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Applications of Remote Image Capture System in Agriculture
| Applications of Remote Image Capture System in Agriculture |
| Autore | Molina Martínez José Miguel |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (310 p.) |
| Soggetto topico | History of engineering & technology |
| Soggetto non controllato |
SVM
budding rate UAV geometric consistency radiometric consistency point clouds ICP reflectance maps vegetation indices Parrot Sequoia artificial intelligence precision agriculture agricultural robot optimization algorithm online operation segmentation coffee leaf rust machine learning deep learning remote sensing Fourth Industrial Revolution Agriculture 4.0 failure strain sandstone digital image correlation Hill-Tsai failure criterion finite element method reference evapotranspiration moisture sensors machine learning regression frequency-domain reflectometry randomizable filtered classifier convolutional neural network U-Net land use banana plantation Panama TR4 aerial photography remote images systematic mapping study agriculture applications total leaf area mixed pixels Cabernet Sauvignon NDVI Normalized Difference Vegetation Index precision viticulture 3D model spatial vision fertirrigation teaching-learning spectrometry Sentinel-2 pasture quality index normalized difference vegetation index normalized difference water index supplementation decision making digital agriculture grape yield estimate berries counting Dilated CNN machine learning algorithms classification performance winter wheat mapping large-scale water stress Prunus avium L. stem water potential low-cost thermography thermal indexes canopy temperature non-water-stressed baselines non-transpiration baseline soil moisture andosols image processing greenhouse automatic tomato harvesting |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557895803321 |
Molina Martínez José Miguel
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Drones for Biodiversity Conservation and Ecological Monitoring
| Drones for Biodiversity Conservation and Ecological Monitoring |
| Autore | Mücher C.A |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (176 p.) |
| Soggetto non controllato |
Pinus nigra
unmanned aerial vehicles (UAVs) biological conservation precision flight altitude accuracy multiscale approach low-cost UAV LTER small UAV ecological monitoring Sequoia long-term monitoring albedo image processing vegetation indices Tanzania ground-truth Sentinel-2 biodiversity threats field experiments effective management great apes drone ecological integrity multispectral rice crops conservation protected areas survey response surface aerial survey bird censuses multispectral mapping drones UAS hyperspectral UAV random forest Pinus sylvestris NDVI UAVs Parrot Sequoia supervised classification drone mapping RPAS greenness index image resolution Plegadis falcinellus Motus biodiversity Landsat 8 Sentinel boreal forest phenology LTSER western swamphen Parrot SEQUOIA native grassland forêt Montmorency drought forest regeneration radio-tracking |
| ISBN | 3-03921-981-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367736803321 |
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Mücher C.A
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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