processed and interpreted. Nowadays, there has been a growing interest in the geophysical time series and image processing analysis in all most disciplines relates to Earth Sciences, such as Seismology, Geochemistry, Geodesy, Volcanology, Geology and Satellite Observations.
A major challenge that arises is how to structure and organize the huge amount of data and to determine the type of information that could help the scientific community for a deeper knowledge on the complex dynamics of geophysical and geochemical systems in our Planet.
The high volume of data recorded by those systems requires an appropriate framework that can enhance classical approaches by exploiting the latent knowledge embedded in the data. New rising methodologies have to tackle the long-term problems of data management, accessibility and deployment. Data Mining, Cloud Computing and Machine Learning are the most appropriate disciplines for the analysis of such high throughput data.
In this session, we welcome contributions focused on recent machine learning advances applied to Earth and planetary sciences, with a focus on remote sensing techniques and early warning systems. This is a highly interdisciplinary session, where artificial intelligence is combined with Earth sciences techniques in order to improve the knowledge of the complexity of our Planet.
This session is partially sponsored by the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 798480, and by Government of Spain through the research project TEC2015-814 68752.

Remote sensing techniques and earth system modelling have been widely used in earth science and environmental science. In particular, the world is suffering significant environmental changes such as hydro-climatic extremes, sea level rise, melting glaciers and ice caps and forest fires. The earth observations and earth system models provide valuable insight into climate variability and environmental change. Meanwhile, the question on how to derive and present uncertainties in earth observations and model simulations has gained enormous attention among communities in the earth sciences.

However, quantification of uncertainties in satellite-based data products and model simulations is still a challenging task. Various approaches have been proposed within the community to tackle the validation problem for satellite-based data products and model simulations. These progress include theory advancement, mathematics, methodologies, techniques, communication of uncertainty and traceability.

The aim of this session is to summarize current state-of-the-art in uncertainty quantification and utilization for satellite-based earth observations and earth system models.

Software is critical to the success of science. Creating and using Free and Open Source Software (FOSS) fosters contributions from the scientific community, creates a peer-reviewed and consensus-oriented environment, and promotes sustainability of science infrastructures.
Providing open access to source code also permits reuse of data, reproducibility of science, and creates scientific transparency. Open science is only possible when access to data is open, and data is analysed using open source software. This requires taking responsibility for software development, and adopting stewardship practices for managing, processing and disseminating scientific data products and related services.
This session will also discuss the publication and citation of scientific free and open source software as part of the general record of science and as part of the track record of the scientists who create or apply FOSS tools in their research.
This session will look at the role of FOSS in the geosciences with a special emphasis on the interoperability among established and developing FOSS-tools within geoinformatics. The session will be a forum for the latest advances in FOSS-empowered research, for successful applications of existing FOSS tools for geoscientific tasks, as well as for new developments in geoscience-related to FOSS.

This session aims to highlight Earth Science research concerned with state of the art computational and data infrastructures such as Clouds (commercial, on premis, European EOSC ) and HPC (Supercomputer, Clusters, accelerator-based systems (GPGPU, FPGA)).

We will focus on data intensive workflows (scientific workflows) between Infrastructures e.g. European data and compute infrastructures down to complex analysis workflows on an HPC system e.g. in situ coupling frameworks.

The session presents an opportunity for everyone to present and learn from results achieved, success stories and experience gathered during the process of study, adaptation and exploitation of these systems.

Further contributions are welcome that showcase middleware and tools developed to support Earth Science applications on Cloud and HPC, e.g. to increase effectiveness, robustness or ease of use.

Topics of interest include:
- Data intensive Earth Science applications and how they have been adapted to different HPC infrastructures
- Data mining software stacks in use for large environmental datasets
- HPC simulation and High Performance Data Analytics e.g. code coupling, in-situ workflows
- Experience with Earth Science applications in Cloud environments e.g. solutions on Amazon Web Services, Google Earth Engine, Microsoft Azure, and Earth Science simulation codes in private and European Cloud infrastructures (Open Science Cloud)
- Tools and services for Earth Science data management, workflow execution, web services and portals to ease access to compute resources.
- Tools and middleware for Earth Science applications on Grid, Cloud and on High Performance Computing infrastructures.
- Earth Science Application using cloud native solutions
- Innovative Evaluation and Prediction Applications for Large Earth Science Datasets

The term RSE, originally coined by the UK RSE association (https://rse.ac.uk), says the following about RSEs: "A growing number of people in academia combine expertise in programming with an intricate understanding of research. Although this combination of skills is extremely valuable, these people lack a formal place in the academic system." Surveys among RSEs in Australia, New Zealand, the UK, and Germany found that majority of the respondents prioritised: (1) Increasing recognition of the RSE role, (2) Building appropriate position descriptions and KPIs for better career opportunities, and (3) Developing a stronger community.

