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Advances in Quantitative Remote Sensing in China - In Memory of Prof. Xiaowen Li . Volume 1
| Advances in Quantitative Remote Sensing in China - In Memory of Prof. Xiaowen Li . Volume 1 |
| Autore | Shi Jiancheng |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (404 p.) |
| Soggetto non controllato |
gross primary production (GPP)
interference filter Visible Infrared Imaging Radiometer Suite (VIIRS) cost-efficient precipitation topographic effects land surface temperature Land surface emissivity scale effects spatial-temporal variations statistics methods inter-annual variation spatial representativeness FY-3C/MERSI sunphotometer PROSPECT passive microwave flux measurements urban scale vegetation dust-retention multiple ecological factors leaf age standard error of the mean LUT method spectra SURFRAD Land surface temperature aboveground biomass uncertainty land surface variables copper Northeast China forest disturbance end of growing season (EOS) random forest model probability density function downward shortwave radiation machine learning MODIS products composite slope daily average value canopy reflectance spatiotemporal representative light use efficiency hybrid method disturbance index quantitative remote sensing inversion SCOPE GPP South China's anisotropic reflectance vertical structure snow cover land cover change start of growing season (SOS) MS-PT algorithm aerosol pixel unmixing HiWATER algorithmic assessment surface radiation budget latitudinal pattern ICESat GLAS vegetation phenology SIF metric comparison Antarctica spatial heterogeneity comprehensive field experiment reflectance model sinusoidal method NDVI BRDF cloud fraction NPP VPM China dense forest vegetation remote sensing Cunninghamia high resolution geometric-optical model phenology LiDAR ZY-3 MUX point cloud multi-scale validation Fraunhofer Line Discrimination (FLD) rice fractional vegetation cover (FVC) interpolation high-resolution freeze/thaw drought Synthetic Aperture Radar (SAR) controlling factors sampling design downscaling Chinese fir MRT-based model RADARSAT-2 northern China leaf area density potential evapotranspiration black-sky albedo (BSA) decision tree CMA fluorescence quantum efficiency in dark-adapted conditions (FQE) surface solar irradiance validation geographical detector model vertical vegetation stratification spatiotemporal distribution and variation gap fraction phenological parameters spatio-temporal albedometer variability GLASS gross primary productivity (GPP) EVI2 machine learning algorithms latent heat GLASS LAI time series boreal forest leaf maize heterogeneity temperature profiles crop-growing regions satellite observations rugged terrain species richness voxel LAI TMI data GF-1 WFV spectral HJ-1 CCD leaf area index evapotranspiration land-surface temperature products (LSTs) SPI AVHRR Tibetan Plateau snow-free albedo PROSPECT-5B+SAILH (PROSAIL) model MCD43A3 C6 3D reconstruction photoelectric detector multi-data set BEPS aerosol retrieval plant functional type multisource data fusion remote sensing leaf spectral properties solo slope land surface albedo longwave upwelling radiation (LWUP) terrestrial LiDAR AMSR2 geometric optical radiative transfer (GORT) model MuSyQ-GPP algorithm tree canopy FY-3C/MWRI meteorological factors solar-induced chlorophyll fluorescence metric integration observations polar orbiting satellite arid/semiarid homogeneous and pure pixel filter thermal radiation directionality biodiversity gradient boosting regression tree forest canopy height Landsat subpixel information MODIS humidity profiles NIR geostationary satellite |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910346664203321 |
Shi Jiancheng
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||
| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Quantitative Remote Sensing in China - In Memory of Prof. Xiaowen Li
| Advances in Quantitative Remote Sensing in China - In Memory of Prof. Xiaowen Li |
| Autore | Shi Jiancheng |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (404 p.) |
| Soggetto non controllato |
gross primary production (GPP)
