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Analysis-ready satellite data mosaics from Landsat and Sentinel-2 imagery
Hans Ole Ørka1, Jãnis Gailis2, Mathias Vege2
1Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, Ås NO-1432, Norway.
Methodsx
|January 24, 2023
Summary
Geomosaic creates analysis-ready satellite data mosaics from Landsat and Sentinel-2 imagery. This open-source Python tool preserves pixel metadata and supports diverse analysis needs.
Area of Science:
- Earth Observation
- Geospatial Analysis
- Remote Sensing
Background:
- High-resolution satellite imagery from Landsat and Sentinel-2 archives is abundant.
- Mosaicking is a crucial preprocessing step for analyzing satellite data.
- Existing methods may not preserve data structure, metadata, or support specific temporal requirements.
Purpose of the Study:
- To present Geomosaic, a novel method for creating analysis-ready satellite data mosaics.
- To address the need for preserving original data structure and metadata.
- To support diverse analytical applications and institutional computing requirements.
Main Methods:
- Developed an open-source algorithm coded in Python named Geomosaic.
- Designed the method to process Landsat and Sentinel-2 satellite imagery.
- Ensured the tool supports in-house computing centers and multiple platforms.
Main Results:
- Geomosaic produces analysis-ready satellite data mosaics.
- The generated mosaics retain pixel metadata essential for further analysis.
- The method is applicable to Landsat and Sentinel-2 archives.
Conclusions:
- Geomosaic offers an effective solution for satellite data mosaicking.
- The tool enhances the usability of satellite imagery for various scientific applications.
- The open-source nature promotes accessibility and wider adoption in remote sensing research.
Keywords:
Earth observationGeomosaic - analysis-ready satellite data mosaicsLand cover classificationOptical satellite imageryPreprocessingRemote sensingMore Related Videos
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