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Advancing Earth Surface Representation via Enhanced Use of Earth Observations in Monitoring and Forecasting Applications
Advancing Earth Surface Representation via Enhanced Use of Earth Observations in Monitoring and Forecasting Applications
Autore Ruston Benjamin
Pubbl/distr/stampa MDPI - Multidisciplinary Digital Publishing Institute, 2019
Descrizione fisica 1 electronic resource (262 pages)
Soggetto non controllato direct and inverse methods
absorption coefficient
emissivity
land-surface model
variational retrieval
temporal autocorrelation
Bayesian bias correction
hyperspectral
infrared
BRDF
satellite rainfall
MCD43C1
penetration depth
RTTOV
earth-observations
earth system modelling
representative depth
land
Changjiang (Yangtze) estuary
CDOM
soil moisture
surface
Maqu network
surface soil moisture
MODIS
soil effective temperature
GOCI
microwave remote sensing
rain gauge
QAA inversion
broadband emissivity
radiation
surface parameters
satellite data
East Africa
ISBN 3-03921-065-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910367566003321
Ruston Benjamin  
MDPI - Multidisciplinary Digital Publishing Institute, 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Atmospheric Measurements with Unmanned Aerial Systems (UAS)
Atmospheric Measurements with Unmanned Aerial Systems (UAS)
Autore Guzman Marcelo
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica 1 electronic resource (248 p.)
Soggetto topico Research & information: general
Soggetto non controllato unmanned aerial vehicles (UAV)
drones
geostatistics
atmospheric physics
meteorology
spatial sampling
unmanned aerial vehicles
unmanned aerial systems, turbulence
atmospheric boundary layer
TK-1G sounding rocket
near space
data analysis
remote sensing
unmanned aerial systems
atmospheric composition
sensors
UAS
RPAS
ALADINA
airborne turbulence
radiation measurements
aerosol measurements
field experiments
validation methods
unmanned aircraft
meteorological observation
stable atmospheric boundary layer
turbulence
remotely piloted aircraft systems (RPAS)
ground-based in-situ observations
boundary layer remote sensing
Arctic
polar
sea ice
source estimation
methane emissions
natural gas
leak surveys
inverse emissions
MONITOR
UAV
LDAR
air pollution
unmanned aerial vehicle (UAV)
PM2.5
meteorological condition
long-distance transport
satellite data
RMLD-UAV
methane
mass flux
leak rate quantification
wind speed and direction estimation algorithms
flow probes
airspeed measurement
small unmanned aircraft systems (sUAS)
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Altri titoli varianti Atmospheric Measurements with Unmanned Aerial Systems
Record Nr. UNINA-9910557665003321
Guzman Marcelo  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Remote Sensing in Hydrology and Water Resources Management
Remote Sensing in Hydrology and Water Resources Management
Autore Duan Weili
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica 1 electronic resource (487 p.)