interference filter Visible Infrared Imaging Radiometer Suite (VIIRS) cost-efficient precipitation topographic effects land surface temperature Land surface emissivity scale effects spatial-temporal variations statistics methods inter-annual variation spatial representativeness FY-3C/MERSI sunphotometer PROSPECT passive microwave flux measurements urban scale vegetation dust-retention multiple ecological factors leaf age standard error of the mean LUT method spectra SURFRAD Land surface temperature aboveground biomass uncertainty land surface variables copper Northeast China forest disturbance end of growing season (EOS) random forest model probability density function downward shortwave radiation machine learning MODIS products composite slope daily average value canopy reflectance spatiotemporal representative light use efficiency hybrid method disturbance index quantitative remote sensing inversion SCOPE GPP South China's anisotropic reflectance vertical structure snow cover land cover change start of growing season (SOS) MS-PT algorithm aerosol pixel unmixing HiWATER algorithmic assessment surface radiation budget latitudinal pattern ICESat GLAS vegetation phenology SIF metric comparison Antarctica spatial heterogeneity comprehensive field experiment reflectance model sinusoidal method NDVI BRDF cloud fraction NPP VPM China dense forest vegetation remote sensing Cunninghamia high resolution geometric-optical model phenology LiDAR ZY-3 MUX point cloud multi-scale validation Fraunhofer Line Discrimination (FLD) rice fractional vegetation cover (FVC) interpolation high-resolution freeze/thaw drought Synthetic Aperture Radar (SAR) controlling factors sampling design downscaling Chinese fir MRT-based model RADARSAT-2 northern China leaf area density potential evapotranspiration black-sky albedo (BSA) decision tree CMA fluorescence quantum efficiency in dark-adapted conditions (FQE) surface solar irradiance validation geographical detector model vertical vegetation stratification spatiotemporal distribution and variation gap fraction phenological parameters spatio-temporal albedometer variability GLASS gross primary productivity (GPP) EVI2 machine learning algorithms latent heat GLASS LAI time series boreal forest leaf maize heterogeneity temperature profiles crop-growing regions satellite observations rugged terrain species richness voxel LAI TMI data GF-1 WFV spectral HJ-1 CCD leaf area index evapotranspiration land-surface temperature products (LSTs) SPI AVHRR Tibetan Plateau snow-free albedo PROSPECT-5B+SAILH (PROSAIL) model MCD43A3 C6 3D reconstruction photoelectric detector multi-data set BEPS aerosol retrieval plant functional type multisource data fusion remote sensing leaf spectral properties solo slope land surface albedo longwave upwelling radiation (LWUP) terrestrial LiDAR AMSR2 geometric optical radiative transfer (GORT) model MuSyQ-GPP algorithm tree canopy FY-3C/MWRI meteorological factors solar-induced chlorophyll fluorescence metric integration observations polar orbiting satellite arid/semiarid homogeneous and pure pixel filter thermal radiation directionality biodiversity gradient boosting regression tree forest canopy height Landsat subpixel information MODIS humidity profiles NIR geostationary satellite |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910346664103321 |
|
Shi Jiancheng
|
||
| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
ALOS-2/PALSAR-2 Calibration, Validation, Science and Applications
| ALOS-2/PALSAR-2 Calibration, Validation, Science and Applications |
| Autore | Tadono Takeo |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (240 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology Environmental science, engineering & technology |
| Soggetto non controllato |
Sentinel-1
ALOS/PALSAR-2 land subsidence accuracy assessment Alexandria City Egypt local climate zone random forest feature importance land surface temperature grid cells Sentinel-2 PALSAR-2 ASTER soil moisture ALOS-2 GA-BP water cloud model L-band SAR backscattering soil moisture content LAI HH and HV polarization flood NoBADI Florida Hurricane Irma synthetic aperture radar polarimetric radar co-polarized phase difference radar scattering vegetation radar applications agriculture leaf area index leave-one-out cross-validation oil palm radar vegetation index vegetation descriptors ecosystem carbon cycle L-band SAR vegetation index random forest regression plantation permafrost InSAR Qinghai-Tibet Plateau ALOS thermal melting collapse Sentinel-1A SBAS-InSAR heavy forest area potential landslide identification SAR-based landslide detection Growing Split-Based Approach (GSBA) Hokkaido landslide Putanpunas landslide SAR polarimetry model-free 3-component decomposition for full polarimetric data (MF3CF) radar polarimetry calibration Faraday rotation |
| ISBN | 3-0365-6105-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910639994803321 |
|
Tadono Takeo
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||
| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Earth Observations for Addressing Global Challenges
| Earth Observations for Addressing Global Challenges |
| Autore | Liou Yuei-An |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (248 p.) |
| Soggetto topico |
Research & information: general
Environmental economics |
| Soggetto non controllato |
snow albedo radiative forcing
snow albedo feedback radiative kernel remote sensing cloud fraction integrated liquid water integrated water vapour diurnal cycle microwave radiometer classification self-learning training data crop leaf area index comparison MODIS uncertainty China EVI climatic factor driving force grey relational analysis (GRA) Inner Mongolia Autonomous Region (IMAR) Earth Observation (EO) satellite sensors platform SAR GNSS-R optical sensors polar weather ice marine land surface temperature urban heat island surface urban heat island land use land management unit Earth observation radiometer VIS/NIR imager terrestrial ecosystem MODIS GPP product calibration arid region oasis-desert ecosystem Land use and land cover (LULC) cloud-to-ground (CG) lightning particulate matter (PM10) sulfur dioxide (SO2) El Niño 2015-16 trace gases Upper Troposphere Lower Stratosphere |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557664003321 |
|
Liou Yuei-An
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Learning to Understand Remote Sensing Images . Volume 2
| Learning to Understand Remote Sensing Images . Volume 2 |
| Autore | Wang Qi |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (363 pages) |
| Soggetto non controllato |
metadata
image classification sensitivity analysis ROI detection residual learning image alignment adaptive convolutional kernels Hough transform class imbalance land surface temperature inundation mapping multiscale representation object-based convolutional neural networks scene classification morphological profiles hyperedge weight estimation hyperparameter sparse representation semantic segmentation vehicle classification flood Landsat imagery target detection multi-sensor building damage detection optimized kernel minimum noise fraction (OKMNF) sea-land segmentation nonlinear classification land use SAR imagery anti-noise transfer network sub-pixel change detection Radon transform segmentation remote sensing image retrieval TensorFlow convolutional neural network particle swarm optimization optical sensors machine learning mixed pixel optical remotely sensed images object-based image analysis very high resolution images single stream optimization ship detection ice concentration online learning manifold ranking dictionary learning urban surface water extraction saliency detection spatial attraction model (SAM) quality assessment Fuzzy-GA decision making system land cover change multi-view canonical correlation analysis ensemble land cover semantic labeling sparse representation dimensionality expansion speckle filters hyperspectral imagery fully convolutional network infrared image Siamese neural network Random Forests (RF) feature matching color matching geostationary satellite remote sensing image change feature analysis road detection deep learning aerial images image segmentation aerial image multi-sensor image matching HJ-1A/B CCD endmember extraction high resolution multi-scale clustering heterogeneous domain adaptation hard classification regional land cover hypergraph learning automatic cluster number determination dilated convolution MSER semi-supervised learning gate Synthetic Aperture Radar (SAR) downscaling conditional random fields urban heat island hyperspectral image remote sensing image correction skip connection ISPRS spatial distribution geo-referencing Support Vector Machine (SVM) very high resolution (VHR) satellite image classification ensemble learning synthetic aperture radar conservation convolutional neural network (CNN) THEOS visible light and infrared integrated camera vehicle localization structured sparsity texture analysis DSFATN CNN image registration UAV unsupervised classification SVMs SAR image fuzzy neural network dimensionality reduction GeoEye-1 feature extraction sub-pixel energy distribution optimizing saliency analysis deep convolutional neural networks sparse and low-rank graph hyperspectral remote sensing tensor low-rank approximation optimal transport SELF spatiotemporal context learning Modest AdaBoost topic modelling multi-seasonal Segment-Tree Filtering locality information GF-4 PMS image fusion wavelet transform hashing machine learning techniques satellite images climate change road segmentation remote sensing tensor sparse decomposition Convolutional Neural Network (CNN) multi-task learning deep salient feature speckle canonical correlation weighted voting fully convolutional network (FCN) despeckling multispectral imagery ratio images linear spectral unmixing hyperspectral image classification multispectral images high resolution image multi-objective convolution neural network transfer learning 1-dimensional (1-D) threshold stability Landsat kernel method phase congruency subpixel mapping (SPM) tensor MODIS GSHHG database compressive sensing |
| ISBN | 3-03897-699-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367755503321 |
|
Wang Qi
|
||
| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Learning to Understand Remote Sensing Images . Volume 1
| Learning to Understand Remote Sensing Images . Volume 1 |
| Autore | Wang Qi |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (414 pages) |
| Soggetto non controllato |
metadata
image classification sensitivity analysis ROI detection residual learning image alignment adaptive convolutional kernels Hough transform class imbalance land surface temperature inundation mapping multiscale representation object-based convolutional neural networks scene classification morphological profiles hyperedge weight estimation hyperparameter sparse representation semantic segmentation vehicle classification flood Landsat imagery target detection multi-sensor building damage detection optimized kernel minimum noise fraction (OKMNF) sea-land segmentation nonlinear classification land use SAR imagery anti-noise transfer network sub-pixel change detection Radon transform segmentation remote sensing image retrieval TensorFlow convolutional neural network particle swarm optimization optical sensors machine learning mixed pixel optical remotely sensed images object-based image analysis very high resolution images single stream optimization ship detection ice concentration online learning manifold ranking dictionary learning urban surface water extraction saliency detection spatial attraction model (SAM) quality assessment Fuzzy-GA decision making system land cover change multi-view canonical correlation analysis ensemble land cover semantic labeling sparse representation dimensionality expansion speckle filters hyperspectral imagery fully convolutional network infrared image Siamese neural network Random Forests (RF) feature matching color matching geostationary satellite remote sensing image change feature analysis road detection deep learning aerial images image segmentation aerial image multi-sensor image matching HJ-1A/B CCD endmember extraction high resolution multi-scale clustering heterogeneous domain adaptation hard classification regional land cover hypergraph learning automatic cluster number determination dilated convolution MSER semi-supervised learning gate Synthetic Aperture Radar (SAR) downscaling conditional random fields urban heat island hyperspectral image remote sensing image correction skip connection ISPRS spatial distribution geo-referencing Support Vector Machine (SVM) very high resolution (VHR) satellite image classification ensemble learning synthetic aperture radar conservation convolutional neural network (CNN) THEOS visible light and infrared integrated camera vehicle localization structured sparsity texture analysis DSFATN CNN image registration UAV unsupervised classification SVMs SAR image fuzzy neural network dimensionality reduction GeoEye-1 feature extraction sub-pixel energy distribution optimizing saliency analysis deep convolutional neural networks sparse and low-rank graph hyperspectral remote sensing tensor low-rank approximation optimal transport SELF spatiotemporal context learning Modest AdaBoost topic modelling multi-seasonal Segment-Tree Filtering locality information GF-4 PMS image fusion wavelet transform hashing machine learning techniques satellite images climate change road segmentation remote sensing tensor sparse decomposition Convolutional Neural Network (CNN) multi-task learning deep salient feature speckle canonical correlation weighted voting fully convolutional network (FCN) despeckling multispectral imagery ratio images linear spectral unmixing hyperspectral image classification multispectral images high resolution image multi-objective convolution neural network transfer learning 1-dimensional (1-D) threshold stability Landsat kernel method phase congruency subpixel mapping (SPM) tensor MODIS GSHHG database compressive sensing |
| ISBN | 3-03897-685-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367755603321 |
|
Wang Qi
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||
| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Remote Sensing Monitoring of Land Surface Temperature (LST)
| Remote Sensing Monitoring of Land Surface Temperature (LST) |
| Autore | Sánchez Juan Manuel |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (337 p.) |
| Soggetto topico | Environmental science, engineering & technology |
| Soggetto non controllato |
Land Surface Temperature (LST)
satellite retrievals of LST LST from GOES satellites land surface temperature drones unmanned aerial vehicles thermal remote sensing MODIS Bayesian Maximum Entropy interpolation Himalaya air temperature topography Landsat split window algorithm TIRS thermal Landsat 8 stray light correction split-window algorithm single-channel algorithm AMSR2 annual cycle parameters random forest cloudy sky LST evapotranspiration data fusion field-scale machine-learning physical model Sentinel-2 Sentinel-3 Downscaling thermal infrared disaggregation Copernicus hyperspectral thermal infrared spectral smoothness temperature-emissivity separation sensitivity analysis noise land surface temperature (LST) daytime LST nighttime LST validation land surface emissivity (LSE) single channel algorithm radiative transfer equation mono window algorithm SURFRAD data GK2A split-window method BSRN LST downscaling LSA-SAF Sentinel 2 DEM spatial averaging biases land surface emissivity measurement uncertainties emissivity box method Fourier transform infrared spectrometer portable spectrometer |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Remote Sensing Monitoring of Land Surface Temperature |
