LEADER 04222nam  2201009z- 450 
001 9910557368003321
005 20231214133649.0
035   $a(CKB)5400000000042211
035   $a(oapen)https://directory.doabooks.org/handle/20.500.12854/76303
035   $a(EXLCZ)995400000000042211
100   $a20202201d2021      |y             0
101 0 $aeng
135   $aurmn|---annan
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aHyperspectral Imaging for Fine to Medium Scale Applications in Environmental Sciences
210   $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2021
215   $a1 electronic resource (218 p.)
311   $a3-0365-0878-3 
311   $a3-0365-0879-1 
330   $aThe aim of the Special Issue ?Hyperspectral Imaging for Fine to Medium Scale Applications in Environmental Sciences? was to present a selection of innovative studies using hyperspectral imaging (HSI) in different thematic fields. This intention reflects the technical developments in the last three decades, which have brought the capacity of HSI to provide spectrally, spatially and temporally detailed data, favoured by e.g., hyperspectral snapshot technologies, miniaturized hyperspectral sensors and hyperspectral microscopy imaging. The present book comprises a suite of papers in various fields of environmental sciences?geology/mineral exploration, digital soil mapping, mapping and characterization of vegetation, and sensing of water bodies (including under-ice and underwater applications). In addition, there are two rather methodically/technically-oriented contributions dealing with the optimized processing of UAV data and on the design and test of a multi-channel optical receiver for ground-based applications. All in all, this compilation documents that HSI is a multi-faceted research topic and will remain so in the future.
606   $aResearch & information: general$2bicssc
610   $ahyperspectral
610   $atopographic correction
610   $aatmospheric correction
610   $aradiometric correction
610   $along-range
610   $along-distance
610   $aStructure from Motion (SfM)
610   $aphotogrammetry
610   $amineral mapping
610   $aminimum wavelength mapping
610   $aMaarmorilik
610   $aRiotinto
610   $aHyperspectral image
610   $abio-optical algorithm
610   $aphycocyanin
610   $achlorophyll-a
610   $amangrove species classification
610   $aclose-range hyperspectral imaging
610   $afield hyperspectral measurement
610   $awaveband selection
610   $amachine learning
610   $ainstrument development
610   $aspectroradiometry
610   $atelescope
610   $areceiver
610   $asoil
610   $asoil salinity
610   $aunmanned aerial vehicle
610   $ahyperspectral imager
610   $arandom forest regression
610   $aelectromagnetic induction
610   $ahyperspectral imaging
610   $atree species
610   $amultiple classifier fusion
610   $aconvolutional neural network
610   $arandom forest
610   $arotation forest
610   $asea ice
610   $aice algae
610   $abiomass
610   $afine-scale
610   $aunder-ice
610   $aunderwater
610   $aantarctica
610   $astructure from motion
610   $ageorectification
610   $amosaicking
610   $apush-broom
610   $aUAV
610   $achlorophyll a
610   $acolored dissolved organic matter
610   $ain situ measurements
610   $avertical distribution
610   $awater column
610   $asnapshot hyperspectral imaging
615  7$aResearch & information: general
700   $aVohland$b Michael$4edt$01294154
702   $aJung$b Andra?s$4edt
702   $aVohland$b Michael$4oth
702   $aJung$b Andra?s$4oth
906   $aBOOK
912   $a9910557368003321
996   $aHyperspectral Imaging for Fine to Medium Scale Applications in Environmental Sciences$93022940
997   $aUNINA