Deutsch
 
Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Konferenzbeitrag

Spectral Modeling of Plastic Litter in Terrestrial Environments - Use of 3D Hyperspectral Ray Tracing Models to Analyze the Spectral Influence of Different Natural Ground Surfaces on Remote Sensing Based Plastic Mapping

Urheber*innen
/persons/resource/kuester

Kuester,  Theres
1.4 Remote Sensing, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/mbochow

Bochow,  M.
1.4 Remote Sensing, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Externe Ressourcen
Es sind keine externen Ressourcen hinterlegt
Volltexte (frei zugänglich)
Es sind keine frei zugänglichen Volltexte in GFZpublic verfügbar
Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Kuester, T., Bochow, M. (2019): Spectral Modeling of Plastic Litter in Terrestrial Environments - Use of 3D Hyperspectral Ray Tracing Models to Analyze the Spectral Influence of Different Natural Ground Surfaces on Remote Sensing Based Plastic Mapping - Papers, 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS) (Amsterdam, Netherlands 2019).
https://doi.org/10.1109/WHISPERS.2019.8920847


Zitierlink: https://gfzpublic.gfz-potsdam.de/pubman/item/item_4950891
Zusammenfassung
Plastics have become an indispensable part of our daily life. It is a group of materials with outstanding properties for various products in a wide range of applications. They are durable, lightweight and cost-effective to manufacture. However, these advantages can develop to disadvantages if plastics are released into the environment uncontrolled and in large quantities. Here, both seas and soils form a final sink. Remote sensing has been used for many decades to observe the earth's surface and the processes that take place on it. The detection and identification of plastic litter is one of the latest applications of remote sensing. In recent publications, the potential of imaging spectroscopy has been highlighted, since it allows material identification and quantification based on material-specific absorption bands. In this study we investigate the influence of the object transparency and background surface reflectance on the detection and identification using hyperspectral remote sensing.