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Sea Surface Temperature Retrievals from Remote Sensing

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ISBN: 9783038974796 / 9783038974802 Year: Pages: 340 DOI: 10.3390/books978-3-03897-480-2 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Chemistry (General)
Added to DOAB on : 2019-02-14 10:39:15
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This book covers topics ranging from a detailed error analysis of SSTs to new applications employed, for example, in the study of the El Niño–La Niña Southern Oscillation, lake temperatures, and coral bleaching. New techniques for interpolation and algorithm development are presented, including improvements for cloud detection. Analysis of the pixel-to-pixel uncertainties provides insight to applications for high spatial resolutions. New approaches for the estimation and evaluation of SSTs are presented. In addition, an overview of the Climate Change Initiative, with specific applications to SST, is presented. The book provides an excellent overview of the current technology, while also highlighting new technologies and their applications to new missions.

Urban Overheating - Progress on Mitigation Science and Engineering Applications

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ISBN: 9783038976363 Year: Pages: 350 DOI: 10.3390/books978-3-03897-637-0 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Meteorology and Climatology --- Science (General)
Added to DOAB on : 2019-04-05 10:34:31
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The combination of global warming and urban sprawl is the origin of the most hazardous climate change effect detected at urban level: Urban Heat Island, representing the urban overheating respect to the countryside surrounding the city. This book includes 18 papers representing the state of the art of detection, assessment mitigation and adaption to urban overheating. Advanced methods, strategies and technologies are here analyzed including relevant issues as: the role of urban materials and fabrics on urban climate and their potential mitigation, the impact of greenery and vegetation to reduce urban temperatures and improve the thermal comfort, the role the urban geometry in the air temperature rise, the use of satellite and ground data to assess and quantify the urban overheating and develop mitigation solutions, calculation methods and application to predict and assess mitigation scenarios. The outcomes of the book are thus relevant for a wide multidisciplinary audience, including: environmental scientists and engineers, architect and urban planners, policy makers and students.

Keywords

heat health --- meteorological modeling --- urban climate --- urban-climate archipelago --- urban heat island --- urban heat island index --- Weather Research and Forecasting model (WRF) --- green area --- built-up area --- air temperature --- measurement --- calculation --- urbanization --- air and surface temperature measurements --- outdoor thermal comfort --- urban heat island --- surface cool island effect --- urban overheating --- urban microclimate --- mitigation strategies --- urban development --- park cool island --- urban cooling --- urban morphology --- micro-climate simulations --- ageing --- emissivity --- measurement --- solar reflectance --- solar reflectance index --- thermal emittance --- urban heat island --- land surface temperature --- “hot spots” --- “cold spots” --- MODIS downscaling --- overheating --- summer heat stress --- urban open space --- shading --- thermal comfort --- Physiologically Equivalent Temperature --- mitigation strategies --- cooling technologies --- cool materials --- WRF-Chem --- urban climate --- air quality --- urban heat island --- surface albedo --- climatic perception --- urban areas --- thermal comfort --- subtropical climate --- cool pavements --- road lighting --- urban heat island --- road surface --- material characterization --- luminance coefficient --- energy savings --- Euramet --- EMPIR 16NRM02 --- building energy performance --- energy simulation --- building retrofit --- multi-objective optimization --- genetic algorithm --- urban overheating --- cost-optimal analysis --- lifecycle analysis --- office buildings --- sustainability --- air temperature --- spectral analysis --- multifractal analysis --- structure functions analysis --- cool roofs --- fine-resolution meteorological modeling --- mobile temperature observations --- urban climate archipelago --- urban heat island --- urban vegetation --- urbanized WRF --- Weather Research and Forecasting model --- multiple linear regression --- urban heat island --- urban climatology --- urban energy balance --- air temperature --- land cover fraction --- urban morphology --- land surface temperature --- heat stress --- urban heat mitigation --- albedo --- cool facades --- spectral reflectance --- urban remote sensing --- empirical line method --- building scale --- local climate zone --- urban climate --- sky view factor --- morphological indicator --- open science --- GIS --- urban heat island --- urban overheating --- non-constructible parcels --- cool surfaces --- urban vegetation --- ENVI-met --- mitigation measures --- Beirut

