2017 Vol. 36, No. 7
Display Method:
2017, 36(7): .
Abstract:
2017, 36(7): 4-14.
doi: 10.1007/s13131-017-1078-z
Abstract:
On the basis of the salinity distribution of isopycnal (σ0=27.2 kg/m3) surface and in salinity minimum, the Antarctic Intermediate Water (AAIW) around South Australia can be classified into five types corresponding to five regions by using in situ CTD observations. Type 1 is the Tasman AAIW, which has consistent hydrographic properties in the South Coral Sea and the North Tasman Sea. Type 2 is the Southern Ocean (SO) AAIW, parallel to and extending from the Subantarctic Front with the freshest and coldest AAIW in the study area. Type 3 is a transition between Type 1 and Type 2. The AAIW transforms from fresh to saline with the latitude declining (equatorward). Type 4, the South Australia AAIW, has relatively uniform AAIW properties due to the semi-enclosed South Australia Basin. Type 5, the Southeast Indian AAIW, progressively becomes more saline through mixing with the subtropical Indian intermediate water from south to north. In addition to the above hydrographic analysis of AAIW, the newest trajectories of Argo (Array for real-time Geostrophic Oceanography) floats were used to constructed the intermediate (1 000 m water depth) current field, which show the major interocean circulation of AAIW in the study area. Finally, a refined schematic of intermediate circulation shows that several currents get together to complete the connection between the Pacific Ocean and the Indian Ocean. They include the South Equatorial Current and the East Australia Current in the Southwest Pacific Ocean, the Tasman Leakage and the Flinders Current in the South Australia Basin, and the extension of Flinders Current in the southeast Indian Ocean.
On the basis of the salinity distribution of isopycnal (σ0=27.2 kg/m3) surface and in salinity minimum, the Antarctic Intermediate Water (AAIW) around South Australia can be classified into five types corresponding to five regions by using in situ CTD observations. Type 1 is the Tasman AAIW, which has consistent hydrographic properties in the South Coral Sea and the North Tasman Sea. Type 2 is the Southern Ocean (SO) AAIW, parallel to and extending from the Subantarctic Front with the freshest and coldest AAIW in the study area. Type 3 is a transition between Type 1 and Type 2. The AAIW transforms from fresh to saline with the latitude declining (equatorward). Type 4, the South Australia AAIW, has relatively uniform AAIW properties due to the semi-enclosed South Australia Basin. Type 5, the Southeast Indian AAIW, progressively becomes more saline through mixing with the subtropical Indian intermediate water from south to north. In addition to the above hydrographic analysis of AAIW, the newest trajectories of Argo (Array for real-time Geostrophic Oceanography) floats were used to constructed the intermediate (1 000 m water depth) current field, which show the major interocean circulation of AAIW in the study area. Finally, a refined schematic of intermediate circulation shows that several currents get together to complete the connection between the Pacific Ocean and the Indian Ocean. They include the South Equatorial Current and the East Australia Current in the Southwest Pacific Ocean, the Tasman Leakage and the Flinders Current in the South Australia Basin, and the extension of Flinders Current in the southeast Indian Ocean.
2017, 36(7): 15-31.
doi: 10.1007/s13131-017-1079-y
Abstract:
Several remotely sensed sea surface salinity (SSS) retrievals with various resolutions from the soil moisture and ocean salinity (SMOS) and Aquarius/SAC-D missions are applied as inputs for retrieving salinity profiles (S) using multilinear regressions. The performance is evaluated using a total root mean square (RMS) error, different error sources, and the feature resolutions of the retrieved S fields. In the mixed layer of the salinity, the SSS-S regression coefficients are uniformly large. The SSS inputs yield smaller RMS errors in the retrieved S with respect to Argo profiles as their spatial or temporal resolution decreases. The projected SSS errors are dominant, and the retrieved S values are more accurate than those of climatology in the tropics except for the tropical Atlantic, where the regression errors are abnormally large. Below that level, because of the influence of a sea level anomaly, the areas of high-accuracy S values shift to higher latitudes except in the high-latitude southern oceans, where the projected SSS errors are abnormally large. A spectral analysis suggests that the CATDS-0.25° results are much noisier and that the BEC-L4-0.25° results are much smoother than those of the other retrievals. Aquarius-CAP-1° generates the smallest RMS errors, and Aquarius-V2-1° performs well in depicting large-scale phenomena. BEC-L3-0.25°, which has small RMS errors and remarkable mesoscale energy, is the best fit for portraying mesoscale features in the SSS and retrieved S fields. The current priority for retrieving S is to improve the reliability of satellite SSS especially at middle and high latitudes, by developing advanced algorithms, combining both sensors, or weighing between accuracy and resolutions.
