0000000000965804

AUTHOR

Kimmo Nurminen

showing 2 related works from this author

CHOOSING OF OPTIMAL REFERENCE SAMPLES FOR BOREAL LAKE CHLOROPHYLL A CONCENTRATION MODELING USING AERIAL HYPERSPECTRAL DATA

2018

Abstract. Optical remote sensing has potential to overcome the limitations of point estimations of lake water quality by providing spatial and temporal information. In open ocean waters the optical properties are dominated by phytoplankton density, while the relationship between color and the constituents is more complicated in inland waters varying regionally and seasonally. Concerning the difficulties relating to comprehensive modeling of complex inland and coastal waters, the alternative approach is considered in this paper: the raw digital numbers (DN) recorded using aerial remote hyperspectral sensing are used without corrections and derived by means of regression modeling to predict C…

lcsh:Applied optics. Photonics010504 meteorology & atmospheric scienceshyperspectral imagingwater quality monitoringchlorophyll a0211 other engineering and technologies02 engineering and technologylcsh:Technology01 natural sciencesStandard deviationPhytoplanktonPredictabilityCluster analysis021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensinglcsh:Tlcsh:TA1501-1820Hyperspectral imagingSampling (statistics)Statistical modelRegression analysislake water coloraerial remote sensinglcsh:TA1-2040Environmental sciencelcsh:Engineering (General). Civil engineering (General)The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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UAV-based hyperspectral monitoring of small freshwater area

2014

Recent development in compact, lightweight hyperspectral imagers have enabled UAV-based remote sensing with reasonable costs. We used small hyperspectral imager based on Fabry-Perot interferometer for monitoring small freshwater area in southern Finland. In this study we shortly describe the utilized technology and the field studies performed. We explain processing pipeline for gathered spectral data and introduce target detection-based algorithm for estimating levels of algae, aquatic chlorophyll and turbidity in freshwater. Certain challenges we faced are pointed out.

ta113hyperspectral imaginguavtarget detectionta1171Hyperspectral imagingPipeline (software)InterferometryGeographyRemote sensing (archaeology)Fabry-Perot interferometerSpectral datafreshwaterta218Remote sensing
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