GM2 – Quantitative Methods and Digital Data in Geomorphology
Frontiers in Geomorphometry and Earth Surface Dynamics: Possibilities, Limitations and Perspectives
This session aims to bridge the existing gap between the process-focused fields (hydrology, geomorphology, soil sciences, natural hazards, planetary science, geo-biology, archaeology) and the technical domain (engineering, computer vision, machine learning, and statistics) where terrain analysis approaches are developed.
The rapid growth of survey technologies and computing advances and the increase of data acquisition from various sources (platforms and sensors) has led to a vast data swamp with unprecedented spatio-temporal range, density, and resolution (from submeter to global scale data), which requires efficient data processing to extract suitable information. The challenge is now the interpretation of surface morphology for a better understanding of processes at a variety of scales, from micro, to local, to global.
We aim to foster inter-disciplinarity with a focus on new techniques in digital terrain analysis and production from any discipline which touches on geomorphometry, including but not exclusive to geomorphology (e.g., tectonic/volcanic/climatic/glacial), planetary science, archaeology, geo-biology, natural hazards, computer vision, remote sensing, image processing.
We invite submissions related to the successful application of geomorphometric methods, innovative geomorphometric variables as well as their physical, mathematical and geographical meanings. Submissions related to new techniques in high-resolution terrain or global scale data production and analysis, independent of the subject, as well as studies focused on the associated error and uncertainty analyses, are also welcome. We actively encourage contributors to present work “in development”, as well as established techniques being used in a novel way. We strongly encourage young scientists to contribute and help drive innovation in our community, presenting their work to this session.
We want to foster collaboration and the sharing of ideas across subject-boundaries, between technique developers and users, enabling us as a community to fully exploit the wealth of knowledge inherent in our digital landscape. Just remember, the driver for new ideas and applications often comes from another speciality, discipline or subject: Your solution may already be out there waiting for you!
High Resolution Topography in the Geosciences: Methods and Applications (including Arne Richter Award for Outstanding ECS Lecture by Giulia Sofia) (co-sponsored by JpGU)
Topographic data are fundamental to landscape characterization across the geosciences, for monitoring change and supporting process modelling. Over the last decade, the dominance of laser-based instruments for high resolution data collection has been challenged by advances in digital photogrammetry and computer vision, particularly in ‘structure from motion’ (SfM) algorithms, which offer a new paradigm to geoscientists.
High resolution topographic (HiRT) data are now obtained over spatial scales from millimetres to kilometres, and over durations of single events to lasting time series (e.g. from sub-second to decadal-duration time-lapse), allowing evaluation of dependencies between event magnitudes and frequencies. Such 4D-reconstruction capabilities enable new insight in diverse fields such as soil erosion, micro-topography reconstruction, volcanology, glaciology, landslide monitoring, and coastal and fluvial geomorphology. Furthermore, broad data integration from multiple sensors offers increasingly exciting opportunities.
This session will evaluate the advances in techniques to model topography and to study patterns of topographic change at multiple temporal and spatial scales. We invite contributions covering all aspects of HiRT reconstruction in the geosciences, and particularly those which transfer traditional expertise or demonstrate a significant advance enabled by novel datasets. We encourage contributions describing workflows that optimize data acquisition and post-processing to guarantee acceptable accuracies and to automate data application (e.g. geomorphic feature detection and tracking), and field-based experimental studies using novel multi-instrument and multi-scale methodologies. A major goal is to provide a cross-disciplinary exchange of experiences with modern technologies and data processing tools, to highlight their potentials, limitations and challenges in different environments.
