Remote Sensing in Agriculture: State-of-the-Art

• Autore: Borgogno-Mondino Enrico
• Pubblicazione: Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
• Descrizione fisica: 1 online resource (220 p.)
• Soggetto topico: Environmental science, engineering and technology; History of engineering and technology; Technology: general issues
• Soggetto non controllato: alpha angle; anisotropy; apple orchard damage; biomass; CDL; corn; crop height; crop management; crop Monitoring; crop water stress monitoring; crop yield prediction; cross-scale; data blending; digital number (DN); DJI Phantom 4 Multispectral (P4M); economic loss; entropy; feature selection; field phenotyping; gap-filling; Hidden Markov Random Field; HMRF; hyperspectral imaging; insurance support; Landsat; lodging; MODIS; northern Mongolia; oasis crop type mapping; Parrot Sequoia (Sequoia); plant disease detection; polarimetric decomposition; precision agriculture (PA); random forest (RF); recursive feature increment (RFI); red-edge spectral bands and indices; reflectance; remote sensing (RS); remote sensing indices; SAR; Sentinel-1; Sentinel-1 and 2 integration; soil moisture Karnataka India; soil moisture semi-empirical model; soybean; spatial resolution; spectral angle mapper; spring wheat; statistically homogeneous pixels (SHPs); storm damage mapping; support vector machine; support vector regression; Synthetic Aperture Radar; synthetic aperture radar (SAR); thermal infrared (TIR); thermal UAV RS; UAV; UAV-based LiDAR; unmanned aerial vehicles (UAVs); vegetation index (VI); vegetation status monitoring; volumetric soil moisture; winter wheat; yellow rust; yield estimation
• Persona (resp. second.): TarantinoEufemia; CapolupoAlessandra; Borgogno-MondinoEnrico
• Sommario/riassunto: The Special Issue on "Remote Sensing in Agriculture: State-of-the-Art" gives an exhaustive overview of the ongoing remote sensing technology transfer into the agricultural sector. It consists of 10 high-quality papers focusing on a wide range of remote sensing models and techniques to forecast crop production and yield, to map agricultural landscape and to evaluate plant and soil biophysical features. Satellite, RPAS, and SAR data were involved. This preface describes shortly each contribution published in such Special Issue.
• Altri titoli varianti: Remote Sensing in Agriculture
• Titolo autorizzato: Remote Sensing in Agriculture: State-of-the-Art
• ISBN: 3-0365-5484-X
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910637779903321
• Lo trovi qui: Univ. Federico II