1<\/sup>James Cook University, Townsville, Australia, 2<\/sup>University of the Sunshine Coast, Brisbane, Australia, 3<\/sup>Victoria University of Wellington – Te Herenga Waka , Kelburn Parade, New Zealand, 4<\/sup>Columbia University , New York, United States, 5<\/sup>The University of Western Australia , Perth, Australia, 6<\/sup>York St John University, York, United Kingdom, 7<\/sup>University of Hull, Hull, United Kingdom<\/em><\/p>\n This session will focus on the recent advancements in geospatial science and their applications in geomorphological research. The increasing availability of high-resolution remotely sensed data from sources such as optical and radar satellite data, satellite-derived digital elevation models (DEMs), drones, LiDAR, and new “big-data” methods and analytical capabilities has revolutionised our ability to study and understand landscapes and their evolution. This session invites contributions that demonstrate the use of these cutting-edge technologies and methods in investigating surface and subsurface processes, landscape change, and hazards.<\/p>\n We welcome abstracts spanning the full spectrum of relevant methods and topics, including but not limited to satellite altimetry to monitor coastal change; drones and LiDAR for detailed geomorphological mapping and high-resolution change detection; ground-penetrating radar for subsurface analysis; and big-data analytics of fluvial systems. The session will explore how existing, new, and emerging data and methods can address critical geomorphological questions, enhance our understanding of natural processes, contribute to hazard management, and advance the geomorphology discipline.<\/p>\n This session encourages an “open-data, open-methods” approach to engagement and collaboration within and beyond this session, in order to share methods and experiences (including failures and successes) that advance the integration of geospatial data and technologies with geomorphological understanding across systems and environments. We encourage contributions that highlight interdisciplinary approaches, case studies from a diverse range of geomorphic settings, and scientists across all career stages.<\/p>\n Daniel H\u00f6lbling1<\/sup>, Andrew Neverman2<\/sup>, Melanie Stammler3<\/sup>, Helen Dias4<\/sup>, Elena Nafieva1<\/sup>, Lorena Abad Crespo1<\/sup><\/strong><\/p>\n 1<\/sup>Department of Geoinformatics – Z_GIS, University of Salzburg, Salzburg, Austria, 2<\/sup>Manaaki Whenua – Landcare Research, Palmerston North, New Zealand, 3<\/sup>Department of Geography, University of Bonn, Bonn, Germany, 4<\/sup>Institute of Energy and Environment, University of S\u00e3o Paulo, S\u00e3o Paulo, Brazil<\/em><\/p>\n Geospatial and remote sensing methods are advancing at a rapid pace, along with a growing amount of spatial data available for geomorphological and landscape dynamics applications. In particular, repeated data acquisitions have increased the temporal frequency of data, opening new opportunities for analysing geomorphological changes over time. This session showcases and explores different geospatial and remote sensing techniques and methods for mapping, analysing and monitoring geomorphological feature changes and landscape dynamics related to fluvial, glacial, volcanic, hillslope, tectonic, coastal, and aeolian processes.<\/p>\n Technologies and methods in focus include but are not limited to the application of aerial or satellite remote sensing with LiDAR, UAV, radar, or multispectral sensors; the use of raster and vector data cubes for the analysis of big Earth Observation (EO) data, including advances in cloud-based EO platforms for time series mapping tasks; development of geomorphometry and terrain analysis techniques with a temporal component; and novel geospatial analysis methods and data acquisition techniques for geomorphological mapping and monitoring in general.<\/p>\n We welcome methodological and applied contributions that highlight the novel use of spatial methods for geomorphological time series analysis, but also those that expand on the challenges of data processing and analysis. Contributions that showcase a reproducible workflow and those that are in development are especially welcome.<\/p>\n Professor Allen Gontz, Professor Harry Jol<\/strong><\/p>\n 1<\/sup>Clarkson University, Potsdam, United States, 2<\/sup>University Of Wisconsin-Eau Claire, Eau Claire, WI, United States<\/em><\/p>\n The session will focus on the application of ground penetrating radar (GPR) and other near-surface geophysical methods to better understand geomorphic environments. Abstracts are sought that demonstrate how GPR and shallow geophysical methods can help one to better understand key questions about subsurface properties, stratigraphy and processes geomorphic.\u00a0 These geophysical methods are used in many geomorphic environments such as coastal, aeolian, fluvial, glacial as well as other unique geoarchaeological settings.\u00a0 Presentations could also include how fundamental science of geophysical imaging such as data acquisition, processing, inversion, interpretation can influence resulting visualization.\u00a0 A conference workshop on the applications of GPR in geomorphic environments is planned.<\/p>\n\t\t\t\t Technological advances in geomorphology Geospatial Innovations in Geomorphological Research: Integrating Remote Sensing and Advanced Technologies Dr Ben Jarihani1,2, Dr Anya Leenman3, Dr Austin Chadwick4, Associate Professor Nik Callow5, Dr David Milan7, Dr Arved Schwendel6 1James Cook University, Townsville, Australia, 2University of the Sunshine Coast, Brisbane, Australia, 3Victoria University of Wellington – Te Herenga Waka ,…<\/p>\n","protected":false},"author":4,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-2398","page","type-page","status-publish","hentry"],"yoast_head":"\n
\nNovel geospatial and remote sensing methods for geomorphological feature mapping and monitoring<\/h3>\n
\nProviding 2D & 3D Subsurface Imagery of Geomorphic Environments: Ground Penetrating Radar and Near-Surface Geophysics<\/h3>\n
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