Forestry Applications of Unmanned Aerial Vehicles (UAVs) 2019
| Forestry Applications of Unmanned Aerial Vehicles (UAVs) 2019 |
| Autore | Matese Alessandro |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 online resource (184 p.) |
| Soggetto topico |
Biology, life sciences
Forestry & related industries Research & information: general |
| Soggetto non controllato |
Accuracy Assessment
ancient trees measurement biomass evaluation burn severity Castanea sativa central Oregon classification convolutional neural network convolutional neural network (CNN) ecohydrology end-to-end learning establishment survey forest fire forest inventory forest modeling forest regeneration Forest Sampling forestry applications hyperspectral imagery image processing juniper woodlands leaf-off leaf-on machine learning Mauritia flexuosa multispectral classification multispectral image object-based image analysis (OBIA) photogrammetric point clouds Photogrammetry precision agriculture precision forestry rangelands Reference Data reforestation remote sensing Remote Sensing reproduction RGB imagery Robinia pseudoacacia L. seedling detection seedling stand inventorying semantic segmentation short rotation coppice spreading structure from motion (SfM) Thematic Mapping tree age prediction UAV UAV photogrammetry unmanned aerial system (UAS) unmanned aerial systems Unmanned Aerial Systems (UAS) unmanned aerial vehicles unmanned aerial vehicles (UAV) Unmanned Aerial Vehicles (UAV) |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Forestry Applications of Unmanned Aerial Vehicles |
| Record Nr. | UNINA-9910557112103321 |
Matese Alessandro
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Lo trovi qui: Univ. Federico II | ||
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UAVs for Vegetation Monitoring
| UAVs for Vegetation Monitoring |
| Autore | de Castro Megías Ana |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (452 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
Acacia
agro-environmental measures artificial intelligence artificial neural network banana broad-sense heritability canopy cover canopy height century-old biochar chlorophyll content CIELab classification close remote sensing CNN container-grown contextual spatial domain/resolution convolution neural network cotton root rot crop canopy crop disease crop mapping crop monitoring curve fitting data aggregation deep learning detection performance disease detection disease diagnosis disease monitoring drone drought tolerance eddy covariance (EC) evapotranspiration (ET) Faster RCNN flight altitude forage grass forest Fusarium wilt Glycine max GRAPEX growth model high throughput field phenotyping HSV hyperspectral image analysis image segmentation Inception v2 individual plant segmentation Indonesia inference time land cover least squares support vector machine machine learning maize tassel method comparison MobileNet v2 multiple linear regression multiscale textures multispectral multispectral image multispectral imagery multispectral remote sensing NDVI neural network nitrogen stress nutrient deficiency oil palm olive groves operating parameters ornamental patch-based CNN phenotyping gap plant detection plant nitrogen estimation plant segmentation plant trails plant-by-plant plant-level precision agriculture purple rapeseed leaves random forest red-edge spectra remote sensing remote sensing technique RGB RGB camera RGB imagery semantic segmentation single-plant solar zenith angle southern Spain spatial resolution SSD sUAS support vector machine tassel branch number texture thermal thermal camera time of day transfer learning transpiration tropics Two Source Energy Balance model (TSEB) U-Net UAS UAV UAV digital images UAV hyperspectral UAV remote sensing unmanned aerial vehicle variable importance vegetation cover vegetation ground cover vegetation index vegetation indices VGG16 visual recognition water stress weed detection wheat yellow rust winter wheat biomass |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557661103321 |
de Castro Megías Ana
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Lo trovi qui: Univ. Federico II | ||
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