Several remotely sensed sea surface salinity (SSS) retrievals with various resolutions from the soil moisture and ocean salinity (SMOS) and Aquarius/SAC-D missions are applied as inputs for retrieving salinity profiles (S) using multilinear regressions. The performance is evaluated using a total root mean square (RMS) error, different error sources, and the feature resolutions of the retrieved S fields. In the mixed layer of the salinity, the SSS-S regression coefficients are uniformly large. The SSS inputs yield smaller RMS errors in the retrieved S with respect to Argo profiles as their spatial or temporal resolution decreases. The projected SSS errors are dominant, and the retrieved S values are more accurate than those of climatology in the tropics except for the tropical Atlantic, where the regression errors are abnormally large. Below that level, because of the influence of a sea level anomaly, the areas of high-accuracy S values shift to higher latitudes except in the high-latitude southern oceans, where the projected SSS errors are abnormally large. A spectral analysis suggests that the CATDS-0.25° results are much noisier and that the BEC-L4-0.25° results are much smoother than those of the other retrievals. Aquarius-CAP-1° generates the smallest RMS errors, and Aquarius-V2-1° performs well in depicting large-scale phenomena. BEC-L3-0.25°, which has small RMS errors and remarkable mesoscale energy, is the best fit for portraying mesoscale features in the SSS and retrieved S fields. The current priority for retrieving S is to improve the reliability of satellite SSS especially at middle and high latitudes, by developing advanced algorithms, combining both sensors, or weighing between accuracy and resolutions.
2017, 36(7): 32-38.
doi: 10.1007/s13131-017-1080-5
Abstract:
As rain drops change the radiation and scattering characteristic of the oceans and the atmosphere, the wind speed measuring by spaceborne remote sensors under rainy conditions remains challenging for years. On the basis of a microwave radiometer (RM) loaded on HY-2 satellite, the sensitivity of some brightness temperature (TB) channels to a rain rate and the wind speed are analyzed. Consequently, two TB combinations which show minor sensitivity to rain are obtained. Meanwhile, the sensitivity of the TB combination to the wind speed is even better to the original TB channel. On the basis of these TB combinations, a wind speed retrieval algorithm is developed and compared with WindSat all-weather wind speed product, HY-2 RM original wind speed product and buoy in situ data. The wind speed retrieval accuracy is better than 2 m/s for rainy conditions, which is evidently superior to HY-2 RM original product. The applicability of this new algorithm is testified for the wind speed measuring in rainy weather with HY-2 RM.
As rain drops change the radiation and scattering characteristic of the oceans and the atmosphere, the wind speed measuring by spaceborne remote sensors under rainy conditions remains challenging for years. On the basis of a microwave radiometer (RM) loaded on HY-2 satellite, the sensitivity of some brightness temperature (TB) channels to a rain rate and the wind speed are analyzed. Consequently, two TB combinations which show minor sensitivity to rain are obtained. Meanwhile, the sensitivity of the TB combination to the wind speed is even better to the original TB channel. On the basis of these TB combinations, a wind speed retrieval algorithm is developed and compared with WindSat all-weather wind speed product, HY-2 RM original wind speed product and buoy in situ data. The wind speed retrieval accuracy is better than 2 m/s for rainy conditions, which is evidently superior to HY-2 RM original product. The applicability of this new algorithm is testified for the wind speed measuring in rainy weather with HY-2 RM.
