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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 online resource (392 p.) |
| Soggetto topico |
Environmental science, engineering and technology
Technology: general issues |
| Soggetto non controllato |
alpine meadow
alpine swamp meadow breach model bridge pier climate change dam breach debris flow deciduous broadleaved tree deep lip surface Deep Neural Network degradation of riparian vegetation dendrogeomorphology earth system science extreme events extreme rainfall extreme rainfall-induced landslide susceptibility model extreme weather feature selection flume test Gaussian process grey correlation analysis gully erosion hillslopes hydrologic model ICU image classification Jiuzhaigou Valley laboratory model test Lancang-Mekong River basin land cover changes land use landform change impact on pier landslide landslide activity landslide evolution landslide hotspots landslide probability model landslide ratio-based logistic regression loess machine learning mechanical behavior mitigation countermeasures MUSCL-Hancock method n/a naive Bayes outburst flood overfall overtopping pore structure PSED Model radial basis function kernel rainfall erosivity factor rainfall threshold rill erosion root distribution root system RUSLE safety factor scour sediment yield seepage seismic signal shallow landslides shallow water equations Shirakami Mountains simulated annealing soil erodibility soil erosion soil management spatiotemporal cluster analysis spectrum similarity analysis static liquefaction susceptibility Syria Taiwan tensile crack tensile strength tree ring TVD-scheme Typhoon Morakot USLE R vegetation community vegetation importance value vegetation restoration water erosion weighted subspace random forest wet-dry front Zechawa Gully |
| 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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