A Google Earth Engine-enabled software for efficiently generating high-quality user-ready Landsat mosaic images
2019
Li, Huan | Wan, Wei | Fang, Yu | Zhu, Siyu | Chen, Xi | Liu, Baojian | Hong, Yang
Preparing experiment-ready images is a labor-intensive but necessary process for almost all remote sensing related studies. This short communication introduces a software to efficiently acquire large-scale high-quality and cloud-free Landsat images to support subsequent analysis and applications. The software fully leverages Google Earth Engine's processing of huge amount of remote sensing images, and the visualization on the availability and accessibility of Landsat images provided by heatmaps at both regional and global scales. The cloud percentage property and quality bands of Landsat surface reflectance products are used for masking clouds, cloud shadows, snow/ice, and low-quality pixels in this study. The software can be applied to effectively choose study areas and prepare data in different fields, such as hydrology, ecology, and human activities. This functioning open-source software can be accessible via GitHub webpages in both JavaScript and Python formats.
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