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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 online resource (266 p.) |
| Soggetto topico |
Environmental economics
Research & information: general |
| Soggetto non controllato |
abaxial
adaxial analytical methods AOTF artificial intelligence biodiversity BRDF canopy spectra chlorophyll content classification classification of agricultural features continuous wavelet transform (CWT) correlation coefficient crop properties discrimination DLARI Eragrostis tef Ethiopia expansive species feature selection field spectroscopy future hyperspectral missions grapevine heavy metals high-resolution spectroscopy for agricultural soils and vegetation hyperspectral hyperspectral data as input for modelling soil, crop, and vegetation hyperspectral databases for agricultural soils and vegetation hyperspectral imaging hyperspectral imaging for vegetation hyperspectral LiDAR hyperspectral remote sensing hyperspectral remote sensing for soil and crops in agriculture invasive species leaf chlorophyll content macronutrient MDATT micronutrient MLR multi-angle observation Natura 2000 new hyperspectral technologies object-oriented segmentation partial least square regression (PLSR) partial least squares peanut plant plant traits platforms and sensors PLS precision agriculture product validation proximal sensing data proximal sensor random forest Red Edge remote sensing replicability reproducibility soil characteristics spectra spectral reflectance spectroscopy support vector machine SVM vegetation vegetation classification vegetation parameters waveband selection |
| 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 | ||
| ||