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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 online resource (404 p.) |
| Soggetto topico | Geography |
| Soggetto non controllato |
Cunninghamia
3D reconstruction aboveground biomass aerosol aerosol retrieval albedometer algorithmic assessment AMSR2 anisotropic reflectance Antarctica arid/semiarid AVHRR BEPS biodiversity black-sky albedo (BSA) boreal forest BRDF canopy reflectance China Chinese fir cloud fraction CMA composite slope comprehensive field experiment controlling factors copper cost-efficient crop-growing regions daily average value decision tree dense forest disturbance index downscaling downward shortwave radiation drought end of growing season (EOS) evapotranspiration EVI2 fluorescence quantum efficiency in dark-adapted conditions (FQE) flux measurements forest canopy height forest disturbance fractional vegetation cover (FVC) Fraunhofer Line Discrimination (FLD) FY-3C/MERSI FY-3C/MWRI gap fraction geographical detector model geometric optical radiative transfer (GORT) model geometric-optical model geostationary satellite GF-1 WFV GLASS GLASS LAI time series GPP gradient boosting regression tree gross primary production (GPP) gross primary productivity (GPP) heterogeneity high resolution high-resolution freeze/thaw HiWATER HJ-1 CCD homogeneous and pure pixel filter humidity profiles hybrid method ICESat GLAS inter-annual variation interference filter interpolation LAI land cover change land surface albedo Land surface emissivity land surface temperature Land surface temperature land surface variables land-surface temperature products (LSTs) Landsat latent heat latitudinal pattern leaf leaf age leaf area density leaf area index leaf spectral properties LiDAR light use efficiency longwave upwelling radiation (LWUP) LUT method machine learning machine learning algorithms maize MCD43A3 C6 meteorological factors metric comparison metric integration MODIS MODIS products MRT-based model MS-PT algorithm multi-data set multi-scale validation multiple ecological factors multisource data fusion MuSyQ-GPP algorithm n/a NDVI NIR Northeast China northern China NPP observations passive microwave phenological parameters phenology photoelectric detector pixel unmixing plant functional type point cloud polar orbiting satellite potential evapotranspiration precipitation probability density function PROSPECT PROSPECT-5B+SAILH (PROSAIL) model quantitative remote sensing inversion RADARSAT-2 random forest model reflectance model remote sensing rice rugged terrain sampling design satellite observations scale effects SCOPE SIF sinusoidal method snow cover snow-free albedo solar-induced chlorophyll fluorescence solo slope South China's spatial heterogeneity spatial representativeness spatial-temporal variations spatio-temporal spatiotemporal distribution and variation spatiotemporal representative species richness spectra spectral SPI standard error of the mean start of growing season (SOS) statistics methods subpixel information sunphotometer surface radiation budget surface solar irradiance SURFRAD Synthetic Aperture Radar (SAR) temperature profiles terrestrial LiDAR thermal radiation directionality Tibetan Plateau TMI data topographic effects tree canopy uncertainty urban scale validation variability vegetation dust-retention vegetation phenology vegetation remote sensing vertical structure vertical vegetation stratification Visible Infrared Imaging Radiometer Suite (VIIRS) voxel VPM ZY-3 MUX |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910346664103321 |
Shi Jiancheng
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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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 online resource (404 p.) |
| Soggetto topico | Geography |
| Soggetto non controllato |
Cunninghamia
3D reconstruction aboveground biomass aerosol aerosol retrieval albedometer algorithmic assessment AMSR2 anisotropic reflectance Antarctica arid/semiarid AVHRR BEPS biodiversity black-sky albedo (BSA) boreal forest BRDF canopy reflectance China Chinese fir cloud fraction CMA composite slope comprehensive field experiment controlling factors copper cost-efficient crop-growing regions daily average value decision tree dense forest disturbance index downscaling downward shortwave radiation drought end of growing season (EOS) evapotranspiration EVI2 fluorescence quantum efficiency in dark-adapted conditions (FQE) flux measurements forest canopy height forest disturbance fractional vegetation cover (FVC) Fraunhofer Line Discrimination (FLD) FY-3C/MERSI FY-3C/MWRI gap fraction geographical detector model geometric optical radiative transfer (GORT) model geometric-optical model geostationary satellite GF-1 WFV GLASS GLASS LAI time series GPP gradient boosting regression tree gross primary production (GPP) gross primary productivity (GPP) heterogeneity high resolution high-resolution freeze/thaw HiWATER HJ-1 CCD homogeneous and pure pixel filter humidity profiles hybrid method ICESat GLAS inter-annual variation interference filter interpolation LAI land cover change land surface albedo Land surface emissivity land surface temperature Land surface temperature land surface variables land-surface temperature products (LSTs) Landsat latent heat latitudinal pattern leaf leaf age leaf area density leaf area index leaf spectral properties LiDAR light use efficiency longwave upwelling radiation (LWUP) LUT method machine learning machine learning algorithms maize MCD43A3 C6 meteorological factors metric comparison metric integration MODIS MODIS products MRT-based model MS-PT algorithm multi-data set multi-scale validation multiple ecological factors multisource data fusion MuSyQ-GPP algorithm n/a NDVI NIR Northeast China northern China NPP observations passive microwave phenological parameters phenology photoelectric detector pixel unmixing plant functional type point cloud polar orbiting satellite potential evapotranspiration precipitation probability density function PROSPECT PROSPECT-5B+SAILH (PROSAIL) model quantitative remote sensing inversion RADARSAT-2 random forest model reflectance model remote sensing rice rugged terrain sampling design satellite observations scale effects SCOPE SIF sinusoidal method snow cover snow-free albedo solar-induced chlorophyll fluorescence solo slope South China's spatial heterogeneity spatial representativeness spatial-temporal variations spatio-temporal spatiotemporal distribution and variation spatiotemporal representative species richness spectra spectral SPI standard error of the mean start of growing season (SOS) statistics methods subpixel information sunphotometer surface radiation budget surface solar irradiance SURFRAD Synthetic Aperture Radar (SAR) temperature profiles terrestrial LiDAR thermal radiation directionality Tibetan Plateau TMI data topographic effects tree canopy uncertainty urban scale validation variability vegetation dust-retention vegetation phenology vegetation remote sensing vertical structure vertical vegetation stratification Visible Infrared Imaging Radiometer Suite (VIIRS) voxel VPM ZY-3 MUX |
