Rapid multispectral data sampling using Google Earth Engine
| Autor: | Alexander C. Whittaker, Philippa J. Mason, Mitch D'Arcy, Sam Brooke |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Geochemistry & Geophysics
Geospatial analysis Computer science 04 Earth Sciences 0208 environmental biotechnology Multispectral image Image processing Cloud computing 02 engineering and technology Terabyte 010502 geochemistry & geophysics computer.software_genre 01 natural sciences 09 Engineering Field (computer science) Software Computers in Earth Sciences 0105 earth and related environmental sciences Database Application programming interface business.industry 020801 environmental engineering 08 Information and Computing Sciences business computer Information Systems |
| Zdroj: | Computers and Geosciences |
| Popis: | 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 of web-based remote sensing tools available for Earth scientists, leveraging the revolution in cloud-based processing power and access to entire satellite image archives. |
| Databáze: | OpenAIRE |
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