Remote sensing and Earth Observations (EO) are used increasingly in the different phases of the risk management and in development cooperation, due to the challenges posed by contemporary issues such as climate change, and increasingly complex social interactions. The advent of new, more powerful sensors and more finely tuned detection algorithms provide the opportunity to assess and quantify natural hazards, their consequences, and vulnerable regions, more comprehensively than ever before.
Several agencies have now inserted permanently into their program the applications of EO data to risk management. During the preparedness and prevention phase, EO revealed, fundamental for hazard, vulnerability and risk mapping. EO data intervenes both in the emergency forecast and early emergency response, thanks to the potential of rapid mapping. EO data is also increasingly being used for mapping useful information for planning interventions in the recovery phase, and then providing the assessment and analysis of natural hazards, from small to large regions around the globe. In this framework, Committee on Earth Observation Satellites (CEOS) has been working from several years on disasters management related to natural hazards (e.g., volcanic, seismic, landslide and flooding ones), including pilots, demonstrators, recovery observatory concepts, Geohazard Supersites and Natural Laboratory (GSNL) initiatives and multi-hazard management projects.

The session is dedicated to multidisciplinary contributions focused on the demonstration of the benefit of the use of EO for natural hazard and risk management.
The research presented might focus on:
- Addressed value of EO data in hazard/risk forecasting models
- Innovative applications of EO data for rapid hazard, vulnerability and risk mapping, the post-disaster recovery phase, and in support of disaster risk reduction strategies
- Development of tools for assessment and validation of hazard/risk models

The use of different types of remote sensing (e.g. thermal, visual, radar, laser, and/or the fusion of these) is highly recommended, with an evaluation of their respective pros and cons focusing also on future opportunities (e.g. new sensors, new algorithms).
Early-stage researchers are strongly encouraged to present their research. Moreover, contributions from international cooperation, such as CEOS and GEO initiatives, are welcome.

Space-based geodetic techniques including Interferometric Synthetic Aperture Radar (InSAR) and SAR-based change detection have become essential tools for high-quality mapping and analysis of the damage, change and deformation induced by natural and anthropogenic processes. Processing of these data have led to many new insights into understanding of geophysical and geological processes related to earthquakes, volcanic eruptions, landslides, sinkholes, floods, glaciers, and groundwater exploitation. They are also extremely useful for civil protection authorities for post-disaster response, detecting precursors of failure, and planning warning systems for areas prone to risk.
All scientists exploiting SAR/InSAR data to address challenges in the areas of the geosphere, cryosphere, biosphere and hydrosphere are cordially invited to contribute to this session. We welcome contributions from innovative processing algorithms, interpretation and modelling methods that are used for generating high-level products from SAR data for applications in earth and environmental sciences. Submissions are encouraged to cover a broad range of topics, which may include, but are not limited to, the following activities: SAR/InSAR algorithm development including cloud-based computing, deep learning and big data analysis, crustal deformation and earthquake cycle, landslides, volcanic processes, land subsidence, sinkholes, mining activities, infrastructure monitoring, flood monitoring, forest biomass and agriculture, glacier and ice dynamics, and permafrost

The use of UAV (also called Remotely Piloted Aircraft Systems - RPAS) for natural hazard characterization and hazard assessment has strongly increased in the last years. Nowadays, the massive diffusion of mini- and micro-RPAS is becoming a valuable alternative to the traditional monitoring and surveying techniques, opening novel and interesting viewpoints. The advantages of the use of RPAS are particularly important in areas characterized by hazardous natural processes, where the acquisition of high resolution remotely sensed data could be a powerful instrument to quickly assess the damages and plan effective rescues without any risk for operators.
In general, the primary goal of these systems is the collection of different data (e.g., images, LiDAR point clouds, gas or radioactivity concentrations) and the delivery of various products (e.g., 3D models, hazard maps, high-resolution orthoimages).
The use of RPAS has promising perspectives not only for natural hazards, but also in other fields of geosciences, to support a high-resolution geological or geomorphological mapping, or to study the evolution of active processes. The high repeatability of RPAS flights and their limited costs allows the multi-temporal analysis of a studied area. However, methodologies, best practices, advantages and limitations of this kind of applications are yet unclear and/or poorly shared by the scientific community.
This session aims at exploring the open research issues and possible applications of RPAS in particular for natural hazard but also for geosciences in general, collecting experiences, case studies, and results, as well as defining methodologies and best practices for their practical use. The session will concern the contributions aiming at: i) describing the development of new methods for the acquisition and processing of RPAS data, ii) introducing the use of new sensors developed or adapted to RPAS, iii) reporting new data processing methods related to image or point cloud segmentation and classification and iv) presenting original case studies that can be considered an excellent example for the scientific community.

Public information:
We decided to propose an online web meeting using the WEBEX platform.
The link to participate to the meeting is the following: https://trialcnrirpi.webex.com/trialcnrirpi/j.php?MTID=ma799e3fe9bad1d36a1ef1a0094573590
PSW: EPsqQ3Yvt29
We will also check the EGU chat to assure that everybody can participate to the session discussion, using Webex or the chat.
Please, download the detailed program

Tangible Cultural Heritage (TCH) plays a key role in building the memory and roots of human society. Unfortunately, TCH sites are often threatened by soil erosion and natural hazards (e.g. landslides, earthquakes, flooding, tropical storms, forest fire); further damage can also arise from the fragility of the site’s structures and materials with respect to anthropogenic hazards (destructive sabotage, war) and incorrect urban planning. The protection and conservation of TCH sites are pressing issues not only for the conservators/scientist’s community but for the whole society. For a correct conservation strategy it is necessary to implement a specific inter-disciplinary approach, that should be planned considering the site characteristics (topography, geomorphological-geological setting) and typology of the related hazard. In this perspective the use of remote sensing (RS) techniques applied from spaceborne, airborne and ground-based to UAV platforms (including, but not limited to, Radar interferometry, Lidar, Digital photogrammetry, Optical and Infrared imaging) combined with detailed field surveys, sample laboratory analysis, geotechnical and geophysical analysis, can provide the fundamental data for the implementation of mapping products and geodatabases, especially in developing countries with limited data, to be used as a starting point for TCH management plans. The goal of this Session is to gather high-quality original contributions and case studies applications on the use of RS techniques for protection and conservation of tangible Cultural and Natural Heritage sites (these include but are not limited to the UNESCO World Heritage and Tentative Lists) for risk mitigation practices and management plans.

Smart monitoring and observation systems for natural hazards, including satellites, seismometers, global networks, unmanned vehicles (e.g., UAV), and other linked devices, have become increasingly abundant. With these data, we observe the restless nature of our Earth and work towards improving our understanding of natural hazard processes such as landslides, debris flows, earthquakes, floods, storms, and tsunamis. The abundance of diverse measurements that we have now accumulated presents an opportunity for earth scientists to employ statistically driven approaches that speed up data processing, improve model forecasts, and give insights into the underlying physical processes. Such big-data approaches are supported by the wider scientific, computational, and statistical research communities who are constantly developing data science and machine learning techniques and software. Hence, data science and machine learning methods are rapidly impacting the fields of natural hazards and seismology. In this session, we will see research from natural hazards and seismology for processes over a broad range of time and spatial scales.

Dr. Pui Anantrasirichai of the University of Bristol, UK will give the invited presentation:
Application of Deep Learning to Detect Ground Deformation in InSAR Data

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.

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

This session is a result of a merge between GI1.3 and GM2.3:

Recent advances in image collection and topographic measurements are providing unprecedented insight into landscape and process characterization across the geosciences. In parallel, the increasing availability of digitised historical images, going back to the late 1800s, together with advances in digital photogrammetry software, have provided new opportunities for assessing and reconstructing long-term surface evolution from local to landscape scale. Such data can extend high-resolution time series into the pre-satellite era and offer exciting potential for distinguishing anthropogenic from natural causes of environmental change. For both historic and contemporary scenarios, augmenting classic techniques with digital imagery and ‘structure from motion’ (SfM) processing has democratized data access and offers a new measurement paradigm to geoscientists.

Such data are now available over spatial scales from millimetres to kilometres, and over durations of single events to lasting time series (e.g. from sub-second to century-duration time-lapse), allowing evaluation of event magnitude and frequency interrelationships. Despite a large volume of historical images available for reprocessing with modern methods, their full potential has not yet been widely exploited and uncertainties remain on the optimal types of information that can be extracted. Substantial opportunities are likely to be exposed by exploring such data resources with machine and deep learning approaches.

The session welcomes submissions from a broad range of geoscience disciplines such as geomorphology, cryosphere, volcanology, hydrology, bio-geosciences, and geology. Our goal is to create a diverse and interdisciplinary session to explore the potential of 2D and 3D image and topographic datasets for reconstructing and interpreting environments and processes, past and present. We aim to exchange experiences of modern photogrammetric and topographic measurement and modelling technologies, along with their associated data processing tools, to highlight their potentials, limitations, and challenges in different environments.

Public information:
We will have a video meeting on Friday evening starting from 6 pm CEST (UTC+2), in addition to the chat session on Friday morning, as scheduled. Authors will give talks in this video meeting, and there will be room for discussions, with the following agenda:

18:00 - 18:05 - Meeting setting and introduction to the session
18:05 - 18:17 - Amaury Dehecq, "Multidecadal elevation changes from spy satellite images: application to glaciers and landslides".
18:17 - 18:29 - Robert McNabb, "An open-source toolset for automated processing of historic spy photos: sPyMicMac".
18:29 - 18:41 - Penelope How, "PyTrx: a Python-based monoscopic terrestrial photogrammetry toolset for glaciology".
18.41 - 18:53 - Sebastian Flöry, "Development of a 3D Viewer for georeferencing and monoplotting of historical terrestrial images".
18.53 - 19:05 - Luca Carturan, "Use of WWI photos for quantitative reconstructions of glaciers along the Italian-Austrian front".
19:05 - 19:17 - Martino Terrone, "Coupling historical maps and Lidar data to recognize man-made landforms in urban areas".
19:17 - 19:25 - a little break
19:25 - 19:37 - William D. Harcourt. "Observing the cryosphere with millimetre wave radar: The case study of Rhône Glacier".
19.37 - 19:49 - Denis Feurer, "Time-SIFT: a frugal method for leveraging multi-temporal photogrammetric data without ancillary data"
19.49 - 20:01 - Helge Smebye, "Combined aerial and ground-based Structure-from-Motion modelling for a vertical rock wall face to estimate volume of failure"
20:01 - 20:13 - Sara Cucchiaro, "Terrestrial-Aerial-SfM and TLS data fusion for agricultural terrace surveys in complex topographic and land cover conditions".
20:13 - 20:25 - Andreas Mayr, "Close-range sensing and object based analysis of shallow landslides and erosion in grasslands".
20:25 - 20:37 - Kieran Wood, "UAS radiation hot-spot detection and refinement."
20:37 - break and discussion with an open end.

Join the video meeting using the following link:
https://kuei.zoom.us/j/99949141405

For an optimal audio and video experience, we suggest that you join the meeting using the Zoom application. When following the meeting link, you will be asked to install it. Alternatively, you may join the meeting using the Chrome browser.

The socio-economic impacts associated with floods are increasing. According to the International Disaster Database (EM-DAT), floods represent the most frequent and most impacting, in terms of the number of people affected, among the weather-related disasters: nearly 0.8 billion people were affected by inundations in the last decade (2006–2015), while the overall economic damage is estimated to be more than $300 billion. Despite this evidence, and the awareness of the environmental role of rivers and their inundation, our knowledge and accurate prediction of flood dynamics remain poor, mainly related to the lack of measurements and ancillary data at the global level.

In this context, remote sensing represents a value source of data and observations that may alleviate the decline in field surveys and gauging stations, especially in remote areas and developing countries. The implementation of remotely-sensed variables (such as digital elevation model, river width, flood extent, water level, land cover, etc.) in hydraulic modelling promises to considerably improve our process understanding and prediction. During the last decades, an increasing amount of research has been undertaken to better exploit the potential of current and future satellite observations, from both government-funded and commercial missions. In particular, in recent years, the scientific community has shown how remotely sensed variables have the potential to play a key role in the calibration and validation of hydraulic models, as well as provide a breakthrough in real-time flood monitoring applications. With the proliferation of open data and more Earth observation data than ever before, this progress is expected to increase.

We encourage presentations related to flood monitoring and mapping through remotely sensed data including: - Remote sensing data for flood hazard and risk mapping, including commercial satellite missions;

- Remote sensing techniques to monitor flood dynamics;
- The use of remotely sensed data for the calibration, or validation, of hydrological or hydraulic models;
- Data assimilation of remotely sensed data into hydrological and hydraulic models;
- Improvement of river discretization and monitoring based on Earth observations;
- River flow estimation from remote sensing;
- River and flood dynamics estimation from satellite (especially time lag, flow velocity, etc.)

Ground Penetrating Radar (GPR) is a safe, advanced, non-destructive and non-invasive imaging technique that can be effectively used for inspecting the subsurface as well as natural and man-made structures. During GPR surveys, a source is used to send high-frequency electromagnetic waves into the ground or structure under test; at the boundaries where the electromagnetic properties of media change, the electromagnetic waves may undergo transmission, reflection, refraction and diffraction; the radar sensors measure the amplitudes and travel times of signals returning to the surface.

This session aims at bringing together scientists, engineers, industrial delegates and end-users working in all GPR areas, ranging from fundamental electromagnetics to the numerous fields of applications. With this session, we wish to provide a supportive framework for (1) the delivery of critical updates on the ongoing research activities, (2) fruitful discussions and development of new ideas, (3) community-building through the identification of skill sets and collaboration opportunities, (4) vital exposure of early-career scientists to the GPR research community.

We have identified a series of topics of interest for this session, listed below.

1. Ground Penetrating Radar instrumentation
- Innovative GPR systems and antennas
- Equipment testing and calibration procedures

2. Ground Penetrating Radar methodology
- Survey planning and data acquisition strategies
- Methods and tools for data analysis, interpretation and visualization
- Data processing, electromagnetic modelling, imaging and inversion techniques
- Studying the relationship between GPR sensed quantities and physical properties of inspected subsurface/structures useful for application needs

3. Ground Penetrating Radar applications and case studies
- Earth sciences
- Civil and environmental engineering
- Archaeology and cultural heritage
- Management of water resources
- Humanitarian mine clearance
- Vital signs detection of trapped people in natural and manmade disasters
- Planetary exploration

4. Combined use of Ground Penetrating Radar and other geoscience instrumentation, in all applications fields

5. Communication and education initiatives and methods

-- Notes --
This session is organized by Members of TU1208 GPR Association (www.gpradar.eu/tu1208), a follow-up initiative of COST (European Cooperation in Science and Technology) Action TU1208 “Civil engineering applications of Ground Penetrating Radar”.