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Utilizing Flood Inundation Observations to Obtain Floodplain Topography in Data-Scarce Regions Keywords: digital elevation model, flood modeling, data assimilation, remote sensing, floodplains Citation: Shastry A and Durand M (2019) Utilizing Flood Inundation Observations to Obtain Floodplain Topography in Data-Scarce Regions. Front. Earth Sci. 6:243. doi: 10.3389/feart.2018.00243 Received: 06 October 2018; Accepted: 17 December 2018; Published: 11 January 2019. Edited by: Paul Bates, University of Bristol, United Kingdom Reviewed by: Andrew Mark Ireson, University of Saskatchewan, Canada Juan Pablo Rodríguez Sánchez, University of Los Andes, Colombia Copyright © 2019 Shastry and Durand. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. *Correspondence: Apoorva Shastry, shastry.7@osu.edu Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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08-19-2025
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maybe something in here can help nDSMs: How digital surface models and digital terrain models elevate your insights https://community.esri.com/t5/human-brain-webgis-questions/ndsms-how-digital-surface-models-and-digital/m-p/1635040#M76
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08-18-2025
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similar, https://community.esri.com/t5/arcgis-enterprise-questions/username-is-longer-than-20-characters/td-p/129448 https://community.esri.com/t5/arcgis-pro-questions/failed-to-execute-rename/td-p/1003369
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08-12-2025
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still a thing, December 31, 1997 ArcInfo Librarian Coverage Layer of COGO parcel polygons converted to AutoCAD and maintain true curves True Arcs, Geocoding and other musings
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08-08-2025
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@AmirBar-Maor ? https://community.esri.com/t5/arcgis-parcel-fabric-questions/creating-a-parcel-fabric-and-what-happens-to/td-p/1619991
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08-08-2025
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you can jump in here https://community.esri.com/t5/arcgis-enterprise-ideas/enterprise-automated-tls-certificate-renewal/idi-p/1606325
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07-29-2025
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How do we get rid of the "Documentation assistant" icon at the lower right web browser corner when viewing esri's online documentaion? This icon redacts as a black spot on any printed document As AGOL admin, settings > AI assistants is not enabled and don't see anything yet about beta on/off Reference: https://doc.arcgis.com/en/arcgis-online/reference/doc-assistant.htm even with print background off it redacts as a white spot
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07-29-2025
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Neural state space alignment for magnitude generalization in humans and recurrent networks Reference: Hannah Sheahan, Fabrice Luyckx, Stephanie Nelli, Clemens Teupe, Christopher Summerfield, Neural state space alignment for magnitude generalization in humans and recurrent networks, Neuron, Volume 109, Issue 7, 2021, Pages 1214-1226.e8, ISSN 0896-6273, https://doi.org/10.1016/j.neuron.2021.02.004. (https://www.sciencedirect.com/science/article/pii/S0896627321000787) Abstract: Summary A prerequisite for intelligent behavior is to understand how stimuli are related and to generalize this knowledge across contexts. Generalization can be challenging when relational patterns are shared across contexts but exist on different physical scales. Here, we studied neural representations in humans and recurrent neural networks performing a magnitude comparison task, for which it was advantageous to generalize concepts of “more” or “less” between contexts. Using multivariate analysis of human brain signals and of neural network hidden unit activity, we observed that both systems developed parallel neural “number lines” for each context. In both model systems, these number state spaces were aligned in a way that explicitly facilitated generalization of relational concepts (more and less). These findings suggest a previously overlooked role for neural normalization in supporting transfer of a simple form of abstract relational knowledge (magnitude) in humans and machine learning systems. Keywords: magnitude; alignment; representation; number; parietal cortex; generalization; normalization; neural network
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07-22-2025
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nDSMs: How digital surface models and digital terrain models elevate your insights https://www.esri.com/partners/up42-gmbh-a2T5x000008Dm9vEAC @AndresHernandezUp42 @rosenjambi
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07-22-2025
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Everything you need to know about Digital Elevation Models (DEMs), Digital Surface Models (DSMs), and Digital Terrain Models (DTMs) @AndresHernandezUp42 https://www.esri.com/partners/up42-gmbh-a2T5x000008Dm9vEAC
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07-22-2025
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Deep Neural Network Regression for Normalized Digital Surface Model Generation With Sentinel-2 Imagery Reference: Print ISSN: 1939-1404 Electronic ISSN: 2151-1535
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07-22-2025
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not this year, but that made me remember this from a few years ago: ..."Machine learning might offer additional opportunities... "Alexa: enter my traverse" Am..."
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07-15-2025
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esri's cogo has always been a separate tool so why is this reader enhancement being deployed differently? for the "required" parcel fabric, here we go again? Migrating Data From ArcStorm or Map Librarian (Coverages) to the Geodatabase and, Arc/Info New technology provides a single point of entry for all ESRI software to access ARC/INFO data in various settings. Traditional coverages ARC/INFO LIBRARIAN tiles ArcStorm databases Server support for ArcStorm on Windows NT Multifeature checkout ARC/INFO client to Spatial Database Engine (SDE ) https://www.loc.gov/preservation/digital/formats/fdd/fdd000284.shtml
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07-15-2025
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are you picking up the ArcGIS Image Server Licenses too? https://enterprise.arcgis.com/en/image/latest/get-started/windows/steps-to-get-arcgis-image-server-up-and-running.htm
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07-08-2025
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