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Mapping Tree Species Diversity
| Mapping Tree Species Diversity |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2023 |
| Descrizione fisica | 1 online resource (414 p.) |
| Soggetto topico |
Geography
Research & information: general |
| Soggetto non controllato |
accuracy
aerial imagery ALS AVIRIS-NG biodiversity biosecurity boreal forest BPWW classification climatic gradient CNN convex hull volume convolutional networks convolutional neural network cross-validation curve matching data fusion dead wood deep learning endangered tree species feature extraction forest forest cover and species forest inventory forest pathology forest species forest stands classification forest structure analysis forestry GEE high-resolution remote sensing imagery hyperspectral multitemporal information illumination correction imbalanced data individual tree crown delineation individual tree species recognition ISRO-NASA campaign Landsat LiDAR machine learning machine learning algorithm mapping Mount Taishan multi-layer perception multi-temporal multisource remote sensing data multitemporal myrtle rust object-based optical data phenological metrics pixel-based classification probability random forest radiative transfer model random forest RGB SAR savanna scale effect segmentation selective logging semideciduous forest Sentinel-1 Sentinel-2 Serbia Siberia single trees spatial autocorrelation spatial divergence species distribution model species diversity spectral diversity time series tree species tree species classification tree species mapping trees species identification tropical forests UAV up-scaling urban forestry Wienerwald biosphere reserve woody vegetation WorldView-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9911053076503321 |
| MDPI - Multidisciplinary Digital Publishing Institute, 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Remote Sensing of the Aquatic Environments
| Remote Sensing of the Aquatic Environments |
| Autore | Carolis Giacomo De |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (292 p.) |
| Soggetto topico |
Geography
Research & information: general |
| Soggetto non controllato |
algal bloom
altimetry data ammonia detection aquaculture aquaculture ponds Arctic CDOM absorbance Chaohu Lake chlorophyll chlorophyll-a convolutional neural network coral reefs Cryosat-2 deep learning DOC Doppler Centroid Anomaly drone applications drought ecohydrology ecological status class of lakes empirical models estuarial and coastal areas European Union Water Framework Directive (2000/60/EC) extraction French Alps geostationary satellite groundwater HAB hydrodynamic model hydrodynamics inland lake inland waters lake level Lake Tana Landsat linear spectral unmixing MODIS mountain temporary pools multi-source remote sensing multiple regression multitemporal NDVI ocean color optical data optical fiber coating optical remote sensing optical sensing Pacific lagoons Paldang Reservoir photogrammetry physical limnology Planetscope polymer optical fibers Rana temporaria remote sensing SAR satellite sediment self-attention sensors sentinel Sentinel-2 Sentinel-3 shallow lakes shelf seas spectroscopic indices surface water synergy thermal infrared turbid water turbidity Ulva water hyacinth water level water quality parameters waterbody temperature |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557720403321 |
Carolis Giacomo De
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||