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GI for Disaster Management
GI for Disaster Management
Autore Altan Orhan
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Descrizione fisica 1 electronic resource (160 p.)
Soggetto topico Research & information: general
Environmental economics
Soggetto non controllato mapping impact
tidal flood
hydrodynamic model
solar salt farming
drone
computer vision
point clouds
machine learning
CNN
GAN
first responder
RECONASS
INACHUS
multi-hazard
susceptibility mapping
developing urban settlements
landslide
flood
logistic regression
Mamdani fuzzy algorithm
M-AHP
cartographic symbols
map symbology
crisis map
comparative analysis
taxonomy
graphic design
availability
promulgation
sharing
standardisation
Black sea
sea level change
tide gauge
satellite altimetry
GNSS
post-fire management
forest regeneration
fire severity mapping
multispectral imagery
Sentinel-2A
unmanned aerial vehicles
Parrot SEQUOIA
climate change
fuzzy logic
GIS, household
Index method
sea level rise
vulnerability
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557426203321
Altan Orhan  
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 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
Opac: Controlla la disponibilità qui
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  
MDPI - Multidisciplinary Digital Publishing Institute, 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Operationalization of Remote Sensing Solutions for Sustainable Forest Management
Operationalization of Remote Sensing Solutions for Sustainable Forest Management
Autore Mozgeris Gintautas
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica 1 electronic resource (296 p.)
Soggetto topico Research & information: general
Soggetto non controllato forest road inventory
total station
global navigation satellite system
point cloud
precision density
positional accuracy
efficiency
mangrove sustainability
deforestation depletion
anthropogenic
natural water balance
Southeast Asia
Phoracantha spp
unmanned aerial vehicle (UAV)
multispectral imagery
vegetation index
thresholding analysis
Large Scale Mean-Shift Segmentation (LSMS)
Random Forest (RF)
forest mask
validation
probability sampling
remote sensing
earth observations
forestry
accuracy assessment
forest classification
forested catchment
hydrological modeling
SWAT model
DEM
airborne laser scanning
deep learning
Landsat
national forest inventory
stand volume
bark beetle
Ips typographus L.
pest
change detection
forest damage
spruce
Sentinel-2
damage mapping
multi-temporal regression
mangrove
replanting
restoration
analytic hierarchy process
UAV
DJI drone
machine learning
forest canopy
canopy gaps
canopy openings percentage
satellite indices
Elastic Net
beech-fir forests
pixel-based supervised classification
random forest
support vector machine
gray level cooccurrence matrix (GLCM)
principal component analysis (PCA)
WorldView-3
wildfires
MaxENT
risk modeling
GIS
multi-scale analysis
Yakutia
Artic
Siberia
phenology modelling
forest disturbance
forest monitoring
bark beetle infestation
forest management
time series analysis
satellite imagery
landsat time series
growing stock volume
forest inventory
harmonic regression
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557584103321
Mozgeris Gintautas  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Remote Sensing for Precision Nitrogen Management
Remote Sensing for Precision Nitrogen Management
Autore Miao Yuxin
Pubbl/distr/stampa Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Descrizione fisica 1 electronic resource (602 p.)
Soggetto topico Technology: general issues
History of engineering & technology
Environmental science, engineering & technology
Soggetto non controllato UAS
multiple sensors
vegetation index
leaf nitrogen accumulation
plant nitrogen accumulation
pasture quality
airborne hyperspectral imaging
random forest regression
sun-induced chlorophyll fluorescence (SIF)
SIF yield indices
upward
downward
leaf nitrogen concentration (LNC)
wheat (Triticum aestivum L.)
