The session presents the state of art information systems in oceanography (metadata, vocabularies, ISO and OGC applications, data models), interoperability (Virtual Research Infrastructures, 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 2020 session should provide new ideas on the interoperability issues deriving from different sources of data.
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. 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.

NEMO (Nucleus for European Modelling of the Ocean) is a state-of-the-art modelling framework of the ocean that includes components for the ocean dynamics, the sea-ice and the biogeochemistry, so as a nesting package allowing to set up zooms and a versatile data assimilation interface (see https://www.nemo-ocean.eu/).
NEMO is used by a large community in Europe and world-wide (~200 projects, ~100 publications each year) covering a wide range of applications : oceanographic research, operational oceanography, seasonal forecast and climate projections.
NEMO is in particular used in 6 Earth System Models within CMIP6 and in Copernicus Marine Services (CMEMS) model-based products.

This session will provide a forum to properly address the new scientific advances in numerical modelling of the ocean and their implication for NEMO developments associated with:
• Ocean dynamics at large to coastal scales, up to 1km resolution ;
• Ocean biogeochemistry
• Sea-ice
• New numerical schemes associated to energy conservation constraints
• High performance computing challenges and techniques

The session will cover both research and operationnal activities contributing to new analysis, ideas and developments of ocean numerical models.
Presentations of results based on new NEMO functionalities and new NEMO model configurations are welcome.

Public information:
Registration for virtual session: https://framaforms.org/virtual-egu-os48-session-1587740583

This session covers an overview of the progress and new scientific approaches for investigating landslides using state-of-the-art techniques such as: Earth Observation (EO), close-range Remote Sensing techniques (RS) and Geophysical Surveying (GS).

A series of remarkable technological progresses are driven new scientific opportunities to better understand landslide dynamics worldwide, including integrated information about rheological properties, water content, rate of deformation and time-varying changes of these parameters through seasonal changes and/or progressive slope damage.

This session welcomes innovative contributions and lessons learned from significant case studies and/or original methods aiming to increase our capability to detect, model and predict landslide processes at different scales, from site specific to regional studies, and over multiple dimensions (e.g. 2D, 3D and 4D).

A special emphasis is expected not only on the particularities of data collection from different platforms (e.g. satellite, aerial, UAV, Ground Based...) and locations (e.g. surface- and borehole-based geophysics) but also on new solutions for digesting and interpreting datasets of high spatiotemporal resolution, landslide characterization, monitoring, modelling, as well as their integration on real-time EWS, rapid mapping and other prevention and protection initiatives. Examples of previous submissions include using one or more of the following techniques: 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 DInSAR, GPS surveying, Seismic Reflection, Surface Waves Analysis, Geophysical Tomography (seismic and electrical), Seismic Ambient Vibrations, Acoustic Emissions, Electro-Magnetic surveys, low-cost sensors, commercial use of small satellites, Multi-Spectral images, etc. 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 very welcomed.

GUEST SPEAKER: this year, we invited professor Jonathan Chambers, team leader of the geophysical tomography cluster at the British Geological Survey (BGS).

