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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 electronic resource (184 p.) |
| Soggetto topico |
Research & information: general
Biology, life sciences Forestry & related industries |
| Soggetto non controllato |
unmanned aerial vehicles
seedling detection forest regeneration reforestation establishment survey machine learning multispectral classification UAV photogrammetry forest modeling ancient trees measurement tree age prediction Mauritia flexuosa semantic segmentation end-to-end learning convolutional neural network forest inventory Unmanned Aerial Systems (UAS) structure from motion (SfM) Unmanned Aerial Vehicles (UAV) Photogrammetry Thematic Mapping Accuracy Assessment Reference Data Forest Sampling Remote Sensing Robinia pseudoacacia L. reproduction spreading short rotation coppice unmanned aerial system (UAS) object-based image analysis (OBIA) convolutional neural network (CNN) juniper woodlands ecohydrology remote sensing unmanned aerial systems central Oregon rangelands seedling stand inventorying photogrammetric point clouds hyperspectral imagery leaf-off leaf-on UAV multispectral image forest fire burn severity classification precision agriculture biomass evaluation image processing Castanea sativa unmanned aerial vehicles (UAV) precision forestry forestry applications RGB imagery |
| 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 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Operationalization of Remote Sensing Solutions for Sustainable Forest Management
| Operationalization of Remote Sensing Solutions for Sustainable Forest Management |
| Autore | Mozgeris Gintautas |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (296 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
forest road inventory
total station global navigation satellite system point cloud precision density positional accuracy efficiency mangrove sustainability deforestation depletion anthropogenic natural water balance Southeast Asia Phoracantha spp unmanned aerial vehicle (UAV) multispectral imagery vegetation index thresholding analysis Large Scale Mean-Shift Segmentation (LSMS) Random Forest (RF) forest mask validation probability sampling remote sensing earth observations forestry accuracy assessment forest classification forested catchment hydrological modeling SWAT model DEM airborne laser scanning deep learning Landsat national forest inventory stand volume bark beetle Ips typographus L. pest change detection forest damage spruce Sentinel-2 damage mapping multi-temporal regression mangrove replanting restoration analytic hierarchy process UAV DJI drone machine learning forest canopy canopy gaps canopy openings percentage satellite indices Elastic Net beech-fir forests pixel-based supervised classification random forest support vector machine gray level cooccurrence matrix (GLCM) principal component analysis (PCA) WorldView-3 wildfires MaxENT risk modeling GIS multi-scale analysis Yakutia Artic Siberia phenology modelling forest disturbance forest monitoring bark beetle infestation forest management time series analysis satellite imagery landsat time series growing stock volume forest inventory harmonic regression |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557584103321 |
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Mozgeris Gintautas
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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 of Leaf Area Index (LAI) and Other Vegetation Parameters
| Remote Sensing of Leaf Area Index (LAI) and Other Vegetation Parameters |
| Autore | Sanchez Juanma Lopez |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (334 p.) |
| Soggetto non controllato |
artificial neural network
downscaling simulation 3D point cloud European beech consistency adaptive threshold evaluation photosynthesis geographic information system P-band PolInSAR validation density-based clustering structure from motion (SfM) EPIC Tanzania signal attenuation trunk canopy closure REDD+ unmanned aerial vehicle (UAV) forest recursive feature elimination Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) aboveground biomass random forest uncertainty household survey spectral information forests biomass root biomass biomass unmanned aerial vehicle Brazilian Amazon VIIRS global positioning system LAI photochemical reflectance index (PRI) allometric scaling and resource limitation R690/R630 modelling aboveground biomass leaf area index forest degradation spectral analyses terrestrial laser scanning BAAPA leaf area index (LAI) stem volume estimation tomographic profiles polarization coherence tomography (PCT) canopy gap fraction automated classification HemiView remote sensing multisource remote sensing Pléiades imagery photogrammetric point cloud farm types terrestrial LiDAR altitude RapidEye forest aboveground biomass recovery southern U.S. forests NDVI machine-learning conifer forest satellite chlorophyll fluorescence (ChlF) tree heights phenology point cloud local maxima clumping index MODIS digital aerial photograph Mediterranean hemispherical sky-oriented photo managed temperate coniferous forests fixed tree window size drought GLAS smartphone-based method forest above ground biomass (AGB) forest inventory over and understory cover sampling design |
| ISBN | 3-03921-240-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Remote Sensing of Leaf Area Index |
| Record Nr. | UNINA-9910367563203321 |
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Sanchez Juanma Lopez
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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