Remote sensing via orbiting satellite sensors is today a common tool to monitor numerous aspects related to the Earth surface and the atmosphere. The amount of data from imagery have increased tremendously since the past years, due to the increase in space missions and public and private agencies involved in this activity. A lot of these data are open-data, and academics and stakeholders in general can freely download and use it for any type of application. The bottle-neck is often not data availability anymore, but the processing resources and tools to analyse it. In particular multi-temporal analysis requires stacks of images thus digital space for storage and processing workflows that are tested and validated. Processing image by image is often not a viable approach anymore. Basic tools for multi-temporal analysis are provided via the same web interface, allowing the user to also apply parallel processing for a faster data extraction. A study case over burned areas in the north-eastern region of Italy are reported, to show how the multi-temporal analysis tools provided can be a valid source of data for further analysis. Multitemporal data consisting on the index values of each pixel inside user-defined areas can be downloaded in a spreadsheet that provides the values, the cell ids, the timestamp and the cloud and snow percentage. Also the full-resolution raster with index values that are rendered on screen can be downloaded as GeoTIFF at each specific date.

INFORSAT: AN ONLINE SENTINEL-2 MULTI-TEMPORAL ANALYSIS TOOL SET USING R CRAN

Pirotti F.;
2022

Abstract

Remote sensing via orbiting satellite sensors is today a common tool to monitor numerous aspects related to the Earth surface and the atmosphere. The amount of data from imagery have increased tremendously since the past years, due to the increase in space missions and public and private agencies involved in this activity. A lot of these data are open-data, and academics and stakeholders in general can freely download and use it for any type of application. The bottle-neck is often not data availability anymore, but the processing resources and tools to analyse it. In particular multi-temporal analysis requires stacks of images thus digital space for storage and processing workflows that are tested and validated. Processing image by image is often not a viable approach anymore. Basic tools for multi-temporal analysis are provided via the same web interface, allowing the user to also apply parallel processing for a faster data extraction. A study case over burned areas in the north-eastern region of Italy are reported, to show how the multi-temporal analysis tools provided can be a valid source of data for further analysis. Multitemporal data consisting on the index values of each pixel inside user-defined areas can be downloaded in a spreadsheet that provides the values, the cell ids, the timestamp and the cloud and snow percentage. Also the full-resolution raster with index values that are rendered on screen can be downloaded as GeoTIFF at each specific date.
2022
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3476624
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