Soggetto topico Research & information: general
Soggetto non controllato precipitation datasets
evaluation
spatial scale
temporal scale
climate
Yellow River Basin
data assimilation
WRF
WRFDA
3DVar
water levels
surface areas
volume variations
hypsometry
bathymetry
lakes
reservoirs
remote sensing
DAHITI
modified strahler approach
airborne LiDAR
DEM
flood inundation
flood map
flood model
LiDAR
terrestrial LiDAR
evapotranspiration
variability
uncertainty
unmanned aerial system
sUAS
multispectral
viticulture
water resources management
California
lake
Tibetan Plateau
hydrological changes
water balance
Chindwin basin
hydrological modelling
multi-variable calibration
satellite-based rainfall product
TRMM
temporal resolution
rainfall erosivity
combined approach
multi-objective optimization
modeling uncertainty
model constraint
SWAT
semiarid area
hydrological variations
normalized difference vegetation index
total water storage change
groundwater change
extreme precipitation
estimation
TMPA 3B42-V7
regional frequency analysis
China
satellite datasets
accuracy evaluation
hydrological applicability
Bosten Lake Basin
actual evapotranspiration
available water resources
climate change
vegetation greening
VIP-RS model
Lancang-Mekong river basin
MSWEP
AgMERRA
APHRODITE
CHIRPS
PERSIANN
error correction
agricultural water management
crop water consumption
remote sensing model
evapotranspiration allocation
inland water
IWCT
Tianjin
Landsat data
Tarim River Basin
desert-oasis ecotone
land-use change
CA-Markov model
remote sensing in hydrology
precipitation
performance evaluation
GPM
Poyang Lake
Yangtze River
assimilation
nonparametric modeling
multi-source
landscape pattern
spatiotemporal changes
influencing factors
watershed
China SE
satellite data
LUE-GPP
SPEI
copula function
conditional probability
soil moisture
neural network
downscaling
microwave data
MODIS data
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557632803321
Duan Weili  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
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 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
Ma Xuanlong  
MDPI - Multidisciplinary Digital Publishing Institute, 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Statistical Analysis and Stochastic Modelling of Hydrological Extremes
Statistical Analysis and Stochastic Modelling of Hydrological Extremes
Autore Tabari Hossein
Pubbl/distr/stampa MDPI - Multidisciplinary Digital Publishing Institute, 2019
Descrizione fisica 1 electronic resource (294 p.)
Soggetto non controllato artificial neural network
downscaling
innovative methods
reservoir inflow forecasting
simulation
extreme events
climate variability
sparse monitoring network
weighted mean analogue
sampling errors
precipitation
drought indices
discrete wavelet
SWSI
hyetograph
trends
climate change
SIAP
Kabul river basin
Hurst exponent
extreme rainfall
evolutionary strategy
the Cauca River
hydrological drought
global warming
least square support vector regression
polynomial normal transform
TRMM
satellite data
Fiji
heavy storm
flood regime
compound events
random forest
uncertainty
seasonal climate forecast
INDC pledge
Pakistan
wavelet artificial neural network
HBV model
temperature
APCC Multi-Model Ensemble
meteorological drought
flow regime
high resolution
rainfall
clausius-clapeyron scaling
statistical downscaling
ENSO
forecasting
variation analogue
machine learning
extreme rainfall analysis
hydrological extremes
multivariate modeling
monsoon
non-stationary
support vector machine
ANN model
stretched Gaussian distribution
drought prediction
non-normality
statistical analysis
extreme precipitation exposure
drought analysis
extreme value theory
streamflow
flood management
ISBN 3-03921-665-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910367749703321
Tabari Hossein  
MDPI - Multidisciplinary Digital Publishing Institute, 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Towards Excellence in Engineering Education
Towards Excellence in Engineering Education
Autore Ouahada Khmaies
Pubbl/distr/stampa MDPI - Multidisciplinary Digital Publishing Institute, 2019
Descrizione fisica 1 electronic resource (174 p.)
Soggetto non controllato high school
education
active methodology
spatial visualization
improving classroom teaching
faculty
evaluation
feedback
curriculum development
active learning
outcomes
learning activity
critical pedagogy
module
engineering
sustainability
teaching/learning strategies
PDF-3D
self-reflection
GIS
crystal system
chemical education
systems engineering
survey
satellite data
engineering education research
viscometer
anti-deficit approach
ternary phase diagrams
engineering education
service-learning
design
CDIO
professionalization
re-thinking the teaching
didactic virtual resources
open source software
didactic virtual tools
reverse engineering
underrepresented minorities
critical theoretical frameworks
pass rate
hidden curriculum
role-play
simulations
STEM
Green Engineering
inductive methods
moderation
mixed-methods
project-based learning
learning tool
spatial abilities
engineering curriculum
Bravais lattices
ISBN 3-03921-252-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910367737503321
Ouahada Khmaies  
MDPI - Multidisciplinary Digital Publishing Institute, 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui