Wright, T. orcid.org/0000-0001-8338-5935 (2024) Future of Remote Sensing for Geohazards and Resource Monitoring. In: Chaussard, E., Jones, C., Chen, J. A. and Donnellan, A., (eds.) Remote Sensing for Characterization of Geohazards and Natural Resources. https://link.springer.com/chapter/10.1007/978-3-031-59306-2_28 . Springer , Cham, Switzerland , pp. 533-551. ISBN 9783031593055
Abstract
Remote Sensing technology, observing systems, and analysis methods are advancing at a bewildering and exhilarating pace. In this chapter, I offer a personal perspective on future development in this field, focusing on applications in geohazards and resource monitoring. Remote sensing is already offering operational data streams in some areas of geohazard and resource monitoring. Future data streams will offer higher spatial and temporal sampling of phenomena, likely supplied by a mix of public and private providers. Collectively, these will enable the development of reliable monitoring systems. Developments in machine learning and modelling will ensure that new data streams can be translated into the information required by decision makers. Collaborations are required that span traditional disciplinary boundaries.
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Item Type: | Book Section |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | This item is protected by copyright. This is an author produced version of a book chapter published in Remote Sensing for Characterization of Geohazards and Natural Resources. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Science |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Inst of Geophysics and Tectonics (IGT) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 16 Jul 2024 09:33 |
Last Modified: | 16 Jul 2024 09:33 |
Published Version: | https://link.springer.com/chapter/10.1007/978-3-03... |
Status: | Published |
Publisher: | Springer |
Series Name: | https://link.springer.com/chapter/10.1007/978-3-031-59306-2_28 |
Identification Number: | 10.1007/978-3-031-59306-2_28 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:214788 |
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Filename: Chapter 5.1 - Feb 2022 version.pdf