| Record Nr. | UNINA-9910557522303321 |
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Sánchez Juan Manuel
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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 Evapotranspiration (ET)
| Remote Sensing of Evapotranspiration (ET) |
| Autore | Gowda Prasanna |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (240 p.) |
| Soggetto non controllato |
Eddy-covariance
surface energy balance model evapotranspiration Oklahoma Mesonet Chi river basin SADFAET a stratification method ecosystem management process-based model heterogeneous conditions land surface temperature ETMonitor model latent heat flux multi-source water resources management remote sensing ET fusion Google Earth Engine water stress component temperature decomposition data fusion Mun river basin Murrumbidgee River catchment remote-sensing Thailand uncertainty field-scale partition land surface model two-source energy balance model Surface Energy Balance System China evapotranspiration partitioning yield calibration unmixing-based method Landsat 8 eddy covariance observations METRIC MODIS surface energy balance algorithm for land (SEBAL) West Africa MPDI-integrated SEBS STARFM multi-source satellite data |
| ISBN | 3-03921-603-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Remote Sensing of Evapotranspiration |
| Record Nr. | UNINA-9910367754003321 |
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Gowda Prasanna
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Remote Sensing of Land Surface Phenology
| Remote Sensing of Land Surface Phenology |
| Autore | Ma Xuanlong |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (276 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology Environmental science, engineering & technology |
| Soggetto non controllato |
climate change
digital camera MODIS Mongolian oak phenology sap flow urbanization plant phenology spatiotemporal patterns structural equation model Google Earth Engine Three-River Headwaters region GPP carbon cycle arctic photosynthesis remote sensing crop sowing date development stage yield gap yield potential process-based model land surface temperature urban heat island effect contribution Hangzhou land surface phenology NDVI spatiotemporal dynamics different drivers random forest model data suitability satellite data spatial scaling effects the Loess Plateau autumn phenology turning point climate changes human activities Qinghai-Tibetan Plateau snow phenology driving factors spatiotemporal variations Northeast China vegetation indexes seasonally dry tropical forest vegetation phenology climatic limitation solar-induced chlorophyll fluorescence enhanced vegetation index gross primary production evapotranspiration water use efficiency NDPI Qilian Mountains snow cover high elevation soil moisture vegetation dynamics carbon exchange |
| ISBN | 3-0365-5326-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910619465703321 |
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Ma Xuanlong
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| MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Remote Sensing of Savannas and Woodlands
| Remote Sensing of Savannas and Woodlands |
| Autore | Hill Michael J |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (286 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
Savanna
alternative stable states MODIS VCF land surface temperature albedo Cerrado Amazon vegetation type optical sar synergism mapping savanna post oak vegetation index ecosystem function phenology encroachment evergreen deciduous vegetation grassland fractional cover trend ecoregion bare soil livestock production systems remote sensing vegetation dynamics vegetation persistence conservation savannas Africa vegetation indices oak-grass savanna hydrology Sentinel-2 land cover grasslands forests monitoring random forest spectral indexes vegetation seasonality aboveground biomass Cerrado ecosystem SAR allometry biomass carbon cost-effective LiDAR TLS plant water availability tree phenology phenocams MODIS terrestrial laser scanning (TLS) Above Ground Biomass (AGB) 3D point cloud vegetation structure |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557426603321 |
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Hill Michael J
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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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