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
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Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
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Lo trovi qui: Univ. Federico II | ||
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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
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MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
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Lo trovi qui: Univ. Federico II | ||
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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 | ||
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Lo trovi qui: Univ. Federico II | ||
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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
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Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
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Lo trovi qui: Univ. Federico II | ||
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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
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Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
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Lo trovi qui: Univ. Federico II | ||
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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
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Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
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Lo trovi qui: Univ. Federico II | ||
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