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Hue-Angle product for low to medium spatial resolution optical satellite sensors
van der Woerd, H.J.; Wernand, M.R. (2018). Hue-Angle product for low to medium spatial resolution optical satellite sensors. Remote Sens. 10(2): 180. https://doi.org/10.3390/rs10020180
In: Remote Sensing. MDPI: Basel. ISSN 2072-4292; e-ISSN 2072-4292, meer
Peer reviewed article  

Beschikbaar in  Auteurs 

Author keywords
    hue; colour; CZCS; Landsat-7 and Landsat-8; MERIS; MODIS; MSI; OLCI; SeaWiFS

Auteurs  Top 
  • van der Woerd, H.J.
  • Wernand, M.R., meer

Abstract
    In the European Citclops project, with a prime aim of developing new tools to involve citizens in the water quality monitoring of natural waters, colour was identified as a simple property that can be measured via a smartphone app and by dedicated low-cost instruments. In a recent paper, we demonstrated that colour, as expressed mainly by the hue angle (α), can also be derived accurately and consistently from the ocean colour satellite instruments that have observed the Earth since 1997. These instruments provide superior temporal coverage of natural waters, albeit at a reduced spatial resolution of 300 m at best. In this paper, the list of algorithms is extended to the very first ocean colour instrument, and the Moderate Resolution Imaging Spectroradiometer (MODIS) 500-m resolution product. In addition, we explore the potential of the hue angle derivation from multispectral imaging instruments with a higher spatial resolution but reduced spectral resolution: the European Space Agency (ESA) multispectral imager (MSI) on Sentinel-2 A,B, the Operational Land Imager (OLI) on the National Aeronautics and Space Administration (NASA) Landsat-8, and its precursor, the Enhanced Thematic Mapper Plus (ETM+) on Landsat-7. These medium-resolution imagers might play a role in an upscaling from point measurements to the typical 1-km pixel size from ocean colour instruments. As the parameter α (the colour hue angle) is fairly new to the community of water remote sensing scientists, we present examples of how colour can help in the image analysis in terms of water-quality products

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