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Electronics, Close-Range Sensors and Artificial Intelligence in Forestry
| Electronics, Close-Range Sensors and Artificial Intelligence in Forestry |
| Autore | Borz Stelian Alexandru |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (248 p.) |
| Soggetto topico |
Research & information: general
Biology, life sciences Forestry & related industries |
| Soggetto non controllato |
forest fire detection
deep learning ensemble learning Yolov5 EfficientDet EfficientNet big data automation artificial intelligence multi-modality acceleration classification events performance motor-manual felling willow Romania region detection of forest fire grading of forest fire weakly supervised loss fine segmentation region-refining segmentation lightweight Faster R-CNN ultrasound sensors road scanner terrestrial laser scanning TLS forest road maintenance forest road monitoring crowned road surface digital twinning climate smart LiDAR digitalization forest loss land-cover change machine learning spatial heterogeneity random forest model geographically weighted regression aboveground biomass estimation remote sensing Sentinel-2 Iran multiple regression artificial neural network k-nearest neighbor random forest canopy drone leaf leaves foliar samples sampling Aerial robotics UAS UAV IoT forest ecology accessibility wood diameter length close-range sensing Augmented Reality comparison accuracy effectiveness potential forestry 4.0 wood technology sawmilling productivity prediction long-term tree ring forestry detection resistance sensor micro-drilling resistance method signal processing Signal-to-Noise Ratio (SNR) |
| ISBN | 3-0365-6171-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910639985003321 |
Borz Stelian Alexandru
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Soil-Water Conservation, Erosion, and Landslide
| Soil-Water Conservation, Erosion, and Landslide |
| Autore | Chen Su-Chin |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (392 p.) |
| Soggetto topico |
Technology: general issues
Environmental science, engineering & technology |
| Soggetto non controllato |
landslide
image classification spectrum similarity analysis extreme rainfall-induced landslide susceptibility model landslide ratio-based logistic regression landslide evolution Typhoon Morakot Taiwan vegetation community vegetation importance value root system soil erosion grey correlation analysis sediment yield RUSLE Lancang-Mekong River basin rainfall threshold landslide probability model debris flow Zechawa Gully mitigation countermeasures Jiuzhaigou Valley water erosion susceptibility Gaussian process climate change radial basis function kernel weighted subspace random forest extreme events extreme weather naive Bayes feature selection machine learning hydrologic model simulated annealing earth system science PSED Model loess ICU static liquefaction mechanical behavior pore structure alpine swamp meadow alpine meadow degradation of riparian vegetation root distribution tensile strength tensile crack soil management land cover changes Syria hillslopes gully erosion vegetation restoration soil erodibility land use bridge pier overfall scour landform change impact on pier shallow water equations wet-dry front outburst flood TVD-scheme MUSCL-Hancock method laboratory model test extreme rainfall rill erosion shallow landslides deep lip surface safety factor rainfall erosivity factor USLE R Deep Neural Network tree ring dendrogeomorphology landslide activity deciduous broadleaved tree Shirakami Mountains spatiotemporal cluster analysis landslide hotspots dam breach seepage overtopping seismic signal flume test breach model |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910566467403321 |
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Chen Su-Chin
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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