A remote sensing signal acquired by a sensor system results from electromagnetic radiation (EM) interactions from incoming or emitted EM with atmospheric constituents, vegetation structures and pigments, soil surfaces or water bodies. Vegetation, soil and water bodies are functional interfaces between terrestrial ecosystems and the atmosphere. The physical types of EM used in RS has increased during the years of remote sensing development. Originally, the main focus was on optical remote sensing. Now, thermal, microwave, polarimetric, angular and quite recently also fluorescence have been added to the EM regions under study.
This has led to the definition of an increasing number of bio-geophysical variables in RS. Products include canopy structural variables (e.g. biomass, leaf area index, fAPAR, leaf area density) as well as ecosystem mass flux exchanges dominated by carbon and water exchange. Many other variables are considered as well, like chlorophyll fluorescence, soil moisture content and evapotranspiration. New modelling approaches including models with fully coupled atmosphere, vegetation and soil matrices led to improved interpretations of the spectral and spatio-temporal variability of RS signals including those of atmospheric aerosols and water vapour.
This session solicits for papers presenting methodologies and results leading to the assimilation in biogeoscience and atmospheric models of cited RS variables as well as data measured in situ for RS validation purposes. Contributions should preferably focus on topics related to climate change, food production (and hence food security), nature preservation and hence biodiversity, epidemiology, and atmospheric chemistry and pollution (stratospheric and troposphere ozone, nitrogen oxides, VOC’s, etc). It goes without saying that we also welcome papers focusing on the assimilation of remote sensing and in situ measurements in bio-geophysical and atmospheric models, as well as the RS extraction techniques themselves.
This session aims to bring together scientists developing remote sensing techniques, products and models leading to strategies with a higher (bio-geophysical) impact on the stability and sustainability of the Earth’s ecosystems.

Public information:
BG2.7
Remote Sensing applications in the Biogeosciences

Chairperson: Frank Veroustraete & Willem Verstraeten
10:45
Welcome
1
D530 | EGU2020-5174
10:50
Potential of LiDAR for species richness prediction at Mount Kilimanjaro
Alice Ziegler and the Research Group at the Kilimanjaro
2
D512 | EGU2020-288
10:57
Understanding wetland dynamics using geostatistics of multi-temporal Earth Observation datasets
Manudeo Narayan Singh and Rajiv Sinha
3
D515 | EGU2020-5421
11:04
Twelve years of SIFTER Sun-Induced Fluorescence retrievals from GOME-2 as an independent constraint on photosynthesis across continents and biomes
Maurits L. Kooreman, K. Folkert Boersma, Erik van Schaik, Anteneh G. Mengistu, Olaf N. E. Tuinder, Piet Stammes, Gerbrand Koren, and Wouter Peters
4
D516 | EGU2020-6674
11:11
Evaluation of understory LAI estimation methodologies over forest ecosystem ICOS sites across Europe
Jan-Peter George Jan Pisek and the Tobias Biermann (2), Arnaud Carrara (3), Edoardo Cremonese (4), Matthias Cuntz (5), Silvano Fares (6), Giacomo Gerosa (7), Thomas Grünwald (8) et al.
5
D517 | EGU2020-8263
11:18
Probing the relationship between formaldehyde column concentrations and soil moisture using mixed models and attribution analysis
Susanna Strada, Josep Penuelas, Marcos Fernández Martinez, Iolanda Filella, Ana Maria Yanez-Serrano, Andrea Pozzer, Maite Bauwens, Trissevgeni Stavrakou, and Filippo Giorgi
6
D518 | EGU2020-9071
11:25
Validation of seasonal time series of remote sensing derived LAI for hydrological modelling
Charlotte Wirion, Boud Verbeiren, and Sindy Sterckx
7
D519 | EGU2020-12000
11:32
Potassium estimation of cotton leaves based on hyperspectral reflectance
Adunias dos Santos Teixeira, Marcio Regys Rabelo Oliveira, Luis Clenio Jario Moreira, Francisca Ligia de Castro Machado, Fernando Bezerra Lopes, and Isabel Cristina da Silva Araújo
8
D528 | EGU2020-4418
11:39
Comparison of the Photochemical Reflectance Index and Solar-induced Fluorescence for Estimating Gross Primary Productivity
Qian Zhang and Jinghua Chen
9
D529 | EGU2020-4582
11:46
Weed-crop competition and the effect on spectral reflectance and physiological processes as demonstrated in maize
Inbal Ronay, Shimrit Maman, Jhonathan E. Ephrath, Hanan Eizenberg, and Dan G. Blumberg
10
D531 | EGU2020-6059
11:53
Remote sensing-aid assessment of wetlands in central Malawi
Emmanuel Ogunyomi, Byongjun Hwang, and Adrian Wood
12:00
Open discussion
12:30
End morning session

Chat time: Wednesday, 6 May 2020, 14:00–15:45
Chairperson: Willem Verstraeten Frank Veroustraete
14:00
Welcome back!
1
D534 | EGU2020-10014
14:05
On the surface apparent reflectance exploitation: Entangled Solar Induced Fluorescence emission and aerosol scattering effects at oxygen absorption regions
Neus Sabater, Pekka Kolmonen, Luis Alonso, Jorge Vicent, José Moreno, and Antti Arola
2
D536 | EGU2020-15832
14:12
Evaluating the impact of different spaceborne land cover distributions on isoprene emissions and their trends using the MEGAN model.
Beata Opacka, Jean-François Müller, Jenny Stavrakou, Maite Bauwens, and Alex B. Guenther
3
D537 | EGU2020-10633
14:19
Application of Copernicus Global Land Service vegetation parameters and ESA soil moisture data to analyze changes in vegetation with respect to the CORINE database
Hajnalka Breuer and Amanda Imola Szabó
4
D538 | EGU2020-13332
14:26
How valuable are citizen science data for a space-borne crop growth monitoring? – The reliability of self-appraisals
Sina C. Truckenbrodt, Friederike Klan, Erik Borg, Klaus-Dieter Missling, and Christiane C. Schmullius
5
D539 | EGU2020-18493
14:33
Learning main drivers of crop dynamics and production in Europe
Anna Mateo Sanchis, Maria Piles, Julia Amorós López, Jordi Muñoz Marí, and Gustau Camps Valls
6
D540 | EGU2020-19003
14:40
Modelling understory light availability in a heterogeneous landscape using drone-derived structural parameters and a 3D radiative transfer model
Dominic Fawcett, Jonathan Bennie, and Karen Anderson
7
D543 | EGU2020-5151
14:47
Global assimilation of ocean-color data of phytoplankton functional types: Impact of different datasets
Lars Nerger, Himansu Pradhan, Christoph Völker, Svetlana Losa, and Astrid Bracher
8
D544 | EGU2020-5251
14:53
PROSPECT-PRO: a leaf radiative transfer model for estimation of leaf protein content and carbon-based constituents
Jean-Baptiste Féret, Katja Berger, Florian de Boissieu, and Zbyněk Malenovský
9
D547 | EGU2020-13447
15:00
Inverting a comprehensive crop model in parsimonious data context using Sentinel 2 images and yield map to infer soil water storage capacity.
André Chanzy and Karen Lammoglia
10
D550 | EGU2020-18798
15:07
Study on The Extraction Method and Spatial-temporal Characteristics of Irrigated Land in Zhangjiakou City
Zijuan Zhu, Lijun Zuo, Zengxiang Zhang, Xiaoli Zhao, Feifei Sun, and TianShi Pan
11
D551 | EGU2020-19953
15:14
Remote sensing and GIS based ecological modelling of potential red deer habitats in the test site region DEMMIN (TERENO)
Amelie McKenna, Alfred Schultz, Erik Borg, Matthias Neumann, and Jan-Peter Mund
15:21
Open discussion
15:45
End afternoon session

Remote sensing, numerical models, and machine learning have been widely used for investigating environmental risks under climate change. It is known that they tend to do an excellent job in mapping, simulating, and projecting the long-term changes in average conditions. However, damages associated with extreme weathers by droughts, floods, forest fires, heat-related mortality, and crop yield loss are often more devastating than those caused by gradual climate changes. How remote sensing, numerical models, and machine learning can be used for assessing the impacts of extreme weathers on the natural and human systems remains uncertain.
This session aims to summarize current progress in assessing the ability of remote sensing, numerical models, and machine learning for quantifying climate risks in multiple sectors, such as water, agriculture, and human health.
We especially welcome investigations focusing on the inter-comparison of methodologies, as well as multi-sectoral, cross-sectoral, and integrated assessments.

This session invites innovative Earth system and climate studies based on geodetic measuring techniques. Modern geodetic observing systems document a wide range of changes in the Earth’s solid and fluid layers at very diverging spatial and temporal scales related to processes as, e.g., glacial isostatic adjustment, the terrestrial water cycle, ocean dynamics and ice-mass balance. Different time spans of observations need to be cross-compared and combined to resolve a wide spectrum of climate-related signals. Geodetic observables are also often compared with geophysical models, which helps to explain observations, evaluate simulations, and finally merge measurements and numerical models via data assimilation.
We appreciate contributions utilizing geodetic data from diverse geodetic satellites including altimetry, gravimetry (CHAMP, GRACE, GOCE and GRACE-FO), navigation satellite systems (GNSS and DORIS) or remote sensing techniques that are based on both passive (i.e., optical and hyperspectral) and active (i.e., SAR) instruments. We welcome studies that cover a wide variety of applications of geodetic measurements and their combination to observe and model Earth system signals in hydrological, ocean, atmospheric, climate and cryospheric sciences. Any new approaches helping to separate and interpret the variety of geophysical signals are equally appreciated. Contributions working towards the newly established Inter-Commission Committee on "Geodesy for Climate Research" (ICCC) of the International Association of Geodesy (IAG) would be particularly interesting for this session.
With author consent, highlights from this session will be tweeted with a dedicated hashtag during the conference in order to increase the impact of the session.

Innovative forward and inverse modeling techniques, advances in numerical solvers and the ever-increasing power of high-performance compute clusters have driven recent developments in inverting seismic and other geophysical data to reveal properties of the Earth at all scales.

The interpretation of single disciplinary geophysical field data often allows for various, equally probable models that may not always sufficiently discern plausible hypotheses that are challenged. Therefore, co-validation of data from different disciplines is critical.

This session provides a forum to present, discuss and learn the state-of-the-art in computational seismology, non-linear and joint inversion, uncertainty quantification and collaborative interpretation.

Invited Speakers:
Christel Tiberi, "Joint inversion and collaborative interpretations in complex geodynamical context";
Andrew Curtis, "Variational Probabilistic Tomography";
Yann Capdeville, "Intrinsic non-uniqueness of the acoustic full waveform inverse problem"

Comprehensive evaluations of Earth Systems Science Prediction (ESSP) systems (e.g., numerical weather prediction, hydrologic prediction, climate prediction and projection, etc.) are essential to understand sources of prediction errors and to improve earth system models. However, numerous roadblocks limit the extent and depth of ESSP system performance evaluations. Observational data used for evaluation are often not representative of the physical structures that are being predicted. Satellite and other large spatial and temporal observations datasets can help provide this information, but the community lacks tools to adequately integrate these large datasets to provide meaningful physical insights on the strengths and weaknesses of predicted fields. ESSP system evaluations also require large storage volumes to handle model simulations, large spatial datasets, and verification statistics which are difficult to maintain. Standardization, infrastructure, and communication in one scientific field is already a challenge. Bridging different communities to allow knowledge transfers, is even harder. The development of innovative methods in open frameworks and platforms is needed to enable meaningful and informative model evaluations and comparisons for many large Earth science applications from weather to climate.

The purpose of this Open Science 2.0 session is to bring experts together to discuss innovative methods for integrating, managing, evaluating, and disseminating information about the quality of ESSP fields in meaningful way. Presentations of these innovative methods applied to Earth science applications is encouraged. The session should generate some interest in communities and research projects building and maintaining these systems (e.g. ESMVal, Copernicus, Climaf, Freva, Birdhouse, MDTF, UV-CDAT, CMEC - PCMDI Metrics Package, Doppyo, MET-TOOLS, CDO, NCO, etc.). The session allows room for the exchange of ideas. An outcome of this session is to connect the scientists, develop a list of tools and techniques that could be developed and provided to the community in the future.

Geostatistics is commonly applied in the Water, Earth and Environmental sciences to quantify spatial variation, produce interpolated maps with quantified uncertainty and optimize spatial sampling designs. Extensions to the space-time domain are also a topic of current interest. Due to technological advances and abundance of new data sources from remote and proximal sensing and a multitude of environmental sensor networks, big data analysis and data fusion techniques have become a major topic of research. Furthermore, methodological advances, such as hierarchical Bayesian modeling and machine learning, have enriched the modelling approaches typically used in geostatistics.

Earth-science data have spatial and temporal features that contain important information about the underlying processes. The development and application of innovative space-time geostatistical methods helps to better understand and quantify the relationship between the magnitude and the probability of occurrence of these events.

This session aims to provide a platform for geostatisticians, soil scientists, hydrologists, earth and environmental scientists to present and discuss innovative geostatistical methods to study and solve major problems in the Water, Earth and Environmental sciences. In addition to methodological innovations, we also encourage contributions on real-world applications of state-of-the-art geostatistical methods.

Given the broad scope of this session, the topics of interest include the following non-exclusive list of subjects:
1. Advanced parametric and non-parametric spatial estimation and prediction techniques
2. Big spatial data: analysis and visualization
3. Optimisation of spatial sampling frameworks and space-time monitoring designs
4. Algorithms and applications on Earth Observation Systems
5. Data Fusion, mining and information analysis
6. Integration of geostatistics with optimization and machine learning approaches
7. Application of covariance functions and copulas in the identification of spatio-temporal relationships
8. Geostatistical characterization of uncertainties and error propagation
9. Bayesian geostatistical analysis and hierarchical modelling
10. Functional data analysis approaches to geostatistics
11. Geostatistical analysis of spatial compositional data
12. Multiple point geostatistics
13. Upscaling and downscaling techniques
14. Ontological framework for characterizing environmental processes

Earth Sciences depend on detailed multi-variate measurements and investigations to understand the physical, geological, chemical, biogeochemical and biological processes of the Earth. Making accurate prognoses and providing solutions for current questions related to climate change, water, energy and food security are important requests towards the Earth Science community worldwide. In addition to these society-driven questions, Earth Sciences are still strongly driven by the eagerness of individuals to understand processes, interrelations and tele-connections within and between small sub-systems and the Earth System as a whole. Understand and predict temporal and spatial changes in the above mentioned Micro- to Earth spanning scales is the key to understand Earth ecosystems; we need to utilize high resolution data across all scales in an integrative/holistic approach. Using Big Data, which are often distributed and particularly very in-homogenous, has become standard practice in Earth Sciences and digitalization in conjunction with Data Science promises new discoveries.
The understanding of the Earth System as a whole and its sub-systems depends on our ability to integrate data from different disciplines, between earth compartments, and across interfaces. The need to advance Data Science capabilities and to enable earth scientists to follow best possible workflows, apply methods, and use computerized tools properly and in an accessible way has been identified worldwide as an important next step for advancing scientific understanding. This is particularly necessary to access knowledge contained in already acquired data, but which due to the limitations of data integration and joint exploration possibilities currently remains invisible. This session aims to bring together researchers from Data and Earth Sciences working on, but not limited to,
• SMART monitoring designs by dealing with advancing monitoring strategies to e.g. detect observational gaps and refine sensor layouts to allow better and statistically robust extrapolation
• Data management and stewardship solutions compliant with FAIR principles, including the development and application of real-time capable data management and processing chains
• Data exploration frameworks providing qualified data from different sources and tailoring available computational and visual methods to explore and analyse multi-parameter data generated through monitoring efforts/ model simulations

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 downstream services, and then, with support from marine Earth Observation experts, to develop your own workflows. 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.

Public information:
This course will still be held, post-EGU week, on the the 19th May 10:00 CEST - 12:00 CEST (8:00 - 10:00 UTC) . More information is available at https://tinyurl.com/ya5fhkaj