2017, 36(7): 39-47.
doi: 10.1007/s13131-017-1082-3
Abstract:
The weather research and forecasting (WRF) model is a new generation mesoscale numerical model with a fine grid resolution (2 km), making it ideal to simulate the macro- and micro-physical processes and latent heating within Typhoon Molave (2009). Simulations based on a single-moment, six-class microphysical scheme are shown to be reasonable, following verification of results for the typhoon track, wind intensity, precipitation pattern, as well as inner-core thermodynamic and dynamic structures. After calculating latent heating rate, it is concluded that the total latent heat is mainly derived from condensation below the zero degree isotherm, and from deposition above this isotherm. It is revealed that cloud microphysical processes related to graupel are the most important contributors to the total latent heat. Other important latent heat contributors in the simulated Typhoon Molave are condensation of cloud water, deposition of cloud ice, deposition of snow, initiation of cloud ice crystals, deposition of graupel, accretion of cloud water by graupel, evaporation of cloud water and rainwater, sublimation of snow, sublimation of graupel, melting of graupel, and sublimation of cloud ice. In essence, the simulated latent heat profile is similar to ones recorded by the Tropical Rainfall Measuring Mission, although specific values differ slightly.
The weather research and forecasting (WRF) model is a new generation mesoscale numerical model with a fine grid resolution (2 km), making it ideal to simulate the macro- and micro-physical processes and latent heating within Typhoon Molave (2009). Simulations based on a single-moment, six-class microphysical scheme are shown to be reasonable, following verification of results for the typhoon track, wind intensity, precipitation pattern, as well as inner-core thermodynamic and dynamic structures. After calculating latent heating rate, it is concluded that the total latent heat is mainly derived from condensation below the zero degree isotherm, and from deposition above this isotherm. It is revealed that cloud microphysical processes related to graupel are the most important contributors to the total latent heat. Other important latent heat contributors in the simulated Typhoon Molave are condensation of cloud water, deposition of cloud ice, deposition of snow, initiation of cloud ice crystals, deposition of graupel, accretion of cloud water by graupel, evaporation of cloud water and rainwater, sublimation of snow, sublimation of graupel, melting of graupel, and sublimation of cloud ice. In essence, the simulated latent heat profile is similar to ones recorded by the Tropical Rainfall Measuring Mission, although specific values differ slightly.
2017, 36(7): 48-55.
doi: 10.1007/s13131-016-1083-2
Abstract:
As a case study, refined iron (Fe) speciation and quantitative characterization of the reductive reactivity of Fe (Ⅲ) oxides are combined to investigate Fe diagenetic processes in a core sediment from the eutrophic Jiaozhou Bay. The results show that a combination of the two methods can trace Fe transformation in more detail and offer nuanced information on Fe diagenesis from multiple perspectives. This methodology may be used to enhance our understanding of the complex biogeochemical cycling of Fe and sulfur in other studies. Microbial iron reduction (MIR) plays an important role in Fe(Ⅲ) reduction over the upper sediments, while a chemical reduction by reaction with dissolved sulfide is the main process at a deeper (> 12 cm) layer. The most bioavailable amorphous Fe(Ⅲ) oxides [Fe(Ⅲ)am] are the main source of the MIR, followed by poorly crystalline Fe(Ⅲ) oxides [Fe(Ⅲ)pc)] and magnetite. Well crystalline Fe(Ⅲ) oxides [Fe (Ⅲ)wc] have barely participated in Fe diagenesis. The importance of the MIR over the upper layer may be a combined result of the high availability of highly reactive Fe oxides and low availability of labile organic matter, and the latter is also the ultimate factor limiting sulfate reduction and sulfide accumulation in the sediments. Microbially reducible Fe(Ⅲ) [MR-Fe(Ⅲ)], which is quantified by kinetics of Fe(Ⅱ)-oxide reduction, mainly consists of the most reactive Fe(Ⅲ)am and less reactive Fe(Ⅲ)pc. The bulk reactivity of the MR-Fe(Ⅲ) pool is equivalent to aged ferrihydrite, and shows down-core decrease due to preferential reduction of highly reactive phases of Fe oxides.
As a case study, refined iron (Fe) speciation and quantitative characterization of the reductive reactivity of Fe (Ⅲ) oxides are combined to investigate Fe diagenetic processes in a core sediment from the eutrophic Jiaozhou Bay. The results show that a combination of the two methods can trace Fe transformation in more detail and offer nuanced information on Fe diagenesis from multiple perspectives. This methodology may be used to enhance our understanding of the complex biogeochemical cycling of Fe and sulfur in other studies. Microbial iron reduction (MIR) plays an important role in Fe(Ⅲ) reduction over the upper sediments, while a chemical reduction by reaction with dissolved sulfide is the main process at a deeper (> 12 cm) layer. The most bioavailable amorphous Fe(Ⅲ) oxides [Fe(Ⅲ)am] are the main source of the MIR, followed by poorly crystalline Fe(Ⅲ) oxides [Fe(Ⅲ)pc)] and magnetite. Well crystalline Fe(Ⅲ) oxides [Fe (Ⅲ)wc] have barely participated in Fe diagenesis. The importance of the MIR over the upper layer may be a combined result of the high availability of highly reactive Fe oxides and low availability of labile organic matter, and the latter is also the ultimate factor limiting sulfate reduction and sulfide accumulation in the sediments. Microbially reducible Fe(Ⅲ) [MR-Fe(Ⅲ)], which is quantified by kinetics of Fe(Ⅱ)-oxide reduction, mainly consists of the most reactive Fe(Ⅲ)am and less reactive Fe(Ⅲ)pc. The bulk reactivity of the MR-Fe(Ⅲ) pool is equivalent to aged ferrihydrite, and shows down-core decrease due to preferential reduction of highly reactive phases of Fe oxides.
2017, 36(7): 56-65.
doi: 10.1007/s13131-017-1084-1
Abstract:
In order to predict the bottom backscattering strength more accurately, the stratified structure of the seafloor is considered. The seafloor is viewed as an elastic half-space basement covered by a fluid sediment layer with finite thickness. On the basis of calculating acoustic field in the water, the sediment layer, and the basement, four kinds of scattering mechanisms are taken into account, including roughness scattering from the water-sediment interface, volume scattering from the sediment layer, roughness scattering from the sediment-basement interface, and volume scattering from the basement. Then a backscattering model for a stratified seafloor applying to low frequency (0.1–10 kHz) is established. The simulation results show that the roughness scattering from the sediment-basement interface and the volume scattering from the basement are more prominent at relative low frequency (below 1.0 kHz). While with the increase of the frequency, the contribution of them to total bottom scattering gradually becomes weak. And the results ultimately approach to the predictions of the high-frequency (10–100 kHz) bottom scattering model. When the sound speed and attenuation of the shear wave in the basement gradually decrease, the prediction of the model tends to that of the full fluid model, which validates the backscattering model for the stratified seafloor in another aspect.
In order to predict the bottom backscattering strength more accurately, the stratified structure of the seafloor is considered. The seafloor is viewed as an elastic half-space basement covered by a fluid sediment layer with finite thickness. On the basis of calculating acoustic field in the water, the sediment layer, and the basement, four kinds of scattering mechanisms are taken into account, including roughness scattering from the water-sediment interface, volume scattering from the sediment layer, roughness scattering from the sediment-basement interface, and volume scattering from the basement. Then a backscattering model for a stratified seafloor applying to low frequency (0.1–10 kHz) is established. The simulation results show that the roughness scattering from the sediment-basement interface and the volume scattering from the basement are more prominent at relative low frequency (below 1.0 kHz). While with the increase of the frequency, the contribution of them to total bottom scattering gradually becomes weak. And the results ultimately approach to the predictions of the high-frequency (10–100 kHz) bottom scattering model. When the sound speed and attenuation of the shear wave in the basement gradually decrease, the prediction of the model tends to that of the full fluid model, which validates the backscattering model for the stratified seafloor in another aspect.
2017, 36(7): 66-76.
doi: 10.1007/s13131-017-1085-0
Abstract:
Hydrothermal plumes released from the eruption of sea floor hydrothermal fluids contain large amounts of ore-forming materials. They precipitate within certain distances from the hydrothermal vent. Six surficial sediment samples from the Southwest Indian Ridge (SWIR) were analyzed by a portable X-ray fluorescence (PXRF) analyzer on board to find a favorable method fast and efficient enough for sea floor sulfide sediment geochemical exploration. These sediments were sampled near, at a moderate distance from, or far away from hydrothermal vents. The results demonstrate that the PXRF is effective in determining the enrichment characteristics of the ore-forming elements in the calcareous sediments from the mid-ocean ridge. Sediment samples (>40 mesh) have high levels of elemental copper, zinc, iron, and manganese, and levels of these elements in sediments finer than 40 mesh are lower and relatively stable. This may be due to relatively high levels of basalt debris/glass in the coarse sediments, which are consistent with the results obtained by microscopic observation. The results also show clear zoning of elements copper, zinc, arsenic, iron, and manganese in the surficial sediments around the hydrothermal vent. Sediments near the vent show relatively high content of the ore-forming elements and either high ratios of copper to iron content and zinc to iron content or high ratios of copper to manganese content and zinc to manganese content. These findings show that the content of the ore-forming elements in the sediments around hydrothermal vents are mainly influenced by the distance of sediments to the vent, rather than grain size. In this way, the PXRF analysis of surface sediment geochemistry is found to satisfy the requirements of recognition geochemical anomaly in mid-ocean ridge sediments. Sediments with diameters finer than 40 mesh should be used as analytical samples in the geochemical exploration for hydrothermal vents on mid-oceanic ridges. The results concerning copper, zinc, arsenic, iron, and manganese and their ratio features can be used as indicators in sediment geochemical exploration of seafloor sulfides.