| 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 | ||
| ||
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 |
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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 online resource (248 p.) |
| Soggetto topico |
Environmental economics
Research & information: general |
| Soggetto non controllato |
arid region
calibration China classification climatic factor cloud fraction cloud-to-ground (CG) lightning comparison crop diurnal cycle driving force Earth observation Earth Observation (EO) El Niño 2015-16 EVI GNSS-R grey relational analysis (GRA) ice Inner Mongolia Autonomous Region (IMAR) integrated liquid water integrated water vapour land management unit land surface temperature land use Land use and land cover (LULC) leaf area index marine microwave radiometer MODIS MODIS GPP product n/a oasis-desert ecosystem optical sensors particulate matter (PM10) platform polar radiative kernel radiometer remote sensing SAR satellite self-learning sensors snow albedo feedback snow albedo radiative forcing sulfur dioxide (SO2) surface urban heat island terrestrial ecosystem trace gases training data uncertainty Upper Troposphere Lower Stratosphere urban heat island VIS/NIR imager weather |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557664003321 |
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Liou Yuei-An
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Learning to Understand Remote Sensing Images: Volume 1 / Qi Wang
| Learning to Understand Remote Sensing Images: Volume 1 / Qi Wang |
| Autore | Wang Qi |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (414 pages) |
| Soggetto topico | Computer science |
| 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 |
9783038976851
3038976857 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367755603321 |
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Wang Qi
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Learning to Understand Remote Sensing Images: Volume 2 / Qi Wang
| Learning to Understand Remote Sensing Images: Volume 2 / Qi Wang |
| 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 |
9783038976998
3038976997 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367755503321 |
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Wang Qi
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||
| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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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 online resource (337 p.) |
| Soggetto topico | Environmental science, engineering & technology |
| Soggetto non controllato |
air temperature
AMSR2 annual cycle parameters Bayesian Maximum Entropy BSRN cloudy sky LST Copernicus data fusion daytime LST DEM disaggregation downscaling Downscaling drones emissivity box method evapotranspiration field-scale Fourier transform infrared spectrometer GK2A Himalaya hyperspectral thermal infrared interpolation land surface emissivity land surface emissivity (LSE) land surface temperature land surface temperature (LST) Land Surface Temperature (LST) Landsat Landsat 8 LSA-SAF LST LST from GOES satellites machine-learning measurement uncertainties MODIS mono window algorithm n/a nighttime LST noise physical model portable spectrometer radiative transfer equation random forest satellite retrievals of LST sensitivity analysis Sentinel 2 Sentinel-2 Sentinel-3 single channel algorithm single-channel algorithm spatial averaging biases spectral smoothness split window algorithm split-window algorithm split-window method stray light correction SURFRAD data temperature-emissivity separation thermal thermal infrared thermal remote sensing TIRS topography unmanned aerial vehicles validation |
| 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) / Pradeep Wagle, Prasanna Gowda
| Remote Sensing of Evapotranspiration (ET) / Pradeep Wagle, Prasanna Gowda |
| Autore | Wagle Pradeep |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (240 p.) |
| Soggetto topico | Biotechnology |
| 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 |
9783039216031
3039216031 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367754003321 |
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Wagle Pradeep
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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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 online resource (276 p.) |
| Soggetto topico |
Environmental science, engineering and technology
History of engineering and technology Technology: general issues |
| Soggetto non controllato |
arctic
autumn phenology carbon cycle carbon exchange climate change climate changes climatic limitation contribution crop sowing date data suitability development stage different drivers digital camera driving factors enhanced vegetation index evapotranspiration Google Earth Engine GPP gross primary production Hangzhou high elevation human activities land surface phenology land surface temperature MODIS Mongolian oak n/a NDPI NDVI Northeast China phenology photosynthesis plant phenology process-based model Qilian Mountains Qinghai-Tibetan Plateau random forest model remote sensing sap flow satellite data seasonally dry tropical forest snow cover snow phenology soil moisture solar-induced chlorophyll fluorescence spatial scaling effects spatiotemporal dynamics spatiotemporal patterns spatiotemporal variations structural equation model the Loess Plateau Three-River Headwaters region turning point urban heat island effect urbanization vegetation dynamics vegetation indexes vegetation phenology water use efficiency yield gap yield potential |
| 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 online resource (286 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
3D point cloud
Above Ground Biomass (AGB) aboveground biomass Africa albedo allometry alternative stable states Amazon bare soil biomass carbon Cerrado Cerrado ecosystem conservation cost-effective deciduous ecoregion ecosystem function encroachment evergreen forests fractional cover grassland grasslands hydrology land cover land surface temperature LiDAR livestock mapping MODIS MODIS VCF monitoring n/a oak-grass savanna optical phenocams phenology plant water availability post oak production systems random forest remote sensing sar SAR savanna Savanna savannas Sentinel-2 spectral indexes synergism terrestrial laser scanning (TLS) TLS tree phenology trend vegetation vegetation dynamics vegetation index vegetation indices vegetation persistence vegetation seasonality vegetation structure vegetation type |
| 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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