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UAVs for Vegetation Monitoring
| UAVs for Vegetation Monitoring |
| Autore | de Castro Megías Ana |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (452 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
UAS
UAV vegetation cover multispectral land cover forest Acacia Indonesia tropics vegetation ground cover vegetation indices agro-environmental measures olive groves southern Spain sUAS water stress ornamental container-grown artificial intelligence machine learning deep learning neural network visual recognition precision agriculture canopy cover image analysis crop mapping evapotranspiration (ET) GRAPEX remote sensing Two Source Energy Balance model (TSEB) contextual spatial domain/resolution data aggregation eddy covariance (EC) Fusarium wilt crop disease banana multispectral remote sensing purple rapeseed leaves unmanned aerial vehicle U-Net plant segmentation nitrogen stress Glycine max RGB canopy height close remote sensing growth model curve fitting NDVI solar zenith angle flight altitude time of day operating parameters CNN Faster RCNN SSD Inception v2 patch-based CNN MobileNet v2 detection performance inference time disease detection cotton root rot plant-level single-plant plant-by-plant classification UAV remote sensing crop monitoring RGB imagery multispectral imagery century-old biochar semantic segmentation random forest crop canopy multispectral image chlorophyll content remote sensing technique individual plant segmentation plant detection transfer learning maize tassel tassel branch number convolution neural network VGG16 plant nitrogen estimation vegetation index image segmentation transpiration method comparison oil palm multiple linear regression support vector machine artificial neural network UAV hyperspectral wheat yellow rust disease monitoring texture spatial resolution RGB camera thermal camera drought tolerance forage grass HSV CIELab broad-sense heritability phenotyping gap high throughput field phenotyping UAV digital images winter wheat biomass multiscale textures red-edge spectra least squares support vector machine variable importance drone hyperspectral thermal nutrient deficiency weed detection disease diagnosis plant trails |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557661103321 |
de Castro Megías Ana
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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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Using Remote Sensing Techniques to Improve Hydrological Predictions in a Rapidly Changing World
| Using Remote Sensing Techniques to Improve Hydrological Predictions in a Rapidly Changing World |
| Autore | Zhang Yongqiang |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (216 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
rainfall monitoring
remote sensing rain rate estimation 5G millimeter-wave E-band LOS-MIMO UAV remote sensing Ephemeral rivers flood peak discharge incipient motion arid ungauged regions flash flood Integrated Multi-Satellite Retrievals for Global Precipitation Measurement Rainfall Triggering Index Yunnan ecological water transfer wetland vegetation ecosystem surface and groundwater interaction northwestern China WRF-3DVar data assimilation coupled atmospheric-hydrologic system rainfall-runoff prediction lumped Hebei model grid-based Hebei model WRF-Hydro modeling system evapotranspiration model SWAT calibration regression Sierra Nevada flux tower water limitation vapor pressure deficit double-mass analysis coefficient of variability seasonal ARIMA MK-S trend analysis evaporation LAI NDVI urban ecosystem sponge city PML-V2 Penman–Monteith equation Sentinel-2 assimilation frequency data assimilation WRF-3DAVR radar reflectivity rainfall forecast urban flood design rainfall ungauged drainage basin RainyDay IDF formula hydrological prediction climate change land use change |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557426703321 |
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Zhang Yongqiang
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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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