Earth observation satellites are collecting vast amounts of free and openly accessible data with immense potential to support environmental, economic, and social fields. As the availability of remotely sensed data increases, so do the methods for accessing and processing it. Many solutions exist for creating cloud-free image composites from often cloudy satellite data, but these typically require coding skills or in-depth training in remote-sensing techniques. This technical barrier prevents many researchers and practitioners from utilising available satellite data. The few user-friendly solutions that exist often have limitations in terms of data export size and quality assessment capabilities. We developed GEE-PICX, a web application with an intuitive graphical user interface on the cloud computing platform Google Earth Engine. This tool addresses the aforementioned challenges by creating cloud-free, analysis-ready image composites for user-defined areas and time periods. It utilises Sentinel-2 and Landsat 5, 7, 8, and 9 images and offers global coverage. Users can aggregate image composites annually or seasonally, with data availability starting from 1984 (the launch of Landsat 5). The workflow automatically filters all available satellite data according to user input, removing clouds, cloud shadows, and snow. It provides spectral band information, calculates various thematic spectral indices (including vegetation, burn, built-up area, bare soil, snow, moisture, and water indices), and includes a quality assessment band indicating the number of valid scenes per pixel. GEE-PICX offers a customizable tool for creating custom data products from freely accessible satellite data, catering to researchers with limited remote sensing experience. It provides extensive temporal and global spatial coverage, with server-side processing eliminating hardware constraints. The tool facilitates easy export of time series as ready-to-use rasters with numerous spectral indices, supporting environmental programmes and biodiversity research across various disciplines.

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GEE-PICX: Generating cloud-free Sentinel-2 and Landsat image composites and spectral indices for custom areas and time frames - a Google Earth Engine web application
GEE-PICX: Generating cloud-free Sentinel-2 and Landsat image composites and spectral indices for custom areas and time frames - a Google Earth Engine web application

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.31223/X5RT1W. This is version 3 of this Preprint.

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Authors

Luisa Pflumm, Hyeonmin Kang, Andreas Wilting, Jürgen Niedballa

Abstract

Earth observation satellites are collecting vast amounts of free and openly accessible data with immense potential to support environmental, economic, and social fields. As the availability of remotely sensed data increases, so do the methods for accessing and processing it. Many solutions exist for creating cloud-free image composites from often cloudy satellite data, but these typically require coding skills or in-depth training in remote-sensing techniques. This technical barrier prevents many researchers and practitioners from utilising available satellite data. The few user-friendly solutions that exist often have limitations in terms of data export size and quality assessment capabilities. We developed GEE-PICX, a web application with an intuitive graphical user interface on the cloud computing platform Google Earth Engine. This tool addresses the aforementioned challenges by creating cloud-free, analysis-ready image composites for user-defined areas and time periods. It utilises Sentinel-2 and Landsat 5, 7, 8, and 9 images and offers global coverage. Users can aggregate image composites annually or seasonally, with data availability starting from 1984 (the launch of Landsat 5). The workflow automatically filters all available satellite data according to user input, removing clouds, cloud shadows, and snow. It provides spectral band information, calculates various thematic spectral indices (including vegetation, burn, built-up area, bare soil, snow, moisture, and water indices), and includes a quality assessment band indicating the number of valid scenes per pixel. GEE-PICX offers a customizable tool for creating custom data products from freely accessible satellite data, catering to researchers with limited remote sensing experience. It provides extensive temporal and global spatial coverage, with server-side processing eliminating hardware constraints. The tool facilitates easy export of time series as ready-to-use rasters with numerous spectral indices, supporting environmental programmes and biodiversity research across various disciplines.


DOI

https://doi.org/10.31223/X5RT1W

Subjects

Environmental Sciences

Keywords

satellite imagery, remote sensing, Cloud-free image mosaic, Environmental monitoring, time series, cloud masking

Dates

Published: 2023-12-10 23:06

Last Updated: 2024-10-24 22:01

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License

CC-BY Attribution-NonCommercial 4.0 International

Additional Metadata

Conflict of interest statement:
None

Data Availability (Reason not available):
The link to the GEE-PICX application is provided on this Github page: https://github.com/Luisa-del/GEE-PICX. The GitHub page also contains a detailed user guide. In order to use the GEE-PICX application, users need to log in to Google Earth Engine using their Google account. The application opens in JavaScript code editor mode to allow for data export. From the application, user inputs are specified and products can be exported to users' Google drive for download. An R script to convert null values of an exported raster to NA is provided on Github. We furthermore provide an R Shiny app to visualize and query time series of annual images downloaded via GEE-PICX on GitHub.