Search results: Found 9

Listing 1 - 9 of 9
Sort by
Sea Surface Salinity Remote Sensing

Authors: ---
ISBN: 9783039210763 / 9783039210770 Year: Pages: 296 DOI: 10.3390/books978-3-03921-077-0 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General)
Added to DOAB on : 2019-12-09 11:49:15
License:

Loading...
Export citation

Choose an application

Abstract

This Special Issue gathers papers reporting research on various aspects of remote sensing of Sea Surface Salinity (SSS) and the use of satellite SSS in oceanography. It includes contributions presenting improvements in empirical or theoretical radiative transfer models; mitigation techniques of external interference such as RFI and land contamination; comparisons and validation of remote sensing products with in situ observations; retrieval techniques for improved coastal SSS monitoring, high latitude SSS and the assessment of ocean interactions with the cryosphere; and data fusion techniques combining SSS with sea surface temperature (SST). New instrument technology for the future of SSS remote sensing is also presented.

Keywords

sea surface salinity --- remote sensing --- mediterranean sea --- smos --- alboran sea --- data processing --- quality assessment --- MICAP --- forward model --- combined active/passive SSS retrieval algorithm --- different instrument configurations --- retrieval errors --- SMAP --- sea surface salinity --- Arctic Ocean --- sea ice --- river discharge --- Arctic Gateways --- sea surface salinity --- remote sensing --- aquarius --- SMAP --- retrieval algorithm --- calibration --- validation --- satellite salinity --- Gulf of Maine --- bias characteristics --- Scotian Shelf --- Aquarius satellite --- sea surface salinity --- Aquarius Validation Data System (AVDS) --- ocean salinity --- microwave remote sensing --- remote sensing --- sea surface salinity --- SMAP --- SMOS --- Gulf of Mexico --- validation --- coastal --- salinity --- upwelling --- sea surface salinity --- remote sensing --- Arctic ocean --- SMOS --- Arctic rivers --- data processing --- quality assessment --- Aquarius --- Argo --- Sea Surface Salinity --- Water Cycle Observation Mission (WCOM) --- interferometric microwave imager (IMI) --- one-dimensional (1D) aperture synthesis radiometer --- sea surface salinity (SSS) --- brightness temperature (TB) --- sea surface salinity --- microwave radiometry --- remote sensing --- calibration --- retrieval algorithm --- validation --- Aquarius --- SMOS --- SMAP --- sea surface temperature --- sea surface salinity --- SMOS --- retroflections --- surface velocity --- water transport --- salt transport --- n/a --- sea surface salinity --- ocean surface roughness --- microwave radiometry --- remote sensing --- forward model --- retrieval algorithm

Participatory Forestry: Involvement, Information and Science

Author:
ISBN: 9783039213313 / 9783039213320 Year: Pages: 250 DOI: 10.3390/books978-3-03921-332-0 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General)
Added to DOAB on : 2019-12-09 11:49:15
License:

Loading...
Export citation

Choose an application

Abstract

Public participation in forestry is a key issue in ensuring the democratization of decision-making processes, increasing the social acceptance of policies, and reducing conflicts between forest users. Public participation also provides an opportunity for the improvement of the quality of information, public debate, personal reflection, and professionalization, raising awareness. Participation in forestry implies the involvement of stakeholders (the interest group participation approach) and/or the involvement of people (the direct citizen participation approach) in the decision-making process. Since the UN Conference on Environment and Development (1992), new norms and perspectives have emerged encouraging a bottom-up approach in forest governance. Consequently, several participatory techniques, methods, and tools for stakeholder involvement in forest governance have been developed and applied. These different experiences allow us to learn from failures and successes and contribute to knowledge improvement. The future challenges of participatory forestry deal with adaptation to changes in ecological, social, and economic contexts.

Entropy in Image Analysis

Author:
ISBN: 9783039210923 / 9783039210930 Year: Pages: 456 DOI: 10.3390/books978-3-03921-093-0 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:06
License:

Loading...
Export citation

Choose an application

Abstract

Image analysis is a fundamental task for extracting information from images acquired across a range of different devices. Since reliable quantitative results are requested, image analysis requires highly sophisticated numerical and analytical methods—particularly for applications in medicine, security, and remote sensing, where the results of the processing may consist of vitally important data. The contributions to this book provide a good overview of the most important demands and solutions concerning this research area. In particular, the reader will find image analysis applied for feature extraction, encryption and decryption of data, color segmentation, and in the support new technologies. In all the contributions, entropy plays a pivotal role.

Keywords

image retrieval --- multi-feature fusion --- entropy --- relevance feedback --- chaotic system --- image encryption --- permutation-diffusion --- SHA-256 hash value --- dynamic index --- entropy --- keyframes --- Shannon’s entropy --- sign languages --- video summarization --- video skimming --- image encryption --- multiple-image encryption --- two-dimensional chaotic economic map --- security analysis --- image encryption --- chaotic cryptography --- cryptanalysis --- chosen-plaintext attack --- image information entropy --- blind image quality assessment (BIQA) --- information entropy, natural scene statistics (NSS) --- Weibull statistics --- discrete cosine transform (DCT) --- ultrasound --- hepatic steatosis --- Shannon entropy --- fatty liver --- metabolic syndrome --- multi-exposure image fusion --- texture information entropy --- adaptive selection --- patch structure decomposition --- image encryption --- time-delay --- random insertion --- information entropy --- chaotic map --- uncertainty assessment --- deep neural network --- random forest --- Shannon entropy --- positron emission tomography --- reconstruction --- field of experts --- additive manufacturing --- 3D prints --- 3D scanning --- image entropy --- depth maps --- surface quality assessment --- machine vision --- image analysis --- Arimoto entropy --- free-form deformations --- normalized divergence measure --- gradient distributions --- nonextensive entropy --- non-rigid registration --- pavement --- macrotexture --- 3-D digital imaging --- entropy --- decay trend --- discrete entropy --- infrared images --- low contrast --- multiscale top-hat transform --- image encryption --- DNA encoding --- chaotic cryptography --- cryptanalysis --- image privacy --- computer aided diagnostics --- colonoscopy --- Rényi entropies --- structural entropy --- spatial filling factor --- binary image --- Cantor set --- Hénon map --- Minkowski island --- prime-indexed primes --- Ramanujan primes --- Kapur’s entropy --- color image segmentation --- whale optimization algorithm --- differential evolution --- hybrid algorithm --- Otsu method --- image encryption --- dynamic filtering --- DNA computing --- 3D Latin cube --- permutation --- diffusion --- fuzzy entropy --- electromagnetic field optimization --- chaotic strategy --- color image segmentation --- multilevel thresholding --- contrast enhancement --- sigmoid --- Tsallis statistics --- q-exponential --- q-sigmoid --- q-Gaussian --- ultra-sound images --- person re-identification --- image analysis --- hash layer --- quantization loss --- Hamming distance --- cross-entropy loss --- image entropy --- Shannon entropy --- generalized entropies --- image processing --- image segmentation --- medical imaging --- remote sensing --- security

New Developments in Statistical Information Theory Based on Entropy and Divergence Measures

Author:
ISBN: 9783038979364 / 9783038979371 Year: Pages: 344 DOI: 10.3390/books978-3-03897-937-1 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Social Sciences --- Sociology --- Statistics
Added to DOAB on : 2019-06-26 08:44:06
License:

Loading...
Export citation

Choose an application

Abstract

This book presents new and original research in Statistical Information Theory, based on minimum divergence estimators and test statistics, from a theoretical and applied point of view, for different statistical problems with special emphasis on efficiency and robustness. Divergence statistics, based on maximum likelihood estimators, as well as Wald’s statistics, likelihood ratio statistics and Rao’s score statistics, share several optimum asymptotic properties, but are highly non-robust in cases of model misspecification under the presence of outlying observations. It is well-known that a small deviation from the underlying assumptions on the model can have drastic effect on the performance of these classical tests. Specifically, this book presents a robust version of the classical Wald statistical test, for testing simple and composite null hypotheses for general parametric models, based on minimum divergence estimators.

Keywords

sparse --- robust --- divergence --- MM algorithm --- Bregman divergence --- generalized linear model --- local-polynomial regression --- model check --- nonparametric test --- quasi-likelihood --- semiparametric model --- Wald statistic --- composite likelihood --- maximum composite likelihood estimator --- Wald test statistic --- composite minimum density power divergence estimator --- Wald-type test statistics --- Bregman divergence --- general linear model --- hypothesis testing --- influence function --- robust --- Wald-type test --- log-linear models --- ordinal classification variables --- association models --- correlation models --- minimum penalized ?-divergence estimator --- consistency --- asymptotic normality --- goodness-of-fit --- bootstrap distribution estimator --- thematic quality assessment --- relative entropy --- logarithmic super divergence --- robustness --- minimum divergence inference --- generalized renyi entropy --- minimum divergence methods --- robustness --- single index model --- model assessment --- statistical distance --- non-quadratic distance --- total variation --- mixture index of fit --- Kullback-Leibler distance --- divergence measure --- ?-divergence --- relative error estimation --- robust estimation --- information geometry --- centroid --- Bregman information --- Hölder divergence --- indoor localization --- robustness --- efficiency --- Bayesian nonparametric --- Bayesian semi-parametric --- asymptotic property --- minimum disparity methods --- Hellinger distance --- Berstein von Mises theorem --- measurement errors --- robust testing --- two-sample test --- misspecified hypothesis and alternative --- 2-alternating capacities --- composite hypotheses --- corrupted data --- least-favorable hypotheses --- Neyman Pearson test --- divergence based testing --- Chernoff Stein lemma --- compressed data --- Hellinger distance --- representation formula --- iterated limits --- influence function --- consistency --- asymptotic normality --- location-scale family --- n/a

New Advances on Zika Virus Research

Authors: ---
ISBN: 9783038977643 Year: Pages: 552 DOI: 10.3390/books978-3-03897-765-0 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Internal medicine --- Medicine (General)
Added to DOAB on : 2019-04-05 10:34:31
License:

Loading...
Export citation

Choose an application

Abstract

Zika virus (ZIKV) is a mosquito-borne member of the Flaviviridae family that historically has been associated with mild febrile illness. However, the recent outbreaks in Brazil in 2015 and its rapid spread throughout South and Central America and the Caribbean, together with its association with severe neurological disorders—including fetal microcephaly and Guillain-Barré syndrome in adults—have changed the historic perspective of ZIKV. Currently, ZIKV is considered an important public health concern that has the potential to affect millions of people worldwide. The significance of ZIKV in human health and the lack of approved vaccines and/or antiviral drugs to combat ZIKV infection have triggered a global effort to develop effective countermeasures to prevent and/or treat ZIKV infection. In this Special Issue of Viruses, we have assembled a collection of 32 research and review articles that cover the more recent advances on ZIKV molecular biology, replication and transmission, virus–host interactions, pathogenesis, epidemiology, vaccine development, antivirals, and viral diagnosis.

Keywords

Ziks virus --- silvestrol --- antiviral --- eIF4A --- hepatocytes --- flavivirus --- arbovirus --- Zika --- sexual transmission --- testis --- prostate --- Zika virus --- ZIKV --- rhesus macaques --- Non-human primates --- NHP --- infection --- natural history --- Asian-lineage --- African-lineage --- zika virus --- ZIKV–host interactions --- viral pathogenesis --- cell surface receptors --- antiviral responses --- viral counteraction --- cytopathic effects --- microcephaly --- ZIKV-associated neurologic disorders --- Zika virus --- serology --- flavivirus --- microsphere immunoassay --- validated --- optimised --- dengue virus --- ZIKV --- reporter virus --- cryptic promoter silencing --- full-length molecular clone --- subgenomic replicon --- plasmid toxicity --- Zika virus --- dengue viruses --- flavivirus --- ELISA --- indirect immunofluorescence --- plaque reduction neutralization test --- polymerase chain reaction --- cross-reactions --- Zika virus --- flavivirus --- infectious cDNA --- replication --- gene expression --- neuropathogenesis --- viral genetic variation --- host genetic variation --- flavivirus --- Zika virus --- therapy --- host-directed antivirals --- Aedes aegypti --- RNA-seq --- insecticide resistance --- Zika virus --- detoxification and immune system responses --- Zika virus --- mosquito-borne flavivirus --- emerging arbovirus --- outbreak control --- molecular diagnostics --- laboratory preparedness --- assay standardization --- external quality assessment --- EQA --- QCMD --- flavivirus --- eye --- zika virus --- blood-retinal barrier --- ocular --- innate response --- Zika virus --- pregnancy --- fetal infection --- congenital Zika syndrome --- Asian lineage --- Zika virus --- Full-length cDNA infectious clones --- Bacterial artificial chromosome --- NS2A protein --- Zika virus --- neural progenitor cells --- neurons --- Zika virus --- antivirals --- therapeutics --- research models and tools --- flavivirus --- Zika virus (ZIKV) --- reverse genetics --- infectious clone --- full-length molecular clone --- bacterial artificial chromosome --- replicon --- infectious RNA --- Zika virus --- flavivirus --- arbovirus --- sexual transmission --- host genetic variation --- immune response --- Zika virus --- flaviviruses --- vaccines --- virus like particles --- clinical trials --- ZIKV --- NS1 protein --- Zika virus --- diagnosis --- monoclonal antibodies --- ELISA --- zika virus --- placenta cells --- microglia cells --- siRNA --- TLR7/8 --- Zika --- viral evolution --- genetic variability --- Bayesian analyses --- Zika virus --- reverse genetics --- infectious cDNA --- Tet-inducible --- MR766 --- FSS13025 --- flavivirus --- ZIKV --- NS5 --- type I IFN antagonist --- point-of-care diagnostics --- isothermal nucleic acid amplification --- nucleic acid computation --- nucleic acid strand exchange --- zika virus --- mosquito --- mosquito surveillance --- multiplex nucleic acid detection --- boolean logic-processing nucleic acid probes --- Zika virus --- flavivirus --- astrocytomas --- dsRNA --- viral fitness --- antiviral --- heme-oxygenase 1 --- Zika virus --- viral replication --- Zika virus --- antiviral compounds --- neural cells --- viral replication --- flavivirus --- Zika virus --- viral persistence --- testicular cells --- testes --- Zika virus --- prM-E proteins --- viral pathogenicity --- virus attachment --- viral replication --- viral permissiveness --- viral survival --- apoptosis --- cytopathic effects --- mutagenesis --- chimeric viruses --- human brain glial cells --- Zika virus --- flavivirus --- microRNAs --- neurons --- neuroinflammation --- anti-viral immunity --- Zika virus --- dengue virus --- secondary infections --- cross-reactions --- IgA --- IgG avidity tests

Sensors in Agriculture

Author:
ISBN: 9783038974123 / 9783038974130 Year: Pages: 346 DOI: 10.3390/books978-3-03897-413-0 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:06
License:

Loading...
Export citation

Choose an application

Abstract

Agriculture requires technical solutions for increasing production while lessening environmental impact by reducing the application of agro-chemicals and increasing the use of environmentally friendly management practices. A benefit of this is the reduction of production costs. Sensor technologies produce tools to achieve the abovementioned goals. The explosive technological advances and developments in recent years have enormously facilitated the attainment of these objectives, removing many barriers for their implementation, including the reservations expressed by farmers. Precision agriculture and ‘smart farming’ are emerging areas where sensor-based technologies play an important role. Farmers, researchers, and technical manufacturers are joining their efforts to find efficient solutions, improvements in production, and reductions in costs. This book brings together recent research and developments concerning novel sensors and their applications in agriculture. Sensors in agriculture are based on the requirements of farmers, according to the farming operations that need to be addressed.

Keywords

wireless sensor network (WSN) --- Wi-SUN --- vine --- mandarin orange --- thermal image --- fluorescent measurement --- X-ray fluorescence spectroscopy --- visible and near-infrared reflectance spectroscopy --- heavy metal contamination --- spectral pre-processing --- feature selection --- machine-learning --- LiDAR --- light-beam --- plant localization --- Kinect --- leaf area index --- radiative transfer model --- neural networks --- GF-1 satellite --- wide field view --- big data --- geo-information --- plant phenotyping --- grapevine breeding --- Vitis vinifera --- ambient intelligence --- wireless sensor --- fuzzy logic --- smart irrigation --- virtual organizations of agents --- CIE-Lab --- precision plant protection --- optical sensor --- weed control --- classification --- NIR hyperspectral imaging --- chemometrics analysis --- weeds --- UAS --- RPAS --- one-class --- machine learning --- remote sensing --- geoinformatics --- plant disease --- pest --- deep convolutional neural networks --- real-time processing --- detection --- hyperspectral imaging --- soil type classification --- total nitrogen --- texture features --- data fusion --- Fusarium --- near-infrared --- spectroscopy --- hulled barely --- partial least squares-discriminant analysis --- remote sensing --- precision agriculture --- crop monitoring --- data fusion --- speckle --- diffusion --- scattering --- biological sensing --- apparent soil electrical conductivity --- ECa-directed soil sampling --- electromagnetic induction --- proximal sensor --- response surface sampling --- salt tolerance --- boron tolerance --- soil mapping --- soil salinity --- spatial variability --- irrigation --- energy balance --- water management --- semi-arid regions --- on-line vis-NIR measurement --- total nitrogen --- total carbon --- spiking --- gradient boosted machines --- artificial neural networks --- random forests --- rice --- striped stem-borer --- hyperspectral imaging --- texture feature --- data fusion --- greenhouse --- wireless sensor network --- data fusion --- dynamic weight --- dataset --- agriculture --- obstacle detection --- computer vision --- cameras --- stereo imaging --- thermal imaging --- LiDAR --- radar --- object tracking --- crop area --- remote sensing image classification --- area frame sampling --- stratification --- regression estimator --- agriculture --- meat spoilage --- vegetable oil --- quality assessment --- electronic nose --- electrochemical sensors --- spectral analysis --- feature selection --- genetic algorithms --- classification --- vegetation indices --- vineyard --- diseases --- spatial data --- sensor --- data fusion --- change of support --- geostatistics --- precision agriculture --- management zones --- event detection --- back propagation model --- multivariate water quality parameters --- time-series data --- spatial-temporal model --- connected dominating set --- water supply network --- SS-OCT --- Capsicum annuum --- germination --- salt concentration --- deep learning --- clover-grass --- precision agriculture --- dry matter composition --- proximity sensing --- 3D reconstruction --- RGB-D sensor --- crop inspection platform --- water depth sensors --- soil moisture sensors --- temperature sensors --- rice field monitoring --- irrigation --- silage --- packing density --- moisture content --- compound sensor --- simultaneous measurement --- birth sensor --- bovine embedded hardware --- ambient intelligence --- virtual organizations of agents --- Fusarium --- near infrared --- discrimination --- hulled barely --- naked barley --- wheat --- dielectric probe --- apple shelf-life --- dielectric dispersion --- electronic nose --- pest scouting --- pest management --- gas sensor --- noninvasive detection --- nitrogen --- near infrared sensors --- drying temperature --- SPA-MLR --- PLS --- CARS --- hyperspectral camera --- handheld --- sensor evaluation --- case studies --- soil --- moisture --- sensor --- landslide --- rice leaves --- chromium content --- laser-induced breakdown spectroscopy --- laser wavelength --- preprocessing methods --- agricultural land --- field crops --- land cover --- photograph-grid method --- remote sensing --- data validation and calibration --- mobile app --- wireless sensor networks (WSN) --- energy efficiency --- distributed systems --- processing of sensed data --- WSN distribution algorithms --- recognition patterns --- agriculture

Sensors in Agriculture

Author:
ISBN: 9783038977445 / 9783038977452 Year: Pages: 354 DOI: 10.3390/books978-3-03897-745-2 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:06
License:

Loading...
Export citation

Choose an application

Abstract

Agriculture requires technical solutions for increasing production while lessening environmental impact by reducing the application of agro-chemicals and increasing the use of environmentally friendly management practices. A benefit of this is the reduction of production costs. Sensor technologies produce tools to achieve the abovementioned goals. The explosive technological advances and developments in recent years have enormously facilitated the attainment of these objectives, removing many barriers for their implementation, including the reservations expressed by farmers. Precision agriculture and ‘smart farming’ are emerging areas where sensor-based technologies play an important role. Farmers, researchers, and technical manufacturers are joining their efforts to find efficient solutions, improvements in production, and reductions in costs. This book brings together recent research and developments concerning novel sensors and their applications in agriculture. Sensors in agriculture are based on the requirements of farmers, according to the farming operations that need to be addressed.

Keywords

wireless sensor network (WSN) --- Wi-SUN --- vine --- mandarin orange --- thermal image --- fluorescent measurement --- X-ray fluorescence spectroscopy --- visible and near-infrared reflectance spectroscopy --- heavy metal contamination --- spectral pre-processing --- feature selection --- machine-learning --- LiDAR --- light-beam --- plant localization --- Kinect --- leaf area index --- radiative transfer model --- neural networks --- GF-1 satellite --- wide field view --- big data --- geo-information --- plant phenotyping --- grapevine breeding --- Vitis vinifera --- ambient intelligence --- wireless sensor --- fuzzy logic --- smart irrigation --- virtual organizations of agents --- CIE-Lab --- precision plant protection --- optical sensor --- weed control --- classification --- NIR hyperspectral imaging --- chemometrics analysis --- weeds --- UAS --- RPAS --- one-class --- machine learning --- remote sensing --- geoinformatics --- plant disease --- pest --- deep convolutional neural networks --- real-time processing --- detection --- hyperspectral imaging --- soil type classification --- total nitrogen --- texture features --- data fusion --- Fusarium --- near-infrared --- spectroscopy --- hulled barely --- partial least squares-discriminant analysis --- remote sensing --- precision agriculture --- crop monitoring --- data fusion --- speckle --- diffusion --- scattering --- biological sensing --- apparent soil electrical conductivity --- ECa-directed soil sampling --- electromagnetic induction --- proximal sensor --- response surface sampling --- salt tolerance --- boron tolerance --- soil mapping --- soil salinity --- spatial variability --- irrigation --- energy balance --- water management --- semi-arid regions --- on-line vis-NIR measurement --- total nitrogen --- total carbon --- spiking --- gradient boosted machines --- artificial neural networks --- random forests --- rice --- striped stem-borer --- hyperspectral imaging --- texture feature --- data fusion --- greenhouse --- wireless sensor network --- data fusion --- dynamic weight --- dataset --- agriculture --- obstacle detection --- computer vision --- cameras --- stereo imaging --- thermal imaging --- LiDAR --- radar --- object tracking --- crop area --- remote sensing image classification --- area frame sampling --- stratification --- regression estimator --- agriculture --- meat spoilage --- vegetable oil --- quality assessment --- electronic nose --- electrochemical sensors --- spectral analysis --- feature selection --- genetic algorithms --- classification --- vegetation indices --- vineyard --- diseases --- spatial data --- sensor --- data fusion --- change of support --- geostatistics --- precision agriculture --- management zones --- event detection --- back propagation model --- multivariate water quality parameters --- time-series data --- spatial-temporal model --- connected dominating set --- water supply network --- SS-OCT --- Capsicum annuum --- germination --- salt concentration --- deep learning --- clover-grass --- precision agriculture --- dry matter composition --- proximity sensing --- 3D reconstruction --- RGB-D sensor --- crop inspection platform --- water depth sensors --- soil moisture sensors --- temperature sensors --- rice field monitoring --- irrigation --- silage --- packing density --- moisture content --- compound sensor --- simultaneous measurement --- birth sensor --- bovine embedded hardware --- ambient intelligence --- virtual organizations of agents --- Fusarium --- near infrared --- discrimination --- hulled barely --- naked barley --- wheat --- dielectric probe --- apple shelf-life --- dielectric dispersion --- electronic nose --- pest scouting --- pest management --- gas sensor --- noninvasive detection --- nitrogen --- near infrared sensors --- drying temperature --- SPA-MLR --- PLS --- CARS --- hyperspectral camera --- handheld --- sensor evaluation --- case studies --- soil --- moisture --- sensor --- landslide --- rice leaves --- chromium content --- laser-induced breakdown spectroscopy --- laser wavelength --- preprocessing methods --- agricultural land --- field crops --- land cover --- photograph-grid method --- remote sensing --- data validation and calibration --- mobile app --- wireless sensor networks (WSN) --- energy efficiency --- distributed systems --- processing of sensed data --- WSN distribution algorithms --- recognition patterns --- agriculture

Learning to Understand Remote Sensing Images

Author:
ISBN: 9783038976844 / 9783038976851 Year: Volume: 1 Pages: 426 DOI: 10.3390/books978-3-03897-685-1 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
Added to DOAB on : 2019-12-09 11:49:15
License:

Loading...
Export citation

Choose an application

Abstract

With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.

