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The Future of Hyperspectral Imaging

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ISBN: 9783039218226 9783039218233 Year: Pages: 220 DOI: 10.3390/books978-3-03921-823-3 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Chemistry (General)
Added to DOAB on : 2019-12-09 16:39:37
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hyperspectral imaging --- Raman --- fluorescence --- sorting --- quality control --- black polymers --- PZT --- classification --- machine learning --- alternating direction method of multipliers --- Cramer–Rao lower bound --- forward observation model --- linear mixture model --- maximum likelihood --- multiband image fusion --- total variation --- fingerprints --- blood detection --- age determination --- hyperspectral imaging --- lossless compression --- multitemporal hyperspectral images --- information theoretic analysis --- predictive coding --- hyperspectral imaging --- plant phenotyping --- disease detection --- spectral tracking --- time series --- hyperspectral imaging --- principal component analysis --- oxygen saturation --- wound healing --- diabetic foot ulcer --- Raman spectroscopy --- chemical imaging --- compressive detection --- spatial light modulators (SLM) --- digital micromirror device (DMD) --- digital light processor (DLP) --- optimal binary filters --- Chemometrics --- multivariate data analysis --- compressive sensing --- hyperspectral imaging --- multiplexing system --- liquid crystal --- three-dimensional imaging --- integral imaging --- remote sensing --- point target detection --- CS-MUSI --- hyperspectral --- video --- imaging --- coastal dynamics --- moving vehicle imaging --- bi-directional reflectance distribution function (BRDF) --- hemispherical conical reflectance factor (HCRF) --- stereo imaging --- digital elevation model --- Virginia Coast Reserve Long Term Ecological Research (VCR LTER) --- Hyperspectral imaging --- painting samples --- retouching pigments --- watercolours --- multivariate analysis --- potatoes --- sprouting --- primordial leaf count --- hyperspectral imaging --- spectroscopy --- fusion --- wavelength selection --- PLSR --- interval partial least squares --- deep learning --- hyperspectral imaging --- neural networks --- machine learning --- image processing --- hyperspectral imaging --- medical imaging by HSI --- HSI for biology --- remote sensing --- hyperspectral microscopy --- fluorescence hyperspectral imaging --- Raman hyperspectral imaging --- infrared hyperspectral imaging --- statistical methods for HSI --- hyperspectral data mining and compression --- statistical methods for HSI --- hyperspectral data mining and compression

Remote Sensing Applications for Agriculture and Crop Modelling

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ISBN: 9783039282265 9783039282272 Year: Pages: 308 DOI: 10.3390/books978-3-03928-227-2 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Geography
Added to DOAB on : 2020-04-07 23:07:08
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Crop models and remote sensing techniques have been combined and applied in agriculture and crop estimation on local and regional scales, or worldwide, based on the simultaneous development of crop models and remote sensing. The literature shows that many new remote sensing sensors and valuable methods have been developed for the retrieval of canopy state variables and soil properties from remote sensing data for assimilating the retrieved variables into crop models. At the same time, remote sensing has been used in a staggering number of applications for agriculture. This book sets the context for remote sensing and modelling for agricultural systems as a mean to minimize the environmental impact, while increasing production and productivity. The eighteen papers published in this Special Issue, although not representative of all the work carried out in the field of Remote Sensing for agriculture and crop modeling,

Keywords

crop residue management --- remote sensing --- satellite images --- hyperspectral sensor --- vegetation index --- yield monitoring --- remote sensing --- proximal sensing --- crop modeling --- soil --- plant --- management zone --- spatial variability --- temporal variability --- precision agriculture --- Á Trous algorithm --- conservation agriculture --- crop inventory --- remote sensing --- spectral-weight variations in fused images --- soil stoichiometry --- land use change --- soil organic carbon --- nitrogen --- Tarim Basin --- SPAD --- leaf nitrogen concentration --- nitrogen nutrition index --- grain yield --- dynamic model --- wheat --- disease --- yield --- septoria tritici blotch --- leaf area index --- crop modelling --- decision support system for agrotechnology transfer (DSSAT) --- Cropsim-CERES Wheat --- sorghum biomass --- prediction modeling --- machine learning --- fAPAR --- Sentinel-2 satellite imagery --- big data technology --- remote sensing --- UAV --- vegetation indices --- relative frequencies --- yield --- precision agriculture --- cultivars --- crop growth model --- data assimilation --- Leaf Area Index --- Sentinel-2 --- EPIC model --- yield estimation --- NDVI --- remote sensing --- GIS --- precision farming --- variable rate technology --- yield mapping --- protein content --- wheat --- canopy temperature depression --- NDVI --- RGB images --- grain yield --- ?13C --- UAV chemical application --- droplet drift --- flat-fan atomizer --- simulation analysis --- control variables --- agricultural land-cover --- multi-spectral --- generalized model --- machine learning --- crop type mapping --- Integrated Administration and Control System --- remote sensing --- hydroponic --- vegetable monitoring --- crop production --- spectral simulation --- hyperspectral data --- n/a --- fractional cover --- irrigation --- satellite --- crop simulation model --- AquaCrop --- yield mapping --- remote sensing --- durum wheat --- precision agriculture --- large cardamom --- remote sensing --- species modelling --- habitat assessment --- climate change

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