Land Surface Monitoring Based on Satellite Imagery
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| Autore: |
Venafra Sara
|
| Titolo: |
Land Surface Monitoring Based on Satellite Imagery
|
| Pubblicazione: | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica: | 1 electronic resource (232 p.) |
| Soggetto topico: | Research & information: general |
| Environmental economics | |
| Soggetto non controllato: | Sentinel-2 |
| spectral bands | |
| LAI | |
| vegetation indices | |
| Sentinel-1 | |
| SAR | |
| RVI | |
| incidence angle | |
| crop coefficient | |
| leaf area index | |
| urban heat island | |
| UHI regional impacts | |
| non-urban areas | |
| remote sensing | |
| thermal band | |
| UHI intensity | |
| remote sensing/GIS | |
| spatial dynamics | |
| landscape metrics | |
| urban–rural gradient | |
| urbanization | |
| automatic monitoring | |
| time series | |
| change detection | |
| urban planning | |
| hyperspectral | |
| cacti | |
| drone | |
| climate change | |
| drought | |
| water deficit index | |
| infrared observations | |
| satellite | |
| surface temperature | |
| air temperature | |
| humidity | |
| dew point temperature | |
| land subsidence | |
| DInSAR | |
| differential interferograms stacking | |
| floods | |
| coastal plain of Tabasco | |
| crop residue | |
| fusion | |
| machine learning algorithm | |
| reflective and radar bands | |
| land-cover change | |
| REDD+ | |
| Google Earth Engine | |
| random forest | |
| landsat | |
| Togo | |
| emissivity | |
| evapotranspiration | |
| heterogeneity | |
| Rao’s Q index | |
| spectral variation hypothesis | |
| thermal infrared | |
| Persona (resp. second.): | SerioCarmine |
| MasielloGuido | |
| VenafraSara | |
| Sommario/riassunto: | This book focuses attention on significant novel approaches developed to monitor land surface by exploiting satellite data in the infrared and visible ranges. Unlike in situ measurements, satellite data provide global coverage and higher temporal resolution, with very accurate retrievals of land parameters. This is fundamental in the study of climate change and global warming. The authors offer an overview of different methodologies to retrieve land surface parameters— evapotranspiration, emissivity contrast and water deficit indices, land subsidence, leaf area index, vegetation height, and crop coefficient—all of which play a significant role in the study of land cover, land use, monitoring of vegetation and soil water stress, as well as early warning and detection of forest fires and drought. |
| Titolo autorizzato: | Land Surface Monitoring Based on Satellite Imagery |
| ISBN: | 3-0365-5930-2 |
| Formato: | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9910639991903321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |