G019
The Continuing Revolution - Exploring New Methods and Science with High Resolution Topographic Datasets

Session ID#: 77367

Session Description:
The broad availability of high resolution topography allows new science questions to be addressed over a vast array of spatial scales.
The advent of automated processing pipelines and high performance computing platforms are transforming the rate at which the evolving surface of the planet can be observed and analyzed. We encourage contributions that examine both the dynamic natural processes or human actions that shape the surface of the Earth and those that detail new novel and innovative practices that generate or use high resolution topographic datasets. We invite submissions from a variety of disciplines that consider the processes that occur at the boundaries of domains, for example, between the oceans and ice sheets, across coastal environments, and at the transition from urbanized areas to rural hinterlands. Process studies of hazards, land use changes or climate driven geomorphological changes, and explorations of innovative methods that drive scientific discovery are both particularly welcome.
Index Terms:

0758 Remote sensing [CRYOSPHERE]
1240 Satellite geodesy: results [GEODESY AND GRAVITY]
4337 Remote sensing and disasters [NATURAL HAZARDS]
8485 Remote sensing of volcanoes [VOLCANOLOGY]

Primary Convener:  Michael J Willis, University of Colorado Boulder, CIRES and Department of Geological Sciences, Boulder, CO, United States
Conveners:  David E Shean, University of Washington, Seattle, WA, United States and Paul J Morin, Polar Geospatial Center, St Paul, MN, United States
Primary Liaison:  Michael J Willis, Cornell University, Ithaca, NY, United States
 
Measuring Landslides and Volcanic Eruptions with ArcticDEM (499389)
Chunli Dai, Ohio State University Main Campus, Byrd Polar Research Center, Columbus, OH, United States, Ian Howat, Ohio State University, Byrd Polar & Climate Research Center, Columbus, OH, United States and Jeffrey Todd Freymueller, Michigan State University, Earth and Environmental Sciences, East Lansing, MI, United States
 
Improved DInSAR time series using high-resolution optical DEMs (499961)
Kristy French Tiampo, University of Colorado Boulder, Department of Geological Sciences, Boulder, United States, Magali Barba-Sevilla, University of Colorado at Boulder, Cooperative Institute for Research in Environmental Sciences and Dept. of Geological Sciences, Boulder, CO, United States, Mylene Fabienne Jacquemart, University of Colorado, Boulder, Cooperative Institute for Research in Environmental Sciences and Department of Geological Sciences, Boulder, United States, Pablo J González, University of Liverpool, COMET, Department of Earth, Ocean, and Ecological Sciences, Liverpool, United Kingdom, Cameron McKee, University of Western Ontario, Earth Sciences, London, ON, Canada, Sergey V Samsonov, Canada Centre for Remote Sensi, Ottawa, ON, Canada and Michael J Willis, University of Colorado Boulder, CIRES and Department of Geological Sciences, Boulder, CO, United States
 
利用PS-InSAR和UAV圖像分析地形細微變形 - 以台灣柴山為例 (505137)
Lin Dy YI, Sanmin Dist., Kaohsiung, Taiwan, Chia-Sheng Hsieh, National Kaohsiung University of Science and Technology, civil engineering, Kaohsiung, Taiwan and Mong-Han Huang, University of Maryland, College Park, College Park, MD, United States
 
NOAA’s High Resolution Topographic and Bathymetric Datasets and Derivative Products (552815)
Hilina Mequanint Tarekegn, NOAA NGS, Silver Spring, MD, United States, Brian Madore, NOAA, RSD, Silver Spring, MD, United States and Gretchen Imahori, National Geodetic Survey, Silver Spring, MD, United States
 
Sand Dune Video Prediction: From Cellular Automaton to Convolutional Neural Networks (CNNs) (622584)
Divya Mohan, University of California, Berkeley, College of Engineering, Berkeley, CA, United States, Jenna Horrall, James Madison University, Computer Science, Chesapeake, VA, United States, Kelly Kochanski, University of Colorado at Boulder, Geological Sciences, Boulder, CO, United States and Barry Rountree, Lawrence Livermore National Laboratory, Computation Division, Livermore, United States
See more of: Geodesy
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