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Applications of Remote Sensing Data in Mapping of Forest Growing Stock and Biomass
| Applications of Remote Sensing Data in Mapping of Forest Growing Stock and Biomass |
| Autore | Aranha José |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (276 p.) |
| Soggetto topico |
Geography
Research and information: general |
| Soggetto non controllato |
above-ground biomass
aboveground biomass AGB estimation and mapping allometric equation ALOS DSM ALOS-2 L band SAR bark roughness bioenergy biomass density biomass estimation DBH diameter at breast height ecosystem services forest AGC estimation forest biomass estimation forest growing stock volume forest inventory data forest succession forest type GEOMON GIS individual tree detection landsat Landsat 8 OLI Landsat dataset leaf area index LiDAR machine learning machine learning algorithms mangroves map quality multiple ES interactions multisource remote sensing nondestructive method norway spruce ordinary kriging Pinus massoniana plantations plant area index random forest remote sensing seasonal images sentinel 2 Sentinel-1 C band SAR Sentinel-2 MSI Sentinel-2A shrubs biomass spatiotemporal evolution SPOT6 imagery stand volume stepwise regression subtropical forest subtropical forests support vector machine for regression synergy terrestrial laser scanning trade-off tree height UAV LiDAR urban vegetation valley basin variable selection vegetation indices WorldView-2 Xuzhou |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557474803321 |
Aranha José
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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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Remote Sensing of Leaf Area Index (LAI) and Other Vegetation Parameters / Hongliang Fang, Juanma Lopez Sanchez, Francisco Javier García-Haro
| Remote Sensing of Leaf Area Index (LAI) and Other Vegetation Parameters / Hongliang Fang, Juanma Lopez Sanchez, Francisco Javier García-Haro |
| Autore | Fang Hongliang |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (334 p.) |
| Soggetto non controllato |
artificial neural network
downscaling simulation 3D point cloud European beech consistency adaptive threshold evaluation photosynthesis geographic information system P-band PolInSAR validation density-based clustering structure from motion (SfM) EPIC Tanzania signal attenuation trunk canopy closure REDD+ unmanned aerial vehicle (UAV) forest recursive feature elimination Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) aboveground biomass random forest uncertainty household survey spectral information forests biomass root biomass biomass unmanned aerial vehicle Brazilian Amazon VIIRS global positioning system LAI photochemical reflectance index (PRI) allometric scaling and resource limitation R690/R630 modelling aboveground biomass leaf area index forest degradation spectral analyses terrestrial laser scanning BAAPA leaf area index (LAI) stem volume estimation tomographic profiles polarization coherence tomography (PCT) canopy gap fraction automated classification HemiView remote sensing multisource remote sensing Pléiades imagery photogrammetric point cloud farm types terrestrial LiDAR altitude RapidEye forest aboveground biomass recovery southern U.S. forests NDVI machine-learning conifer forest satellite chlorophyll fluorescence (ChlF) tree heights phenology point cloud local maxima clumping index MODIS digital aerial photograph Mediterranean hemispherical sky-oriented photo managed temperate coniferous forests fixed tree window size drought GLAS smartphone-based method forest above ground biomass (AGB) forest inventory over and understory cover sampling design |
| ISBN |
9783039212408
3039212400 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367563203321 |
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Fang Hongliang
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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