Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Hyperspectral Imaging for Fine to Medium Scale Applications in Environmental Sciences
| Hyperspectral Imaging for Fine to Medium Scale Applications in Environmental Sciences |
| Autore | Vohland Michael |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (218 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
hyperspectral
topographic correction atmospheric correction radiometric correction long-range long-distance Structure from Motion (SfM) photogrammetry mineral mapping minimum wavelength mapping Maarmorilik Riotinto Hyperspectral image bio-optical algorithm phycocyanin chlorophyll-a mangrove species classification close-range hyperspectral imaging field hyperspectral measurement waveband selection machine learning instrument development spectroradiometry telescope receiver soil soil salinity unmanned aerial vehicle hyperspectral imager random forest regression electromagnetic induction hyperspectral imaging tree species multiple classifier fusion convolutional neural network random forest rotation forest sea ice ice algae biomass fine-scale under-ice underwater antarctica structure from motion georectification mosaicking push-broom UAV chlorophyll a colored dissolved organic matter in situ measurements vertical distribution water column snapshot hyperspectral imaging |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557368003321 |
Vohland Michael
|
||
| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Hyperspectral Remote Sensing of Agriculture and Vegetation
| Hyperspectral Remote Sensing of Agriculture and Vegetation |
| Autore | Pascucci Simone |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (266 p.) |
| Soggetto topico |
Research & information: general
Environmental economics |
| Soggetto non controllato |
hyperspectral LiDAR
Red Edge AOTF vegetation parameters leaf chlorophyll content DLARI MDATT adaxial abaxial spectral reflectance peanut field spectroscopy hyperspectral heavy metals grapevine PLS SVM MLR multi-angle observation hyperspectral remote sensing BRDF vegetation classification object-oriented segmentation spectroscopy artificial intelligence proximal sensing data precision agriculture spectra vegetation plant classification discrimination feature selection waveband selection support vector machine random forest Natura 2000 invasive species expansive species biodiversity proximal sensor macronutrient micronutrient remote sensing hyperspectral imaging platforms and sensors analytical methods crop properties soil characteristics classification of agricultural features canopy spectra chlorophyll content continuous wavelet transform (CWT) correlation coefficient partial least square regression (PLSR) reproducibility replicability partial least squares Ethiopia Eragrostis tef hyperspectral remote sensing for soil and crops in agriculture hyperspectral imaging for vegetation plant traits high-resolution spectroscopy for agricultural soils and vegetation hyperspectral databases for agricultural soils and vegetation hyperspectral data as input for modelling soil, crop, and vegetation product validation new hyperspectral technologies future hyperspectral missions |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557691803321 |
|
Pascucci Simone
|
||
| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||