Growth and Ecosystem Services of Urban Trees

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ISBN: 9783039215928 / 9783039215935 Year: Pages: 170 DOI: 10.3390/books978-3-03921-593-5 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology --- Ecology
Added to DOAB on : 2019-12-09 11:49:16
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Numerous studies indicate an accelerated growth of forest trees, induced by ongoing climate change. Similar trends were recently found for urban trees in major cities worldwide. Studies frequently report about substantial effects of climate change and the urban heat island effect (UHI) on plant growth. The combined effects of increasing temperatures, changing precipitation patterns, and extended growing season lengths, in addition to increasing nitrogen deposition and higher CO2 concentrations, can increase but also reduce plant growth. Closely related to this, the multiple functions and services provided by urban trees may be modified. Urban trees generate numerous ecosystem services, including carbon storage, mitigation of the heat island effect, reduction of rainwater runoff, pollutant filtering, recreation effects, shading, and cooling. The quantity of the ecosystem services is often closely associated with the species, structure, age, and size of the tree as well as with a tree’s vitality. Therefore, greening cities, and particularly planting trees, seems to be an effective option to mitigate climate change and the UHI. The focus of this Special Issue is to underline the importance of trees as part of the urban green areas for major cities in all climate zones. Empirical as well as modeling studies of urban tree growth and their services and disservices in cities worldwide are included. Articles about the dynamics, structures, and functions of urban trees as well as the influence of climate and climate change on urban tree growth, urban species composition, carbon storage, and biodiversity are also discussed.

Remote Sensing of Evapotranspiration (ET)

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ISBN: 9783039216024 / 9783039216031 Year: Pages: 240 DOI: 10.3390/books978-3-03921-603-1 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- Biotechnology
Added to DOAB on : 2019-12-09 11:49:15
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Evapotranspiration (ET) is a critical component of the water and energy balances, and the number of remote sensing-based ET products and estimation methods has increased in recent years. Various aspects of remote sensing of ET are reported in the 11 papers published in this book. The major research areas covered by this book include inter-comparison and performance evaluation of widely used one- and two-source energy balance models, a new dual-source model (Soil Plant Atmosphere and Remote Sensing Evapotranspiration, SPARSE), and a process-based model (ETMonitor); assessment of multi-source (e.g., remote sensing, reanalysis, and land surface model) ET products; development or improvement of data fusion frameworks to predict continuous daily ET at a high spatial resolution (field-scale or 30 m) by fusing the advanced spaceborne thermal emission reflectance radiometer (ASTER), the moderate resolution imaging spectroradiometer (MODIS), and Landsat data; and investigating uncertainties in ET estimates using an ET ensemble composed of several land surface models and diagnostic datasets. The effects of the differences between ET products on water resources and ecosystem management were also investigated. More accurate ET estimates and improved understanding of remotely sensed ET products are crucial for maximizing crop productivity while minimizing water losses and management costs.

Cleaner Combustion

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ISBN: 9783039214778 / 9783039214785 Year: Pages: 196 DOI: 10.3390/books978-3-03921-478-5 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-12-09 11:49:16
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This volume provides unique views of combustion from many technical and international research perspectives.