Solicited speaker: Kuo-Jen Chang (National Taipei University of Technology) - UAS LiDAR data processing, quality assessment and geosciences prospects
Bridging the gap: combining numerical models of surface processes with Earth observations
A key goal within geomorphic research is understanding the links between topographic form, erosion rates, and sediment production, transport and deposition. Numerical modelling, by allowing the creation of controlled analogues of natural systems, provides exciting opportunities to explore landscape evolution and generate testable predictions. Furthermore, the advancement of Earth surface monitoring capabilities in recent decades, such as the increasing availability of high-resolution topographic data and new techniques for constraining rates of erosion and deposition, allows the direct testing of numerical models at larger spatial and temporal scales than previously possible. Combining these different techniques provides exciting opportunities for furthering our understanding of Earth surface processes.
In this session, we invite contributions that use numerical modelling to investigate landscape evolution in a broad sense, and over a range of spatial and temporal scales. We welcome studies using models to constrain one or more of: erosion rates and processes, sediment production, transport and deposition, and sediment residence times. We also particularly wish to highlight studies that combine numerical modelling with direct Earth surface process monitoring techniques, such as topographic, field, stratigraphic, or geochronological data. There is no geographical restriction: studies may be focused on mountain environments or sedimentary basins, or they may establish links between the two; studies beyond planet Earth are welcome too.
Novel Approaches in Geochronology: Quantifying Geomorphological Processes and Landscape Dynamics
Geochronological frameworks are essential for the study of landscape evolution. Over the last decades, geochronological techniques such as cosmogenic nuclides, thermochronology, radiocarbon and luminescence dating have improved in accuracy, precision, and temporal range. Recently, the development of new approaches, new isotopic/mineral systems, and the increasing combination of these techniques are expanding their range of applications. This session explores these advances and novel applications, which include the study of erosional rates and processes, sediment provenance, burial and transport times, bedrock exposure or cooling histories, landscape dynamics, and the examination of potential biases and discordances in geochronological data. We welcome contributions that use dating tools which are established or in development, particularly those that quantify geomorphological processes with novel approaches and/or generic implications. We encourage studies that combine different techniques (e.g. CRN, luminescence, thermochronology, etc.) or data sets (e.g. field, remote sensing, numerical modelling), and/or highlight the latest developments and open questions in the application of geochronometers to landscape evolution questions.
Invited speakers: Prof. Kristina Hippe and Prof. Todd Ehlers.
Geochronological Tools for Environmental Reconstruction and the INTegration of Ice core, MArine and TErrestrial records
During the Quaternary Period, the last 2.6 million years of Earth's history, changes in environments and climate shaped human evolution. In particular, large-scale features of atmospheric circulation patterns varied significantly due to the dramatic changes in global boundary conditions which accompanied abrupt changes in climate. Reconstructing these environmental changes relies heavily on precise and accurate chronologies. Radiocarbon dating continues to play a vital role in providing chronological control over the last 50,000 years, but advances in recent years on a range of other geochronological techniques that are applicable to the Quaternary have made available a much wider diversity of methods. In this session, contributions are particularly welcome that aim to (1) reduce, quantify and express dating uncertainties in any dating method, including high-resolution radiocarbon approaches, (2) use established geochronological methods to answer new questions, (3) use new methods to address longstanding issues, or (4) combine different chronometric techniques for improved results, including the analysis of chronological datasets with novel methods, such as Bayesian age-depth modelling. Applications may aim to understand long-term landscape evolution, quantify rates of geomorphological processes, or provide chronologies for records of climate change.
To fully diagnose the mechanisms behind the complex teleconnections of past abrupt climate transitions accurate dating and correlation is imperative. This is one of the main goals of the INTIMATE initiative. Furthermore, we aim towards a global approach to integrating climate data, by considering archives from the tropics to the poles and develop our understanding of proxy-sensitivities to different aspects of climate and environmental change (e.g. temperature, precipitation, nutrient availability, sunlight). Finally, we should test our hypotheses and challenge our ideas using models of atmosphere-ocean-biosphere processes. INTIMATE aims to provide a better understanding of the mechanisms of abrupt climate change, with a particular emphasis on the integration and interpretation of global records of abrupt climate changes during the last glacial to interglacial cycle.
Our invited speaker is Prof. Tim Jull, the Editor of the Radiocarbon Journal who will speak about
"Annual carbon-14 variability in tree-rings: Causes and Implications for the calibration curve."
Learning from spatial data: unveiling the geo-environment through quantitative approaches
The interactions between geo-environmental and anthropic processes are increasing due to the ever-growing population and its related side effects (e.g., urban sprawl, land degradation, natural resource and energy consumption, etc.). Natural hazards, land degradation and environmental pollution are three of the possible “interactions” between geosphere and anthroposphere. In this context, spatial and spatiotemporal data are of crucial importance for the identification, analysis and modelling of the processes of interest in Earth and Soil Sciences. The information content of such geo-environmental data requires advanced mathematical, statistical and geomorphometric methodologies in order to be fully exploited.
The session aims to explore the challenges and potentialities of quantitative spatial data analysis and modelling in the context of Earth and Soil Sciences, with a special focus on geo-environmental challenges. Studies implementing intuitive and applied mathematical/numerical approaches and highlighting their key potentialities and limitations are particularly sought after. A special attention is paid to spatial uncertainty evaluation and its possible reduction, and to alternative techniques of representation of spatial data (e.g., visualization, sonification, haptic devices, etc.).
In the session, two main topics will be covered (although the session is not limited to them!):
1) Analysis of sparse (fragmentary) spatial data for mapping purposes with evaluation of spatial uncertainty: geostatistics, machine learning, statistical learning, etc.
2) Analysis and representation of exhaustive spatial data at different scales and resolutions: geomorphometry, image analysis, machine learning, pattern recognition, etc.
Issues, limits and solutions for using drone data in the Geosciences
Drones (also Unmanned Aerial Vehicles/Systems (UAV/UAS), Remotely Piloted Aircraft Systems) have revolutionised the ability to collect ultra-high spatial resolution spatial data at the scale of millimetres to centimetres. This has allowed a new scale of mapping and process research in the geosciences. Drones and associated sensors can be cost-effective compared with high spatial resolution airborne and satellite data, providing flexibility in deployment. The development curve of miniaturized drone sensors and data processing software / hardware solution has been transformative, but has not perhaps satisfied scientists’ expectations. Many geoscientists are grappling with quality, stability and reliability in the collection and calibration of data from sensors that have over-promised but under-delivered in practice, or are simply not suited to particular applications. Drone hardware and software has provided tools to process the data, but many tools are black-box, and the resulting observations have quality issues that can impact the questions that are being answered by geoscientists in mapping and process studies. This PICO session will share peoples’ knowledge of the issues and limits of sensors and processing workflows, focusing on communicating and sharing solutions for addressing and advancing our understanding of how ultra-high spatial resolution drone data can (and cannot) be collected, calibrated, processed and then used to answer research questions in the geosciences. Specific themes we wish to promote include:
- Work quantifying sensor quality, stability and reliability in the collection of data, with a focus on sharing information around quantifying limits, providing solutions and communicating best (or limits on) use of data,
- Best practice in the calibration of data (particularly spectral and thermal sensors), and relating this to levels of processing/calibration/validation required to answer geoscience questions,
- Collection and processing of LiDAR and photogrammetry Structure from Motion (SfM) data and the use of fine-resolution digital elevation models (DEMs) in the geosciences,
- Limitations and opportunities in using drones for mapping studies in the geosciences,
- Limitations and opportunities in using drones for process studies in the geosciences,
- Related work that focuses on solutions to issues experienced in using drone data in the geosciences.
- Examples of applications that are affected or overcome issues related to sensor quality, calibration and data pre-processing (orthomosaicing, radiometric correction, vignette correction, BRDF correction, conversion of digital numbers to at-surface reflectance).
We are pleased to announce a keynote presentation from Dr Patrice Carbonneau (University of Durham).
Remotely Piloted Aircraft Systems (RPAS) and geosciences: innovation in methodologies, sensors and activities
The use of Remotely Piloted Aircraft Systems (RPAS) for geosciences applications has strongly increased in last years. Nowadays the massive diffusion of mini- and micro-RPAS is becoming a valuable alternative to the traditional monitoring and surveying applications, opening new 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, etc.) and the delivery of various products (e.g., 3D models, hazard maps, high-resolution orthoimages, etc.).
The possible use of RPAS has promising perspectives not only for natural hazards, but also in the different field of geosciences, to support a high-resolution geological or geomorphological mapping, or to study the evolution of active processes. The high repeatability of RPAS flight 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 geosciences, collecting experiences, case studies, and results, as well as define 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 dataset, 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.
Modelling and monitoring tectonic processes (with special attention to transpression)
Analogue experiments and numerical simulation have become an integral part of the Earth explorer's toolbox to select, formulate, and test hypotheses on the origin and evolution of geological phenomena. In addition, a growing body of structural ground truth and geophysical observations as well as profound advances in remote sensing techniques offers to compare the modeled predictions with nature
To foster synergy between modelers and geologists focusing on field and geophysical or remote sensing data, we provide a multi-disciplinary platform to discuss research on tectonics, structural geology, rock mechanics, geodynamics, volcanology, geomorphology, and sedimentology.
We therefore invite contributions demonstrating the state-of-the-art in analogue and numerical / analytical modelling on a variety of spatial and temporal scales, varying from earthquakes and volcanic eruptions to plate tectonics and landscape evolution, as well as contributions focusing on remote sensing, geophysical and geodetic studies, with a specific focus on transpression. Local to crustal scale transpression is the most common deformation regime recognized at active and ancient plate boundaries formed by oblique plate convergence, and although the concept of strain partitioning is well established, the heterogeneity of transpressive deformation continues to be an important topic.
We especially welcome those presentations that discuss model strengths and weaknesses, challenge the existing limits, or compare/combine the different modelling techniques with observations from the natural world to realistically simulate and better understand the Earth's behavior.
Innovative methods to facilitate open science and data analysis in hydrology - from data collection in challenging environments to data sharing, visualization and modelling
Hydrology relies strongly on heterogeneous data sets and a multitude of computational models. However, several challenges remain in order to obtain all information from the data and model results and, at the same time, carry out scientific work that is reproducible and repeatable.
Data collection is generally the first step in the scientific process, but collecting spatially and temporally dense data sets can be challenging, especially in extreme environments, such as dry, humid or cold areas. Therefore, environmental data sets are often sparse and do not allow us to fully understand the hydrological and associated environmental processes dominant in these areas. Therefore, innovative ideas are needed to build methods able to extract information from the available data and make use of the many signatures in the observations that are still to be explored.
On the other hand, an increasing amount of heterogenous data becomes available from diverse sources such as remote sensing, social media or citizen science. Platforms and tools are needed to interpret such data, identify and understand patterns, trends, and uncertainty and to draw conclusions and implications from data-driven research. New methods for data visualization can be a pivotal for our ability to make new sense of heterogeneous data and to communicate complex datasets and findings in an appropriate way to other researchers and the public.
Eventually, the full scientific process should be open, reproducible and repeatable. Many data sets contain a wide range of derived variables that cannot be easily re-computed from the raw data, either because the raw data is not available or because the computational steps are not adequately described. As a result, very few published results in hydrology are reproducible for the general reader. However, more and more software tools and platforms are becoming available to support open science, partly as a result of collaborations between software experts and hydrologists.
This session invites contributions on topics ranging from data collection and visualization to sharing model code and reproducible workflows, e.g.:
- Platforms and tools for improved data visualization, open science, scientific collaboration and/or communication with a larger audience
- Use of innovative data and data collection techniques, with a focus on data sparse environments
- Case studies illustrating challenges and solutions related to open science
- Innovative types of data and their visualizations
This session is organized in cooperation with the Young Hydrologic Society (youngHS.com).