Imperial College London
Portrait Picture

Dr Alex Whittaker

Faculty of Engineering, Department of Earth Science & Engineering

Reader in Landscape Dynamics
 
 
 
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Contact

 

+44 (0)20 7594 7491a.whittaker Website

 
 
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Location

 

3.51Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Brooke:2020:10.1016/j.cageo.2019.104366,
author = {Brooke, SAS and DArcy, M and Mason, PJ and Whittaker, AC},
doi = {10.1016/j.cageo.2019.104366},
journal = {Computers & Geosciences},
pages = {104366--104366},
title = {Rapid multispectral data sampling using Google Earth Engine},
url = {http://dx.doi.org/10.1016/j.cageo.2019.104366},
volume = {135},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - The advent of cloud-based GIS tools has enabled the rapid exploration and processing of geospatial datasets. The Google Earth Engine (GEE) platform provides a library of algorithms and a powerful application programming interface (API) to produce flexible cloud-based applications that leverage Google’s computing infrastructure for geospatial analysis. We introduce ”Spectral Point”, a new GUI tool developed in GEE that allows users to explore, process and extract multispectral data rapidly within a single browser window. The ability to access and measure spectral signals from surface deposits using the entire available Landsat and Sentinel 2 archive is of tremendous benefit to geomorphic research, removing the need to download and process terabytes worth of imagery. Spectral values from composite imagery collected in GEE that relate to changes in surface mineral composition agree with corresponding point values using conventional desktop Landsat processing. The ”Spectral Point” tool makes it fast and simple to extract quantitative, contrast-corrected brightness data from multispectral imagery compared conventional desktop-based approaches. At the same time, the user needs no experience developing code, proprietary third-party software or dedicated high-performance computing and only a modern web browser. The ”Spectral Point” tool has many potential applications in the remote study of Earth’s surface; for example, we explore a case study from the western United States that demonstrates how the tool can be used for mapping, geochronology, and estimating weathering rates for Quaternary landforms. With increasing numbers of satellites, we are now faced with a growing deluge of geospatial data. Cloud-based solutions to mapping, field reconnaissance and image processing will be increasingly necessary to handle this valuable but untapped satellite image resource. ”Spectral Point” is an example of a new generation o
AU  - Brooke,SAS
AU  - DArcy,M
AU  - Mason,PJ
AU  - Whittaker,AC
DO  - 10.1016/j.cageo.2019.104366
EP  - 104366
PY  - 2020///
SN  - 0098-3004
SP  - 104366
TI  - Rapid multispectral data sampling using Google Earth Engine
T2  - Computers & Geosciences
UR  - http://dx.doi.org/10.1016/j.cageo.2019.104366
UR  - https://www.sciencedirect.com/science/article/pii/S0098300419300251?via%3Dihub
UR  - http://hdl.handle.net/10044/1/77580
VL  - 135
ER  -
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