Advances in Quantitative Remote Sensing in China – In Memory of Prof. Xiaowen Li

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ISBN: 9783038972709 Year: Volume: 1 Pages: 404 DOI: 10.3390/books978-3-03897-271-6 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Geography
Added to DOAB on : 2019-03-08 11:42:05
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Quantitative land remote sensing has recently advanced dramatically, particularly in China. It has been largely driven by vast governmental investment, the availability of a huge amount of Chinese satellite data, geospatial information requirements for addressing pressing environmental issues and other societal benefits. Many individuals have also fostered and made great contributions to its development, and Prof. Xiaowen Li was one of these leading figures. This book is published in memory of Prof. Li. The papers collected in this book cover topics from surface reflectance simulation, inversion algorithm and estimation of variables, to applications in optical, thermal, Lidar and microwave remote sensing. The wide range of variables include directional reflectance, chlorophyll fluorescence, aerosol optical depth, incident solar radiation, albedo, surface temperature, upward longwave radiation, leaf area index, fractional vegetation cover, forest biomass, precipitation, evapotranspiration, freeze/thaw snow cover, vegetation productivity, phenology and biodiversity indicators. They clearly reflect the current level of research in this area. This book constitutes an excellent reference suitable for upper-level undergraduate students, graduate students and professionals in remote sensing.

Keywords

evapotranspiration --- Northeast China --- MS–PT algorithm --- spatial-temporal variations --- controlling factors --- potential evapotranspiration --- vegetation remote sensing --- reflectance model --- spectra --- leaf --- copper --- PROSPECT --- leaf area density --- terrestrial LiDAR --- tree canopy --- vertical structure --- voxel --- spatial representativeness --- heterogeneity --- validation --- land-surface temperature products (LSTs) --- observations --- HiWATER --- remote sensing --- spatiotemporal representative --- cost-efficient, sampling design --- heterogeneity --- validation --- FY-3C/MERSI --- GLASS --- Land surface temperature --- Land surface emissivity --- GPP --- SIF --- MuSyQ-GPP algorithm --- BEPS --- vegetation phenology --- Tibetan Plateau --- MODIS --- NDVI --- start of growing season (SOS) --- end of growing season (EOS) --- GLASS LAI time series --- forest disturbance --- disturbance index --- latent heat --- machine learning algorithms --- plant functional type --- high-resolution freeze/thaw --- AMSR2 --- MODIS --- LAI --- ZY-3 MUX --- GF-1 WFV --- HJ-1 CCD --- maize --- PROSPECT-5B+SAILH (PROSAIL) model --- spatial heterogeneity --- variability --- evapotranspiration --- land surface variables --- probability density function --- HiWATER --- spectral --- albedometer --- interference filter --- photoelectric detector --- validation --- land surface albedo --- multi-scale validation --- rugged terrain --- MRT-based model --- MCD43A3 C6 --- precipitation --- statistics methods --- China --- Tibetan Plateau --- South China’s --- drought --- SPI --- TMI data --- crop-growing regions --- downward shortwave radiation --- machine learning --- gradient boosting regression tree --- AVHRR --- CMA --- BRDF --- aerosol --- MODIS --- sunphotometer --- arid/semiarid --- solar-induced chlorophyll fluorescence --- fluorescence quantum efficiency in dark-adapted conditions (FQE) --- SCOPE --- Fraunhofer Line Discrimination (FLD) --- gross primary productivity (GPP) --- longwave upwelling radiation (LWUP) --- Visible Infrared Imaging Radiometer Suite (VIIRS) --- surface radiation budget --- hybrid method --- remote sensing --- leaf age --- leaf spectral properties --- leaf area index --- Cunninghamia --- Chinese fir --- canopy reflectance --- NIR --- EVI2 --- geometric optical radiative transfer (GORT) model --- land surface albedo --- snow-free albedo --- rugged terrain --- topographic effects --- black-sky albedo (BSA) --- GPP --- NPP --- MODIS --- validation --- phenology --- RADARSAT-2 --- rice --- Synthetic Aperture Radar (SAR) --- decision tree --- forest canopy height --- aboveground biomass --- ICESat GLAS --- Landsat --- random forest model --- anisotropic reflectance --- BRDF --- rugged terrain --- solo slope --- composite slope --- surface solar irradiance --- geostationary satellite --- polar orbiting satellite --- LUT method --- SURFRAD --- downward shortwave radiation --- daily average value --- Antarctica --- sinusoidal method --- cloud fraction --- interpolation --- boreal forest --- GPP --- spatiotemporal distribution and variation --- meteorological factors --- phenological parameters --- multisource data fusion --- aerosol retrieval --- urban scale --- vegetation dust-retention --- multiple ecological factors --- geographical detector model --- snow cover --- passive microwave --- FY-3C/MWRI --- algorithmic assessment --- China --- land surface temperature --- satellite observations --- flux measurements --- latitudinal pattern --- land cover change --- fractional vegetation cover (FVC) --- multi-data set --- northern China --- spatio-temporal --- inter-annual variation --- uncertainty --- standard error of the mean --- downscaling --- GPP --- spatial heterogeneity --- remote sensing --- subpixel information --- LiDAR --- point cloud --- leaf --- gap fraction --- 3D reconstruction --- biodiversity --- remote sensing --- species richness --- metric comparison --- metric integration --- leaf area index --- MODIS products --- Landsat --- high resolution --- homogeneous and pure pixel filter --- pixel unmixing --- vertical vegetation stratification --- gross primary production (GPP) --- light use efficiency --- dense forest --- MODIS --- VPM --- temperature profiles --- humidity profiles --- n/a --- geometric-optical model --- thermal radiation directionality --- quantitative remote sensing inversion --- scale effects --- comprehensive field experiment