Keywords

hyperspectral image classification --- SELF --- SVMs --- Segment-Tree Filtering --- multi-sensor --- change feature analysis --- object-based --- multispectral images --- heterogeneous domain adaptation --- transfer learning --- multi-view canonical correlation analysis ensemble --- semi-supervised learning --- canonical correlation weighted voting --- ensemble learning --- image classification --- spatial attraction model (SAM) --- subpixel mapping (SPM) --- land cover --- mixed pixel --- spatial distribution --- hard classification --- building damage detection --- Fuzzy-GA decision making system --- machine learning techniques --- optical remotely sensed images --- sensitivity analysis --- texture analysis --- quality assessment --- ratio images --- Synthetic Aperture Radar (SAR) --- speckle --- speckle filters --- ice concentration --- SAR imagery --- convolutional neural network --- urban surface water extraction --- threshold stability --- sub-pixel --- linear spectral unmixing --- Landsat imagery --- image registration --- image fusion --- UAV --- metadata --- visible light and infrared integrated camera --- semantic segmentation --- CNN --- deep learning --- ISPRS --- remote sensing --- gate --- hyperspectral image --- sparse and low-rank graph --- tensor --- dimensionality reduction --- semantic labeling --- convolution neural network --- fully convolutional network --- sea-land segmentation --- ship detection --- hyperspectral image --- target detection --- multi-task learning --- sparse representation --- locality information --- remote sensing image correction --- color matching --- optimal transport --- CNN --- very high resolution images --- segmentation --- multi-scale clustering --- vehicle localization --- vehicle classification --- high resolution --- aerial image --- convolutional neural network (CNN) --- class imbalance --- deep learning --- convolutional neural network (CNN) --- fully convolutional network (FCN) --- classification --- remote sensing --- high resolution --- semantic segmentation --- deep convolutional neural networks --- manifold ranking --- single stream optimization --- high resolution image --- feature extraction --- hypergraph learning --- morphological profiles --- hyperedge weight estimation --- semantic labeling --- convolutional neural networks --- remote sensing --- deep learning --- aerial images --- hyperspectral image --- feature extraction --- dimensionality reduction --- optimized kernel minimum noise fraction (OKMNF) --- hyperspectral remote sensing --- endmember extraction --- multi-objective --- particle swarm optimization --- image alignment --- feature matching --- geostationary satellite remote sensing image --- GSHHG database --- Hough transform --- dictionary learning --- road detection --- Radon transform --- geo-referencing --- multi-sensor image matching --- Siamese neural network --- satellite images --- synthetic aperture radar --- inundation mapping --- flood --- optical sensors --- spatiotemporal context learning --- Modest AdaBoost --- HJ-1A/B CCD --- GF-4 PMS --- hyperspectral image classification --- automatic cluster number determination --- adaptive convolutional kernels --- hyperspectral imagery --- 1-dimensional (1-D) --- Convolutional Neural Network (CNN) --- Support Vector Machine (SVM) --- Random Forests (RF) --- machine learning --- deep learning --- TensorFlow --- multi-seasonal --- regional land cover --- saliency analysis --- remote sensing --- ROI detection --- hyperparameter sparse representation --- dictionary learning --- energy distribution optimizing --- multispectral imagery --- nonlinear classification --- kernel method --- dimensionality expansion --- deep convolutional neural networks --- road segmentation --- conditional random fields --- satellite images --- aerial images --- THEOS --- land cover change --- downscaling --- sub-pixel change detection --- machine learning --- MODIS --- Landsat --- very high resolution (VHR) satellite image --- topic modelling --- object-based image analysis --- image segmentation --- unsupervised classification --- multiscale representation --- GeoEye-1 --- wavelet transform --- fuzzy neural network --- remote sensing --- conservation --- urban heat island --- land surface temperature --- climate change --- land use --- land cover --- Landsat --- remote sensing --- SAR image --- despeckling --- dilated convolution --- skip connection --- residual learning --- scene classification --- saliency detection --- deep salient feature --- anti-noise transfer network --- DSFATN --- infrared image --- image registration --- MSER --- phase congruency --- hashing --- remote sensing image retrieval --- online learning --- hyperspectral image --- compressive sensing --- structured sparsity --- tensor sparse decomposition --- tensor low-rank approximation

Learning to Understand Remote Sensing Images

Author:
ISBN: 9783038976981 / 9783038976998 Year: Volume: 2 Pages: 376 DOI: 10.3390/books978-3-03897-699-8 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
Added to DOAB on : 2019-12-09 11:49:15
License:

Loading...
Export citation

Choose an application

Abstract

With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.

Keywords

hyperspectral image classification --- SELF --- SVMs --- Segment-Tree Filtering --- multi-sensor --- change feature analysis --- object-based --- multispectral images --- heterogeneous domain adaptation --- transfer learning --- multi-view canonical correlation analysis ensemble --- semi-supervised learning --- canonical correlation weighted voting --- ensemble learning --- image classification --- spatial attraction model (SAM) --- subpixel mapping (SPM) --- land cover --- mixed pixel --- spatial distribution --- hard classification --- building damage detection --- Fuzzy-GA decision making system --- machine learning techniques --- optical remotely sensed images --- sensitivity analysis --- texture analysis --- quality assessment --- ratio images --- Synthetic Aperture Radar (SAR) --- speckle --- speckle filters --- ice concentration --- SAR imagery --- convolutional neural network --- urban surface water extraction --- threshold stability --- sub-pixel --- linear spectral unmixing --- Landsat imagery --- image registration --- image fusion --- UAV --- metadata --- visible light and infrared integrated camera --- semantic segmentation --- CNN --- deep learning --- ISPRS --- remote sensing --- gate --- hyperspectral image --- sparse and low-rank graph --- tensor --- dimensionality reduction --- semantic labeling --- convolution neural network --- fully convolutional network --- sea-land segmentation --- ship detection --- hyperspectral image --- target detection --- multi-task learning --- sparse representation --- locality information --- remote sensing image correction --- color matching --- optimal transport --- CNN --- very high resolution images --- segmentation --- multi-scale clustering --- vehicle localization --- vehicle classification --- high resolution --- aerial image --- convolutional neural network (CNN) --- class imbalance --- deep learning --- convolutional neural network (CNN) --- fully convolutional network (FCN) --- classification --- remote sensing --- high resolution --- semantic segmentation --- deep convolutional neural networks --- manifold ranking --- single stream optimization --- high resolution image --- feature extraction --- hypergraph learning --- morphological profiles --- hyperedge weight estimation --- semantic labeling --- convolutional neural networks --- remote sensing --- deep learning --- aerial images --- hyperspectral image --- feature extraction --- dimensionality reduction --- optimized kernel minimum noise fraction (OKMNF) --- hyperspectral remote sensing --- endmember extraction --- multi-objective --- particle swarm optimization --- image alignment --- feature matching --- geostationary satellite remote sensing image --- GSHHG database --- Hough transform --- dictionary learning --- road detection --- Radon transform --- geo-referencing --- multi-sensor image matching --- Siamese neural network --- satellite images --- synthetic aperture radar --- inundation mapping --- flood --- optical sensors --- spatiotemporal context learning --- Modest AdaBoost --- HJ-1A/B CCD --- GF-4 PMS --- hyperspectral image classification --- automatic cluster number determination --- adaptive convolutional kernels --- hyperspectral imagery --- 1-dimensional (1-D) --- Convolutional Neural Network (CNN) --- Support Vector Machine (SVM) --- Random Forests (RF) --- machine learning --- deep learning --- TensorFlow --- multi-seasonal --- regional land cover --- saliency analysis --- remote sensing --- ROI detection --- hyperparameter sparse representation --- dictionary learning --- energy distribution optimizing --- multispectral imagery --- nonlinear classification --- kernel method --- dimensionality expansion --- deep convolutional neural networks --- road segmentation --- conditional random fields --- satellite images --- aerial images --- THEOS --- land cover change --- downscaling --- sub-pixel change detection --- machine learning --- MODIS --- Landsat --- very high resolution (VHR) satellite image --- topic modelling --- object-based image analysis --- image segmentation --- unsupervised classification --- multiscale representation --- GeoEye-1 --- wavelet transform --- fuzzy neural network --- remote sensing --- conservation --- urban heat island --- land surface temperature --- climate change --- land use --- land cover --- Landsat --- remote sensing --- SAR image --- despeckling --- dilated convolution --- skip connection --- residual learning --- scene classification --- saliency detection --- deep salient feature --- anti-noise transfer network --- DSFATN --- infrared image --- image registration --- MSER --- phase congruency --- hashing --- remote sensing image retrieval --- online learning --- hyperspectral image --- compressive sensing --- structured sparsity --- tensor sparse decomposition --- tensor low-rank approximation

Listing 1 - 9 of 9
Sort by
Narrow your search

Publisher

MDPI - Multidisciplinary Digital Publishing Institute (9)


License

CC by-nc-nd (9)


Language

eng (9)


Year
From To Submit

2019 (9)