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GeoMultiSens: Scalable Multi-Sensor Analysis Platform for Remote Sensing Data

Urheber*innen
/persons/resource/sips

Sips,  M.
1.5 Geoinformatics, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/dransch

Dransch,  D.
1.5 Geoinformatics, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/eggi

Eggert,  Daniel
1.5 Geoinformatics, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Freytag,  Johann-Christoph
External Organizations;

/persons/resource/hollstei

Hollstein,  Andre
1.4 Remote Sensing, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Hostert,  Patrick
External Organizations;

Peters,  Mathias
External Organizations;

Pflugmacher,  Dirk
External Organizations;

Rabe,  Andreas
External Organizations;

Reinefeld,  Alexander
External Organizations;

/persons/resource/danschef

Scheffler,  D.
1.4 Remote Sensing, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Schintke,  Florian
External Organizations;

/persons/resource/segl

Segl,  K.
1.4 Remote Sensing, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Seibert,  Felix
External Organizations;

/persons/resource/taesch

Taeschner,  Jochen
1.5 Geoinformatics, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

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Zitation

Sips, M., Dransch, D., Eggert, D., Freytag, J.-C., Hollstein, A., Hostert, P., Peters, M., Pflugmacher, D., Rabe, A., Reinefeld, A., Scheffler, D., Schintke, F., Segl, K., Seibert, F., Taeschner, J.(2018): GeoMultiSens: Scalable Multi-Sensor Analysis Platform for Remote Sensing Data, Potsdam : GFZ Data Services.
https://doi.org/10.5880/GFZ.1.5.2018.005


Zitierlink: https://gfzpublic.gfz-potsdam.de/pubman/item/item_3615904
Zusammenfassung
GeoMultiSens developed an integrated processing pipeline to support the analysis of homogenized data from various remote sensing archives. The processing pipeline has five main components: (1) visual assessment of remote sensing Earth observations, (2) homogenization of selected Earth observation, (3) efficient data management with XtreemFS, (4) Python-based parallel processing and analysis algorithms implemented in a Flink cloud environment, and (5) visual exploration of the results. GeoMultiSens currently supports the classification of land-cover for Europe.