Advances in Quantitative Remote Sensing in China – In Memory of Prof. Xiaowen Li

Authors: --- ---
ISBN: 9783038972761 Year: Volume: 2 Pages: 404 DOI: 10.3390/books978-3-03897-277-8 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Geography
Added to DOAB on : 2019-03-08 11:42:05
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Abstract

Quantitative land remote sensing has recently advanced dramatically, particularly in China. It has been largely driven by vast governmental investment, the availability of a huge amount of Chinese satellite data, geospatial information requirements for addressing pressing environmental issues and other societal benefits. Many individuals have also fostered and made great contributions to its development, and Prof. Xiaowen Li was one of these leading figures. This book is published in memory of Prof. Li. The papers collected in this book cover topics from surface reflectance simulation, inversion algorithm and estimation of variables, to applications in optical, thermal, Lidar and microwave remote sensing. The wide range of variables include directional reflectance, chlorophyll fluorescence, aerosol optical depth, incident solar radiation, albedo, surface temperature, upward longwave radiation, leaf area index, fractional vegetation cover, forest biomass, precipitation, evapotranspiration, freeze/thaw snow cover, vegetation productivity, phenology and biodiversity indicators. They clearly reflect the current level of research in this area. This book constitutes an excellent reference suitable for upper-level undergraduate students, graduate students and professionals in remote sensing.