laser-induced fluorescence
leaf nitrogen concentration
back-propagation neural network
principal component analysis
fluorescence characteristics
canopy nitrogen density
radiative transfer model
hyperspectral
winter wheat
flooded rice
pig slurry
aerial remote sensing
vegetation indices
N recommendation approach
Mediterranean conditions
nitrogen
vertical distribution
plant geometry
remote sensing
maize
UAV
multispectral imagery
LNC
non-parametric regression
red-edge
NDRE
dynamic change model
sigmoid curve
grain yield prediction
leaf chlorophyll content
red-edge reflectance
spectral index
precision N fertilization
chlorophyll meter
NDVI
NNI
canopy reflectance sensing
N mineralization
farmyard manures
Triticum aestivum
discrete wavelet transform
partial least squares
hyper-spectra
rice
nitrogen management
reflectance index
multiple variable linear regression
Lasso model
Multiplex®3 sensor
nitrogen balance index
nitrogen nutrition index
nitrogen status diagnosis
precision nitrogen management
terrestrial laser scanning
spectrometer
plant height
biomass
nitrogen concentration
precision agriculture
unmanned aerial vehicle (UAV)
digital camera
leaf chlorophyll concentration
portable chlorophyll meter
crop
PROSPECT-D
sensitivity analysis
UAV multispectral imagery
spectral vegetation indices
machine learning
plant nutrition
canopy spectrum
non-destructive nitrogen status diagnosis
drone
multispectral camera
SPAD
smartphone photography
fixed-wing UAV remote sensing
random forest
canopy reflectance
crop N status
Capsicum annuum
proximal optical sensors
Dualex sensor
leaf position
proximal sensing
cross-validation
feature selection
hyperparameter tuning
image processing
image segmentation
nitrogen fertilizer recommendation
supervised regression
RapidSCAN sensor
nitrogen recommendation algorithm
in-season nitrogen management
nitrogen use efficiency
yield potential
yield responsiveness
standard normal variate (SNV)
continuous wavelet transform (CWT)
wavelet features optimization
competitive adaptive reweighted sampling (CARS)
partial least square (PLS)
grapevine
hyperparameter optimization
multispectral imaging
precision viticulture
RGB
multispectral
coverage adjusted spectral index
vegetation coverage
random frog algorithm
active canopy sensing
integrated sensing system
discrete NIR spectral band data
soil total nitrogen concentration
moisture absorption correction index
particle size correction index
coupled elimination
ISBN 3-0365-5710-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910637794503321
Miao Yuxin  
Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
UAVs for Vegetation Monitoring
UAVs for Vegetation Monitoring
Autore de Castro Megías Ana
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica 1 electronic resource (452 p.)
Soggetto topico Research & information: general
Soggetto non controllato UAS
UAV
vegetation cover
multispectral
land cover
forest
Acacia
Indonesia
tropics
vegetation ground cover
vegetation indices
agro-environmental measures
olive groves
southern Spain
sUAS
water stress
ornamental
container-grown
artificial intelligence
machine learning
deep learning
neural network
visual recognition
precision agriculture
canopy cover
image analysis
crop mapping
evapotranspiration (ET)
GRAPEX
remote sensing
Two Source Energy Balance model (TSEB)
contextual spatial domain/resolution
data aggregation
eddy covariance (EC)
Fusarium wilt
crop disease
banana
multispectral remote sensing
purple rapeseed leaves
unmanned aerial vehicle
U-Net
plant segmentation
nitrogen stress
Glycine max
RGB
canopy height
close remote sensing
growth model
curve fitting
NDVI
solar zenith angle
flight altitude
time of day
operating parameters
CNN
Faster RCNN
SSD
Inception v2
patch-based CNN
MobileNet v2
detection performance
inference time
disease detection
cotton root rot
plant-level
single-plant
plant-by-plant
classification
UAV remote sensing
crop monitoring
RGB imagery
multispectral imagery
century-old biochar
semantic segmentation
random forest
crop canopy
multispectral image
chlorophyll content
remote sensing technique
individual plant segmentation
plant detection
transfer learning
maize tassel
tassel branch number
convolution neural network
VGG16
plant nitrogen estimation
vegetation index
image segmentation
transpiration
method comparison
oil palm
multiple linear regression
support vector machine
artificial neural network
UAV hyperspectral
wheat yellow rust
disease monitoring
texture
spatial resolution
RGB camera
thermal camera
drought tolerance
forage grass
HSV
CIELab
broad-sense heritability
phenotyping gap
high throughput field phenotyping
UAV digital images
winter wheat biomass
multiscale textures
red-edge spectra
least squares support vector machine
variable importance
drone
hyperspectral
thermal
nutrient deficiency
weed detection
disease diagnosis
plant trails
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557661103321
de Castro Megías Ana  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui