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Around 10% of the global population lives in the world’s coastal zones, mostly concentrated in the world’s largest megacities. In many regions, the population is exposed to a variety of natural hazards and space-based observations. This Special Issue will focus on the usage of remote sensing alone or in synergy with in situ measurments and modeling tools to provide precise and systematic information about processes acting in the world’s coastal zones.
Research & information: general --- ACOLITE --- coastal waters --- atmospheric correction --- time-series --- management --- Sentinel-2 --- radon transform --- remote sensing --- bathymetry inversion --- multi-scale monitoring --- image augmentation --- phytoplankton remote sensing --- coastal ocean --- red tides --- black pixel assumption --- satellite --- sediment transport --- coastal geomorphology --- ocean color --- GOCI --- VIIRS --- turbid waters --- satellite-derived bathymetry --- Copernicus programme --- multi-temporal approach --- lidar --- turbidity --- coastal upwelling --- wind forcing --- river plume --- MODIS --- Arctic Ocean --- hurricanes --- water quality --- Puerto Rico --- harmful algal blooms --- Chattonella spp. --- Skeletonema spp. --- backscattering --- Ariake Sea --- chlorophyll-a variability --- spring–neap tides --- MODIS-Aqua --- total suspended sediment --- river discharge --- band registration --- morphological registration --- multispectral camera --- Micasense Rededge-M --- Pearl River estuary --- diffuse attenuation coefficient --- S-EOF --- land subsidence --- multi-temporal SAR interferometry --- sea-surface height --- relative sea level change --- satellite altimetry data --- GNSS --- coastal urban centers --- natural protected areas --- climate change impact --- physics-based inversion method --- ocean surface circulation --- high frequency radar --- self-organizing map --- empirical orthogonal function --- neural networks --- synoptic characteristics --- wave radar --- sea waves --- model data --- Mediterranean sea --- small river plume --- aerial drone --- coastal processes --- frontal zones --- internal waves --- along-track interferometric synthetic aperture radar (ATI-SAR) --- current line-of-sight (LOS) velocity --- azimuth ambiguity --- baseline-to-platform speed ratio estimation --- storm surge --- coastal flooding --- marine storms --- natural hazards --- steric-effect --- satellite altimetry --- ADG/CDOM colored dissolved organic matter --- Sentinel 3 --- southwestern Puerto Rico --- ocean tidal backwater --- stage–discharge relation --- ocean tide model --- Mekong Delta --- suspended particulate matter --- ocean color data --- satellite remote sensing --- in situ measurements --- C2RCC --- Landsat-8 OLI --- Sentinel-2 MSI --- Mzymta River --- Black Sea --- MUR SST --- SST fronts --- Inner Sea of Chiloé --- northern Patagonia --- suspended sediment --- Typhoon Soudelor --- spatial–temporal distribution --- HF marine radars --- wave energy --- ACOLITE --- coastal waters --- atmospheric correction --- time-series --- management --- Sentinel-2 --- radon transform --- remote sensing --- bathymetry inversion --- multi-scale monitoring --- image augmentation --- phytoplankton remote sensing --- coastal ocean --- red tides --- black pixel assumption --- satellite --- sediment transport --- coastal geomorphology --- ocean color --- GOCI --- VIIRS --- turbid waters --- satellite-derived bathymetry --- Copernicus programme --- multi-temporal approach --- lidar --- turbidity --- coastal upwelling --- wind forcing --- river plume --- MODIS --- Arctic Ocean --- hurricanes --- water quality --- Puerto Rico --- harmful algal blooms --- Chattonella spp. --- Skeletonema spp. --- backscattering --- Ariake Sea --- chlorophyll-a variability --- spring–neap tides --- MODIS-Aqua --- total suspended sediment --- river discharge --- band registration --- morphological registration --- multispectral camera --- Micasense Rededge-M --- Pearl River estuary --- diffuse attenuation coefficient --- S-EOF --- land subsidence --- multi-temporal SAR interferometry --- sea-surface height --- relative sea level change --- satellite altimetry data --- GNSS --- coastal urban centers --- natural protected areas --- climate change impact --- physics-based inversion method --- ocean surface circulation --- high frequency radar --- self-organizing map --- empirical orthogonal function --- neural networks --- synoptic characteristics --- wave radar --- sea waves --- model data --- Mediterranean sea --- small river plume --- aerial drone --- coastal processes --- frontal zones --- internal waves --- along-track interferometric synthetic aperture radar (ATI-SAR) --- current line-of-sight (LOS) velocity --- azimuth ambiguity --- baseline-to-platform speed ratio estimation --- storm surge --- coastal flooding --- marine storms --- natural hazards --- steric-effect --- satellite altimetry --- ADG/CDOM colored dissolved organic matter --- Sentinel 3 --- southwestern Puerto Rico --- ocean tidal backwater --- stage–discharge relation --- ocean tide model --- Mekong Delta --- suspended particulate matter --- ocean color data --- satellite remote sensing --- in situ measurements --- C2RCC --- Landsat-8 OLI --- Sentinel-2 MSI --- Mzymta River --- Black Sea --- MUR SST --- SST fronts --- Inner Sea of Chiloé --- northern Patagonia --- suspended sediment --- Typhoon Soudelor --- spatial–temporal distribution --- HF marine radars --- wave energy
Choose an application
Around 10% of the global population lives in the world’s coastal zones, mostly concentrated in the world’s largest megacities. In many regions, the population is exposed to a variety of natural hazards and space-based observations. This Special Issue will focus on the usage of remote sensing alone or in synergy with in situ measurments and modeling tools to provide precise and systematic information about processes acting in the world’s coastal zones.
Research & information: general --- ACOLITE --- coastal waters --- atmospheric correction --- time-series --- management --- Sentinel-2 --- radon transform --- remote sensing --- bathymetry inversion --- multi-scale monitoring --- image augmentation --- phytoplankton remote sensing --- coastal ocean --- red tides --- black pixel assumption --- satellite --- sediment transport --- coastal geomorphology --- ocean color --- GOCI --- VIIRS --- turbid waters --- satellite-derived bathymetry --- Copernicus programme --- multi-temporal approach --- lidar --- turbidity --- coastal upwelling --- wind forcing --- river plume --- MODIS --- Arctic Ocean --- hurricanes --- water quality --- Puerto Rico --- harmful algal blooms --- Chattonella spp. --- Skeletonema spp. --- backscattering --- Ariake Sea --- chlorophyll-a variability --- spring–neap tides --- MODIS-Aqua --- total suspended sediment --- river discharge --- band registration --- morphological registration --- multispectral camera --- Micasense Rededge-M --- Pearl River estuary --- diffuse attenuation coefficient --- S-EOF --- land subsidence --- multi-temporal SAR interferometry --- sea-surface height --- relative sea level change --- satellite altimetry data --- GNSS --- coastal urban centers --- natural protected areas --- climate change impact --- physics-based inversion method --- ocean surface circulation --- high frequency radar --- self-organizing map --- empirical orthogonal function --- neural networks --- synoptic characteristics --- wave radar --- sea waves --- model data --- Mediterranean sea --- small river plume --- aerial drone --- coastal processes --- frontal zones --- internal waves --- along-track interferometric synthetic aperture radar (ATI-SAR) --- current line-of-sight (LOS) velocity --- azimuth ambiguity --- baseline-to-platform speed ratio estimation --- storm surge --- coastal flooding --- marine storms --- natural hazards --- steric-effect --- satellite altimetry --- ADG/CDOM colored dissolved organic matter --- Sentinel 3 --- southwestern Puerto Rico --- ocean tidal backwater --- stage–discharge relation --- ocean tide model --- Mekong Delta --- suspended particulate matter --- ocean color data --- satellite remote sensing --- in situ measurements --- C2RCC --- Landsat-8 OLI --- Sentinel-2 MSI --- Mzymta River --- Black Sea --- MUR SST --- SST fronts --- Inner Sea of Chiloé --- northern Patagonia --- suspended sediment --- Typhoon Soudelor --- spatial–temporal distribution --- HF marine radars --- wave energy
Choose an application
Around 10% of the global population lives in the world’s coastal zones, mostly concentrated in the world’s largest megacities. In many regions, the population is exposed to a variety of natural hazards and space-based observations. This Special Issue will focus on the usage of remote sensing alone or in synergy with in situ measurments and modeling tools to provide precise and systematic information about processes acting in the world’s coastal zones.
ACOLITE --- coastal waters --- atmospheric correction --- time-series --- management --- Sentinel-2 --- radon transform --- remote sensing --- bathymetry inversion --- multi-scale monitoring --- image augmentation --- phytoplankton remote sensing --- coastal ocean --- red tides --- black pixel assumption --- satellite --- sediment transport --- coastal geomorphology --- ocean color --- GOCI --- VIIRS --- turbid waters --- satellite-derived bathymetry --- Copernicus programme --- multi-temporal approach --- lidar --- turbidity --- coastal upwelling --- wind forcing --- river plume --- MODIS --- Arctic Ocean --- hurricanes --- water quality --- Puerto Rico --- harmful algal blooms --- Chattonella spp. --- Skeletonema spp. --- backscattering --- Ariake Sea --- chlorophyll-a variability --- spring–neap tides --- MODIS-Aqua --- total suspended sediment --- river discharge --- band registration --- morphological registration --- multispectral camera --- Micasense Rededge-M --- Pearl River estuary --- diffuse attenuation coefficient --- S-EOF --- land subsidence --- multi-temporal SAR interferometry --- sea-surface height --- relative sea level change --- satellite altimetry data --- GNSS --- coastal urban centers --- natural protected areas --- climate change impact --- physics-based inversion method --- ocean surface circulation --- high frequency radar --- self-organizing map --- empirical orthogonal function --- neural networks --- synoptic characteristics --- wave radar --- sea waves --- model data --- Mediterranean sea --- small river plume --- aerial drone --- coastal processes --- frontal zones --- internal waves --- along-track interferometric synthetic aperture radar (ATI-SAR) --- current line-of-sight (LOS) velocity --- azimuth ambiguity --- baseline-to-platform speed ratio estimation --- storm surge --- coastal flooding --- marine storms --- natural hazards --- steric-effect --- satellite altimetry --- ADG/CDOM colored dissolved organic matter --- Sentinel 3 --- southwestern Puerto Rico --- ocean tidal backwater --- stage–discharge relation --- ocean tide model --- Mekong Delta --- suspended particulate matter --- ocean color data --- satellite remote sensing --- in situ measurements --- C2RCC --- Landsat-8 OLI --- Sentinel-2 MSI --- Mzymta River --- Black Sea --- MUR SST --- SST fronts --- Inner Sea of Chiloé --- northern Patagonia --- suspended sediment --- Typhoon Soudelor --- spatial–temporal distribution --- HF marine radars --- wave energy
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This book focuses on the fundamental and applied research of the non-destructive estimation and diagnosis of crop leaf and plant nitrogen status and in-season nitrogen management strategies based on leaf sensors, proximal canopy sensors, unmanned aerial vehicle remote sensing, manned aerial remote sensing and satellite remote sensing technologies. Statistical and machine learning methods are used to predict plant-nitrogen-related parameters with sensor data or sensor data together with soil, landscape, weather and/or management information. Different sensing technologies or different modelling approaches are compared and evaluated. Strategies are developed to use crop sensing data for in-season nitrogen recommendations to improve nitrogen use efficiency and protect the environment.
Technology: general issues --- History of engineering & technology --- Environmental science, engineering & technology --- UAS --- multiple sensors --- vegetation index --- leaf nitrogen accumulation --- plant nitrogen accumulation --- pasture quality --- airborne hyperspectral imaging --- random forest regression --- sun-induced chlorophyll fluorescence (SIF) --- SIF yield indices --- upward --- downward --- leaf nitrogen concentration (LNC) --- wheat (Triticum aestivum L.) --- laser-induced fluorescence --- leaf nitrogen concentration --- back-propagation neural network --- principal component analysis --- fluorescence characteristics --- canopy nitrogen density --- radiative transfer model --- hyperspectral --- winter wheat --- flooded rice --- pig slurry --- aerial remote sensing --- vegetation indices --- N recommendation approach --- Mediterranean conditions --- nitrogen --- vertical distribution --- plant geometry --- remote sensing --- maize --- UAV --- multispectral imagery --- LNC --- non-parametric regression --- red-edge --- NDRE --- dynamic change model --- sigmoid curve --- grain yield prediction --- leaf chlorophyll content --- red-edge reflectance --- spectral index --- precision N fertilization --- chlorophyll meter --- NDVI --- NNI --- canopy reflectance sensing --- N mineralization --- farmyard manures --- Triticum aestivum --- discrete wavelet transform --- partial least squares --- hyper-spectra --- rice --- nitrogen management --- reflectance index --- multiple variable linear regression --- Lasso model --- Multiplex®3 sensor --- nitrogen balance index --- nitrogen nutrition index --- nitrogen status diagnosis --- precision nitrogen management --- terrestrial laser scanning --- spectrometer --- plant height --- biomass --- nitrogen concentration --- precision agriculture --- unmanned aerial vehicle (UAV) --- digital camera --- leaf chlorophyll concentration --- portable chlorophyll meter --- crop --- PROSPECT-D --- sensitivity analysis --- UAV multispectral imagery --- spectral vegetation indices --- machine learning --- plant nutrition --- canopy spectrum --- non-destructive nitrogen status diagnosis --- drone --- multispectral camera --- SPAD --- smartphone photography --- fixed-wing UAV remote sensing --- random forest --- canopy reflectance --- crop N status --- Capsicum annuum --- proximal optical sensors --- Dualex sensor --- leaf position --- proximal sensing --- cross-validation --- feature selection --- hyperparameter tuning --- image processing --- image segmentation --- nitrogen fertilizer recommendation --- supervised regression --- RapidSCAN sensor --- nitrogen recommendation algorithm --- in-season nitrogen management --- nitrogen use efficiency --- yield potential --- yield responsiveness --- standard normal variate (SNV) --- continuous wavelet transform (CWT) --- wavelet features optimization --- competitive adaptive reweighted sampling (CARS) --- partial least square (PLS) --- grapevine --- hyperparameter optimization --- multispectral imaging --- precision viticulture --- RGB --- multispectral --- coverage adjusted spectral index --- vegetation coverage --- random frog algorithm --- active canopy sensing --- integrated sensing system --- discrete NIR spectral band data --- soil total nitrogen concentration --- moisture absorption correction index --- particle size correction index --- coupled elimination
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