Keywords

evapotranspiration --- Northeast China --- MS–PT algorithm --- spatial-temporal variations --- controlling factors --- potential evapotranspiration --- vegetation remote sensing --- reflectance model --- spectra --- leaf --- copper --- PROSPECT --- leaf area density --- terrestrial LiDAR --- tree canopy --- vertical structure --- voxel --- spatial representativeness --- heterogeneity --- validation --- land-surface temperature products (LSTs) --- observations --- HiWATER --- remote sensing --- spatiotemporal representative --- cost-efficient, sampling design --- heterogeneity --- validation --- FY-3C/MERSI --- GLASS --- Land surface temperature --- Land surface emissivity --- GPP --- SIF --- MuSyQ-GPP algorithm --- BEPS --- vegetation phenology --- Tibetan Plateau --- MODIS --- NDVI --- start of growing season (SOS) --- end of growing season (EOS) --- GLASS LAI time series --- forest disturbance --- disturbance index --- latent heat --- machine learning algorithms --- plant functional type --- high-resolution freeze/thaw --- AMSR2 --- MODIS --- LAI --- ZY-3 MUX --- GF-1 WFV --- HJ-1 CCD --- maize --- PROSPECT-5B+SAILH (PROSAIL) model --- spatial heterogeneity --- variability --- evapotranspiration --- land surface variables --- probability density function --- HiWATER --- spectral --- albedometer --- interference filter --- photoelectric detector --- validation --- land surface albedo --- multi-scale validation --- rugged terrain --- MRT-based model --- MCD43A3 C6 --- precipitation --- statistics methods --- China --- Tibetan Plateau --- South China’s --- drought --- SPI --- TMI data --- crop-growing regions --- downward shortwave radiation --- machine learning --- gradient boosting regression tree --- AVHRR --- CMA --- BRDF --- aerosol --- MODIS --- sunphotometer --- arid/semiarid --- solar-induced chlorophyll fluorescence --- fluorescence quantum efficiency in dark-adapted conditions (FQE) --- SCOPE --- Fraunhofer Line Discrimination (FLD) --- gross primary productivity (GPP) --- longwave upwelling radiation (LWUP) --- Visible Infrared Imaging Radiometer Suite (VIIRS) --- surface radiation budget --- hybrid method --- remote sensing --- leaf age --- leaf spectral properties --- leaf area index --- Cunninghamia --- Chinese fir --- canopy reflectance --- NIR --- EVI2 --- geometric optical radiative transfer (GORT) model --- land surface albedo --- snow-free albedo --- rugged terrain --- topographic effects --- black-sky albedo (BSA) --- GPP --- NPP --- MODIS --- validation --- phenology --- RADARSAT-2 --- rice --- Synthetic Aperture Radar (SAR) --- decision tree --- forest canopy height --- aboveground biomass --- ICESat GLAS --- Landsat --- random forest model --- anisotropic reflectance --- BRDF --- rugged terrain --- solo slope --- composite slope --- surface solar irradiance --- geostationary satellite --- polar orbiting satellite --- LUT method --- SURFRAD --- downward shortwave radiation --- daily average value --- Antarctica --- sinusoidal method --- cloud fraction --- interpolation --- boreal forest --- GPP --- spatiotemporal distribution and variation --- meteorological factors --- phenological parameters --- multisource data fusion --- aerosol retrieval --- urban scale --- vegetation dust-retention --- multiple ecological factors --- geographical detector model --- snow cover --- passive microwave --- FY-3C/MWRI --- algorithmic assessment --- China --- land surface temperature --- satellite observations --- flux measurements --- latitudinal pattern --- land cover change --- fractional vegetation cover (FVC) --- multi-data set --- northern China --- spatio-temporal --- inter-annual variation --- uncertainty --- standard error of the mean --- downscaling --- GPP --- spatial heterogeneity --- remote sensing --- subpixel information --- LiDAR --- point cloud --- leaf --- gap fraction --- 3D reconstruction --- biodiversity --- remote sensing --- species richness --- metric comparison --- metric integration --- leaf area index --- MODIS products --- Landsat --- high resolution --- homogeneous and pure pixel filter --- pixel unmixing --- vertical vegetation stratification --- gross primary production (GPP) --- light use efficiency --- dense forest --- MODIS --- VPM --- temperature profiles --- humidity profiles --- n/a --- geometric-optical model --- thermal radiation directionality --- quantitative remote sensing inversion --- scale effects --- comprehensive field experiment

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
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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

