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Big Data in Bioeconomy : Results from the European DataBio Project
| Big Data in Bioeconomy : Results from the European DataBio Project |
| Autore | Södergård Caj |
| Pubbl/distr/stampa | Cham, : Springer International Publishing AG, 2021 |
| Descrizione fisica | 1 online resource (416 p.) |
| Altri autori (Persone) |
MildorfTomas
HabyarimanaEphrem BerreArne J FernandesJose A Zinke-WehlmannChristian |
| Soggetto topico |
Forestry & silviculture: practice & techniques
Agricultural science Databases Environmental economics Dades massives Biologia econòmica |
| Soggetto genere / forma | Llibres electrònics |
| Soggetto non controllato |
Data-driven bioeconomy
big data artificial intelligence agriculture forestry earth observation satellite images fishery open access |
| ISBN | 3-030-71069-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Foreword -- Introduction -- Glossary -- Contents -- Part I Technological Foundation: Big Data Technologies for BioIndustries -- 1 Big Data Technologies in DataBio -- 1.1 Basic Concepts of Big Data -- 1.2 Pipelines and the BDV Reference Model -- 1.3 Open, Closed and FAIR Data -- 1.4 The DataBio Platform -- 1.5 Introduction to the Technology Chapters -- Literature -- 2 Standards and EO Data Platforms -- 2.1 Introduction -- 2.2 Standardization Organizations and Initiatives -- 2.2.1 The Role of Location in Bioeconomy -- 2.2.2 The Role of Semantics in Bioeconomy
2.3 Architecture Building Blocks for Cloud Based Services -- 2.4 Principles of an Earth Observation Cloud Architecture for Bioeconomy -- 2.4.1 Paradigm Shift: From SOA to Web API -- 2.4.2 Data and Processing Platform -- 2.4.3 Exploitation Platform -- 2.5 Standards for an Earth Observation Cloud Architecture -- 2.5.1 Applications and Application Packages -- 2.5.2 Application Deployment and Execution Service (ADES) -- 2.5.3 Execution Management Service (EMS) -- 2.5.4 AP, ADES, and EMS Interaction -- 2.6 Standards for Billing and Quoting -- 2.7 Standards for Security 2.8 Standards for Discovery, Cataloging, and Metadata -- 2.9 Summary -- References -- Part II Data Types -- 3 Sensor Data -- 3.1 Introduction -- 3.2 Internet of Things in Bioeconomy Sectors -- 3.3 Examples from DataBio -- 3.3.1 Gaiatrons -- 3.3.2 AgroNode -- 3.3.3 SensLog and Data Connectors -- 3.3.4 Mobile/Machinery Sensors -- References -- 4 Remote Sensing -- 4.1 Introduction -- 4.2 Earth Observation Relation to Big Data -- 4.3 Data Formats, Storage and Access -- 4.3.1 Formats and Standards -- 4.3.2 Data Sources -- 4.4 Selected Technologies -- 4.4.1 Metadata Catalogue 4.4.2 Object Storage and Data Access -- 4.5 Usage of Earth Observation Data in DataBio's Pilots -- References -- 5 Crowdsourced Data -- 5.1 Introduction -- 5.2 SensLog VGI Profile -- 5.3 Maps as Citizens Science Objects -- References -- 6 Genomics Data -- 6.1 Introduction -- 6.2 Genomic and Other Omics Data in DataBio -- 6.3 Genomic Data Management Systems -- References -- Part III Data Integration and Modelling -- 7 Linked Data and Metadata -- 7.1 Introduction -- 7.2 Metadata -- 7.3 Linked Data -- 7.4 Linked Data Best Practices -- 7.5 The Linked Open Data (LOD) Cloud 7.6 Enterprise Linked Data (LED) -- References -- 8 Linked Data Usages in DataBio -- 8.1 Introduction -- 8.2 Linked Data Pipeline Instantiations in DataBio -- 8.2.1 Linked Data in Agriculture Related to Cereals and Biomass Crops -- 8.2.2 Linked Sensor Data from Machinery Management -- 8.2.3 Linked Open EU-Datasets Related to Agriculture and Other Bio Sectors -- 8.2.4 Linked (Meta) Data of Geospatial Datasets -- 8.2.5 Linked Fishery Data -- 8.3 Experiences from DataBio with Linked Data -- 8.3.1 Usage and Exploitation of Linked Data -- 8.3.2 Experiences in the Agricultural Domain 8.3.3 Experiences with DBpedia |
| Record Nr. | UNINA-9910494568803321 |
Södergård Caj
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| Cham, : Springer International Publishing AG, 2021 | ||
| 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
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| 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
|
||
| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Remote Sensing in Coastline Detection
| Remote Sensing in Coastline Detection |
| Autore | Dominici Donatella |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (138 p.) |
| Soggetto topico | History of engineering & technology |
| Soggetto non controllato |
DGPS measurements
video camera observation shoreline position beach survey Sentinel-2 Remote Sensing habitat mapping mangroves coral reefs climate change vulnerable habitats side-scan sonar swath bathymetry habitat monitoring hurricane Sandy hurricane Joaquin shoreline detection remote sensing WorldView-2 Abruzzo multispectral classification shoreline coastline satellite images synthetic aperture radar (SAR) Sentinel-1 shoreline extraction coastline extraction active connection matrix (ACM) J-Net Dynamic edge detection canny edge detector coastline mapping geomatics SfM photogrammetry network RTK sea level rise coastlines 2100 storm surges heritage sites Pyrgi Mediterranean UAV DSM |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557546503321 |
|
Dominici Donatella
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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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