This session is calling for examples and success stories from geoscience community members who contribute to research software but face the above challenges.

We welcome contributions from RSEs across the EGU family. Topics surrounding career growth can include but are not limited to sharing experiences of:
- Creating and/or maintaining an RSE group
- Effective RSE focused events [e.g. career fairs, workshops..]
- Factors that influence RSE career progression
- Effective teaching strategies at all stages of RSE life
- Building sustainable development communities
- The recognition, or lack, of RSEs in academic outputs
- Skills required for RSEs [HPC, FPGAs, cloud, containers, ML, …]
- Thoughts on where "we" need to make improvements in RSE life

The session will start with a short report on a survey initiated after last year’s EGU on RSEs in the geosciences. Your participation in the survey is still welcome: https://bit.ly/rse-survey-egu

Citizen science (the involvement of the public in scientific processes) is gaining momentum in one discipline after another, thereby more and more data on biodiversity, earthquakes, weather, climate, health issues among others are being collected at different scales that can extend the frontiers of knowledge. Successful citizen observatories can potentially be scaled up in order to contribute to larger environmental and policy strategies and actions (such as the European Earth Observation monitoring systems) and to be integrated in GEOSS and Copernicus. Making credible contributions to science can empower citizens to actively participate in environmental decision making, can raise awareness about environmental issues and can help bridge the science-society gap. Often, citizen science is seen in the context of Open Science, which is a broad movement embracing Open Data, Open Access, Open Educational Resources, Open Source, Open Methodology, and Open Peer Review to transparently publish and share scientific research - thus leveraging Citizen Science and Reproducible Research.

Both, open science in general and citizen science in particular, pose great challenges for researchers, and to support the goals of the various openness initiatives, this session looks at what is possible nowadays and what is ready for application in geosciences. Success stories, failures, best practices and solutions will be presented, in addition to various related networks. We aim to show how researchers, citizens, funding agencies, governments and other stakeholders can benefit from citizen science and open science, acknowledging the drawbacks and highlighting the opportunities available for geoscientists.

In this session, we are looking for successful approaches of working with citizen science and open science to bridge the gap between a multitude of stakeholders in research, policy, economy, practice and society at large by finding emerging environmental issues and empowering citizens. This session shall be an open space to exchange experiences and to present either successful examples or failed efforts. Learning from others and understanding what to adopt and what to change help the participants in their own undertakings and new initiatives, so that they become future success stories.

We want to ask and find answers to the following questions:
Which approaches can be used in Earth, Planetary and Space Sciences?
What are the biggest challenges and how to overcome them?
What kind of citizen scientist involvement and open science strategies exist?
How to ensure transparency in project results and analyses?
How to evaluate successful bridging of the science-society-gap?

Data science, analytics and visualization technologies and methods emerge as significant capabilities that address a number of challenges and present new opportunities in improving Earth and Space science data usability. This session will highlight and discuss the novelty and strength of these emerging fields and technologies of these components, and their trends. We invite papers and presentations to examine and share the experience of:
- What benefits they offer to Earth and Space Science
- What science research challenges they address
- How they help transform science data into information and knowledge
- In what ways they can advance scientific research
- What lessons did we learn in the development and infusion of these methods and technologies

Virtual reality has significantly grown in recent years in both teaching and research. This Technique allows the user to explore virtual worlds resulting from numerical modeling, geophysical data processing or image processing (photogrammetry for example) at various spatial and temporal scales. For example, it is possible to observe atoms and molecules, to move in crystalline structures, to visualize elements of subsoil reconstructed from seismic data, or to move in extraterrestrial landscapes or in models mantle convection. Depending on the technology used, this reality could be two-dimensional or three-dimensional, static or animated. The user can interact with the environment or simply be a spectator. This tool therefore offers new perspectives for measurement and observation in the world of research. It also offers new ways to explore the Earth and planets and is underused for teaching. The objective of this session is to explore the latest developments in virtual reality in the earth sciences. Presentations proposing new approaches for research as well as for teaching are welcome.

This year marks the 250th anniversary of the birth of Alexander von Humboldt (1769-1859), the intrepid explorer of the Andes and other regions in the world, and the most famous scientist of his time. Alexander von Humboldt is perhaps best known for his radical new vision of nature as a complex and interconnected global force, thereby becoming the founder of the field of biogeography and laying the ground for modern Earth-System Science approaches. It seems fitting to pay tribute to Alexander von Humboldt’s legacy by reviewing the state of the art in studies of the coupled lithosphere – atmosphere – hydrosphere – biosphere system with a focus on the Andean mountain belt. The Andes have become one of the main natural laboratories in the world to explore these questions and many recent studies have addressed its tectonic and geodynamic evolution, but also the two-way couplings between surface uplift, climatic evolution and biodiversity in the Andes and its foreland. This Union Session will bring together world-leading specialists on these questions with the aim to shed light on both suspected and unexpected couplings in the system.

Over the whole Earth history, the climate has encountered tipping points, shifting from one regulated system to the other. This tilting motion affects both climate and the carbon cycle and has played a major role in the evolution of the Earth climate, at all timescales. Earth History has been ponctuated by large climate changes and carbon cycle reorganizations, from large climate variations occurring in deep times (snowball events, terrestrialisation, Mesozoic and early Cenozoic warm episodes, quaternary glacial cycles…) to past and on-going abrupt events. Many potential triggers of those climate and carbon cycle shifts have been proposed and tested through modeling studies, and against field data, such as those directly or indirectly linked with tectonics (plate motion, orogenesis, opening/closing of seaways, weathering…) and orbital forcing. Given that the Earth climate is currently experiencing an unprecedented transition under anthropogenic pressure, understanding the mechanisms behind the scene is crucial.

Our aim is to point out the most recent results concerning how a complex system as the climate of the Earth has undergone many tipping points and what is the specificity of the future climate changes. Therefore, within this session, we would like to encourage talks discussing advances in our record and modeling of the forces triggering and amplifying the changes of Earth climate and carbon cycle across spatial and temporal scales.

In today’s changing world we need to tap the potential of every talented mind to develop solutions for a sustainable future. The existence of under-representation of different groups (cultural, national and gender) remains a reality across the fields of science, technology, engineering, and mathematics (STEM fields) around the world, including the geosciences. This Union Symposium will focus on remaining obstacles that contribute to these imbalances, with the goal of identifying best practices and innovative ideas to overcome obstacles.

EGU is welcoming six high-level speakers from the funding agencies and research centres on both sides of the Atlantic related to geosciences to present efforts and discuss initiatives to tackle both implicit and explicit biases. Speakers are:

Jill Karsten, AGU Diversity and Inclusion Task Force (confirmed)
Erika Marín-Spiotta, University of Wisconsin - Madison (confirmed)
Daniel Conley, Lund University (confirmed)
Giulio di Toro, University of Padua (confirmed)
Liviu Matenco, Utrecht University (confirmed)
Barbara Romanowicz, European Research Council (confirmed)

Atmospheric composition matters to climate, weather forecasting, human health, terrestrial and aquatic ecosystems, agricultural productivity, aeronautical operations, renewable energy production, and more. Hence research in atmospheric composition is becoming increasingly cross-cutting and linked to many disciplines including climate, biogeosciences, hydrology, natural hazards, computer and data sciences, socio-economic studies and many others. There is a growing need for atmospheric composition information and an improved understanding of the processes that drive changes in the composition and resulting impacts. While atmospheric composition research is advancing rapidly, there is a need to pay more attention to the translation of this research to support societal needs. Although translational research is a major focus of the health sciences and meteorology, it is in a relatively early stage in atmospheric composition. In this Union Symposium, we plan to highlight the need for, and to illustrate exciting advances in the translation of atmospheric composition research to support services. We will build upon work within the World Meteorological Organization and other communities related to the closer linkages of weather, atmospheric composition, and climate research and related services. We will also articulate the needs for advances in observing systems, models and a better understanding of fundamental processes. This session will also serve as a celebration of the 30 year anniversary of the WMO Global Atmosphere Watch programme and an opportunity for the broader community to envision partnerships needed to facilitate the effective translation of atmospheric composition research.

In October 2018, the IPCC published its special report on impacts of global warming of 1.5 deg C. Another recent, highly publicised study suggests that the planet could pass an irreversible threshold into a so called “Hothouse Earth” state for a temperature increase of as low as 2 degrees C above pre-industrial temperatures, while other studies and commentaries have emphasised the urgency on climate action, arguing that 2020 must be a turning point for global fossil fuel emissions, to increase the chance of maintaining a safe operating space for the humans on the planet. In 2018, the IPCC celebrated its 30th anniversary. The importance of taking action on human-induced climate change has been emphasised with governments around the world since the 1990s yet CO2 concentrations continue to rise and international initiatives have, to date, had limited and insufficient impact to avert some of the most serious consequences of climate change.
How close are we to one or more critical thresholds (cliff edge)? Is there time to avert passing one or more of these thresholds? What can the geoscience community do to reduce the risks? How important is bottom up versus top down action to ensuring the least worst outcome? These are some of the questions we will debate with world experts in their field and authors of the thought papers on these topics.