Entropy Applications in Environmental and Water Engineering

Authors: --- ---
ISBN: 9783038972228 Year: Pages: 512 DOI: 10.3390/books978-3-03897-223-5 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Environmental Engineering --- General and Civil Engineering --- Technology (General)
Added to DOAB on : 2019-03-21 15:50:41
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Entropy theory has wide applications to a range of problems in the fields of environmental and water engineering, including river hydraulic geometry, fluvial hydraulics, water monitoring network design, river flow forecasting, floods and droughts, river network analysis, infiltration, soil moisture, sediment transport, surface water and groundwater quality modeling, ecosystems modeling, water distribution networks, environmental and water resources management, and parameter estimation. Such applications have used several different entropy formulations, such as Shannon, Tsallis, Reacutenyi Burg, Kolmogorov, Kapur, configurational, and relative entropies, which can be derived in time, space, or frequency domains. More recently, entropy-based concepts have been coupled with other theories, including copula and wavelets, to study various issues associated with environmental and water resources systems. Recent studies indicate the enormous scope and potential of entropy theory in advancing research in the fields of environmental and water engineering, including establishing and explaining physical connections between theory and reality. The objective of this Special Issue is to provide a platform for compiling important recent and current research on the applications of entropy theory in environmental and water engineering. The contributions to this Special Issue have addressed many aspects associated with entropy theory applications and have shown the enormous scope and potential of entropy theory in advancing research in the fields of environmental and water engineering.

Keywords

complexity --- streamflow --- water level --- composite multiscale sample entropy --- trend --- Poyang Lake basin --- four-parameter exponential gamma distribution --- principle of maximum entropy --- precipitation frequency analysis --- methods of moments --- maximum likelihood estimation --- flood frequency analysis --- generalized gamma (GG) distribution --- principle of maximum entropy (POME) --- entropy theory --- principle of maximum entropy (POME) --- GB2 distribution --- flood frequency analysis --- non-point source pollution --- ANN --- entropy weighting method --- data-scarce --- multi-events --- spatio-temporal variability --- soil water content --- entropy --- arid region --- joint entropy --- NDVI --- temperature --- precipitation --- groundwater depth --- Hei River basin --- turbulent flow --- canopy flow --- randomness --- coherent structures --- Shannon entropy --- Kolmogorov complexity --- entropy --- information transfer --- optimization --- radar --- rainfall network --- water resource carrying capacity --- forewarning model --- entropy of information --- fuzzy analytic hierarchy process --- projection pursuit --- accelerating genetic algorithm --- entropy production --- conditional entropy production --- stochastic processes --- scaling --- climacogram --- turbulence --- water resources vulnerability --- connection entropy --- changing environment --- set pair analysis --- Anhui Province --- cross-entropy minimization --- land suitability evaluation --- spatial optimization --- monthly streamflow forecasting --- Burg entropy --- configurational entropy --- entropy spectral analysis time series analysis --- entropy --- water monitoring --- network design --- hydrometric network --- information theory --- entropy applications --- hydrological risk analysis --- maximum entropy-copula method --- uncertainty --- Loess Plateau --- entropy --- water engineering --- Tsallis entropy --- principle of maximum entropy --- Lagrangian function --- probability distribution function --- flux concentration relation --- uncertainty --- information --- informational entropy --- variation of information --- continuous probability distribution functions --- confidence intervals --- precipitation --- variability --- marginal entropy --- crop yield --- Hexi corridor --- flow duration curve --- Shannon entropy --- entropy parameter --- modeling --- spatial and dynamics characteristic --- hydrology --- tropical rainfall --- statistical scaling --- Tsallis entropy --- multiplicative cascades --- Beta-Lognormal model --- rainfall forecast --- cross entropy --- ant colony fuzzy clustering --- combined forecast --- information entropy --- mutual information --- kernel density estimation --- ENSO --- nonlinear relation --- scaling laws --- power laws --- water distribution networks --- robustness --- flow entropy --- entropy theory --- frequency analysis --- hydrometeorological extremes --- Bayesian technique --- rainfall --- entropy ensemble filter --- ensemble model simulation criterion --- EEF method --- bootstrap aggregating --- bagging --- bootstrap neural networks --- El Niño --- ENSO --- neural network forecast --- sea surface temperature --- tropical Pacific --- entropy --- cross elasticity --- mean annual runoff --- water resources --- resilience --- quaternary catchment --- complement --- substitute --- entropy theory --- complex systems --- hydraulics --- hydrology --- water engineering --- environmental engineering

Learning to Understand Remote Sensing Images

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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
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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

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