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Hyperspectral Remote Sensing of Agriculture and Vegetation
| Hyperspectral Remote Sensing of Agriculture and Vegetation |
| Autore | Pascucci Simone |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (266 p.) |
| Soggetto topico |
Research & information: general
Environmental economics |
| Soggetto non controllato |
hyperspectral LiDAR
Red Edge AOTF vegetation parameters leaf chlorophyll content DLARI MDATT adaxial abaxial spectral reflectance peanut field spectroscopy hyperspectral heavy metals grapevine PLS SVM MLR multi-angle observation hyperspectral remote sensing BRDF vegetation classification object-oriented segmentation spectroscopy artificial intelligence proximal sensing data precision agriculture spectra vegetation plant classification discrimination feature selection waveband selection support vector machine random forest Natura 2000 invasive species expansive species biodiversity proximal sensor macronutrient micronutrient remote sensing hyperspectral imaging platforms and sensors analytical methods crop properties soil characteristics classification of agricultural features canopy spectra chlorophyll content continuous wavelet transform (CWT) correlation coefficient partial least square regression (PLSR) reproducibility replicability partial least squares Ethiopia Eragrostis tef hyperspectral remote sensing for soil and crops in agriculture hyperspectral imaging for vegetation plant traits high-resolution spectroscopy for agricultural soils and vegetation hyperspectral databases for agricultural soils and vegetation hyperspectral data as input for modelling soil, crop, and vegetation product validation new hyperspectral technologies future hyperspectral missions |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557691803321 |
Pascucci Simone
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Remote Sensing for Precision Nitrogen Management
| Remote Sensing for Precision Nitrogen Management |
| Autore | Miao Yuxin |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (602 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology Environmental science, engineering & technology |
| Soggetto non controllato |
UAS
multiple sensors vegetation index leaf nitrogen accumulation plant nitrogen accumulation pasture quality airborne hyperspectral imaging random forest regression sun-induced chlorophyll fluorescence (SIF) SIF yield indices upward downward leaf nitrogen concentration (LNC) wheat (Triticum aestivum L.) laser-induced fluorescence leaf nitrogen concentration back-propagation neural network principal component analysis fluorescence characteristics canopy nitrogen density radiative transfer model hyperspectral winter wheat flooded rice pig slurry aerial remote sensing vegetation indices N recommendation approach Mediterranean conditions nitrogen vertical distribution plant geometry remote sensing maize UAV multispectral imagery LNC non-parametric regression red-edge NDRE dynamic change model sigmoid curve grain yield prediction leaf chlorophyll content red-edge reflectance spectral index precision N fertilization chlorophyll meter NDVI NNI canopy reflectance sensing N mineralization farmyard manures Triticum aestivum discrete wavelet transform partial least squares hyper-spectra rice nitrogen management reflectance index multiple variable linear regression Lasso model Multiplex®3 sensor nitrogen balance index nitrogen nutrition index nitrogen status diagnosis precision nitrogen management terrestrial laser scanning spectrometer plant height biomass nitrogen concentration precision agriculture unmanned aerial vehicle (UAV) digital camera leaf chlorophyll concentration portable chlorophyll meter crop PROSPECT-D sensitivity analysis UAV multispectral imagery spectral vegetation indices machine learning plant nutrition canopy spectrum non-destructive nitrogen status diagnosis drone multispectral camera SPAD smartphone photography fixed-wing UAV remote sensing random forest canopy reflectance crop N status Capsicum annuum proximal optical sensors Dualex sensor leaf position proximal sensing cross-validation feature selection hyperparameter tuning image processing image segmentation nitrogen fertilizer recommendation supervised regression RapidSCAN sensor nitrogen recommendation algorithm in-season nitrogen management nitrogen use efficiency yield potential yield responsiveness standard normal variate (SNV) continuous wavelet transform (CWT) wavelet features optimization competitive adaptive reweighted sampling (CARS) partial least square (PLS) grapevine hyperparameter optimization multispectral imaging precision viticulture RGB multispectral coverage adjusted spectral index vegetation coverage random frog algorithm active canopy sensing integrated sensing system discrete NIR spectral band data soil total nitrogen concentration moisture absorption correction index particle size correction index coupled elimination |
| ISBN | 3-0365-5710-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910637794503321 |
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Miao Yuxin
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||