The geosciences are currently used by policymakers in a wide variety of areas to help guide the decision-making process and ensure that the best possible outcome is achieved. While the importance of scientific advice and the use of evidence in the policymaking process is generally acknowledged by both policymakers and scientists, how scientific advice is integrated and who is responsible is still unclear.

EU Policymakers frequently highlight institutionalised processes for integrating scientific advice into policy such as European Commission's Group of Chief Scientific Advisors (SAM) and the EU Commission’s Register of Expert Groups. But how efficient and accessible are these mechanisms really?

Some emphasise the need for scientists to have their own policy networks in place so that they can share their research outcomes with policymakers who can then use it directly or pass it on to those responsible for relevant legislation. But from funding applications to teaching and even outreach activities – scientists are often already overloaded with additional tasks on top of their own research. Can they really be held responsible for keeping up with the latest policy news and maintaining a constantly changing network of policymakers as well?

This debate will feature a mixed panel of policymakers and geoscientists who have previously given scientific advice. Some key questions that the panel will debate include:
• How can the accessibility of current EU science-advisory mechanisms be improved?
• Are scientists doing enough to share their research?
• And who is responsible for ensuring that quality scientific evidence is used in policymaking?

Speakers will be encouraged to explain any science advisory mechanism that they highlight (e.g. SAM) to ensure that the debate is understood by all those in attendance.

While the panel and subsequent debate will have an EU focus, it is likely that many of the issues discussed will be applicable to countries around the world.

The ever more challenging work environments and increasing pressures on Early Career Scientists e.g. publish or perish, securing grant proposals, developing transferable skills and many more – and all while having a lack of job security. This puts a big strain on Early Career Scientists and this can lead to neglected mental well-being which in turn increases the risk of developing anxiety, depression or other mental health issues. The graduate survey from 2017 (https://www.nature.com/nature/journal/v550/n7677/full/nj7677-549a.html) shows that 12% of respondents had sought help or advice for anxiety or depression during their PhD.

In this debate we want to discuss: Is there a problem? How ECS can take control of their mental wellbeing and prioritise this in the current research environment? And what support would ECS like to see from organisations like EGU or their employers?

"What counts may not be countable and what is countable may not count". Assessments of scientists and their institutions tend to focus on easy-to-measure metrics related to research outputs such as publications, citations, and grants. However, society is increasingly dependent on Earth science research and data for immediate decisions and long-term planning. There is a growing need for scientists to communicate, engage, and work directly with the public and policy makers, and practice open scholarship, especially regarding data and software. Improving the reward and recognition structure to encourage broader participation of scientists in these activities must involve societies, institutions, and funders. EGU, AGU, and JPGU have all taken steps to improve this recognition, from developing new awards to starting journals around the topic of engaging the public to implementing FAIR data practices in the Earth, environmental, and space sciences, but far more is needed for a broad cultural change. How can we fairly value and credit harder-to-measure, these less tangible contributions, compared to the favoured metrics? And how can we shift the emphasis away from the "audit culture" towards measuring performance and excellence? This session will present a distinguished panel of stakeholders discussing how to implement and institutionalize these changes.

Wed, 10 Apr, 12:45-14:00 / Room E1

Plastic pollution is recognized as one of the most serious and urgent problems facing our planet. Rates of manufacture, use and ultimately disposal of plastics continue to soar, posing an enormous threat to the planet’s oceans and rivers and the flora and fauna they support. There is an urgent need for global action, backed by sound scientific understanding, to tackle this problem.

This Union Symposium will address the problems posed to our planet by plastic pollution, and examine options for dealing with the threat.

The Games Night is a space to gather, socialise, and play some games. The catch is that all the games are based on Geoscience! Bring along your own games or try one of the others in the session and meet the people who created them. This will also be your chance to try games featured in the Games for Geoscience session.

Join us to help put some of the world's most vulnerable places on the map. A mapathon is a mapping marathon, where we get together to contribute to OpenStreetMap - the world's free map.
No experience is necessary - just bring your laptop and we will provide the training. Learn more about crowdsourcing, open data and humanitarian response - we will also provide some tips for how to host a mapathon at your home institution.

Plastic Oceans UK have been experts on plastic pollution for nearly a decade - solving the plastic crisis through their science, sustainability and education programmes. This all began with the award-winning documentary A Plastic Ocean, now available for streaming on Netflix.

Through changing attitudes, behaviours and practices on the use and value of plastics, we can stop plastic pollution reaching the ocean within a generation.

Come along to the screening of A Plastic Ocean to understand the impacts of plastic pollution around the world, what action we can take to stop plastics entering our natural world and pose your questions to the film's producer, Jo Ruxton, at the end of film.

http://plasticoceans.uk/