Hydrothermal plumes released from the eruption of sea floor hydrothermal fluids contain large amounts of ore-forming materials. They precipitate within certain distances from the hydrothermal vent. Six surficial sediment samples from the Southwest Indian Ridge (SWIR) were analyzed by a portable X-ray fluorescence (PXRF) analyzer on board to find a favorable method fast and efficient enough for sea floor sulfide sediment geochemical exploration. These sediments were sampled near, at a moderate distance from, or far away from hydrothermal vents. The results demonstrate that the PXRF is effective in determining the enrichment characteristics of the ore-forming elements in the calcareous sediments from the mid-ocean ridge. Sediment samples (>40 mesh) have high levels of elemental copper, zinc, iron, and manganese, and levels of these elements in sediments finer than 40 mesh are lower and relatively stable. This may be due to relatively high levels of basalt debris/glass in the coarse sediments, which are consistent with the results obtained by microscopic observation. The results also show clear zoning of elements copper, zinc, arsenic, iron, and manganese in the surficial sediments around the hydrothermal vent. Sediments near the vent show relatively high content of the ore-forming elements and either high ratios of copper to iron content and zinc to iron content or high ratios of copper to manganese content and zinc to manganese content. These findings show that the content of the ore-forming elements in the sediments around hydrothermal vents are mainly influenced by the distance of sediments to the vent, rather than grain size. In this way, the PXRF analysis of surface sediment geochemistry is found to satisfy the requirements of recognition geochemical anomaly in mid-ocean ridge sediments. Sediments with diameters finer than 40 mesh should be used as analytical samples in the geochemical exploration for hydrothermal vents on mid-oceanic ridges. The results concerning copper, zinc, arsenic, iron, and manganese and their ratio features can be used as indicators in sediment geochemical exploration of seafloor sulfides.
2017, 36(7): 77-85.
doi: 10.1007/s13131-017-1000-8
Abstract:
The difference analysis of physical-mechanical properties of muddy sediments is made in the central South Yellow Sea and the Zhe-Min (Zhejiang Province to Fujian Province of China) coastal area. The results show that sediments in the two regions are both dominated by mud. There are perfect negative power function correlations between the water content and the density, the compression coefficient and the compression modulus; a good positive power function correlation between the liquid limit and the plastic limit, a perfect positive linear correlation between the water content and the void ratio, and a perfect polynomial function correlation between the miniature vane shear strength and the pocket penetration resistance. In general, compared with sediments in the Zhe-Min coastal area, sediments in the central South Yellow Sea possess high water content, high void ratio, low density, high plasticity, high compressibility, low shear strength. The causes of the differences between physical-mechanical properties of sediments are analyzed from the topographic features, material sources, hydrodynamic conditions, deposition rate, and material composition. Compared with the Zhe-Min coastal area, the central South Yellow Sea is far from the Mainland and low-lying; has poor hydrodynamic condition; the materials diffused to the area are less and dominated by fine clay, have the high content of smectite and organic matters. These factors lead to sediments of the central South Yellow Sea has the higher water content, the higher plasticity, the lower density, and the lower strength than sediments in the Zhe-Min coastal area.
The difference analysis of physical-mechanical properties of muddy sediments is made in the central South Yellow Sea and the Zhe-Min (Zhejiang Province to Fujian Province of China) coastal area. The results show that sediments in the two regions are both dominated by mud. There are perfect negative power function correlations between the water content and the density, the compression coefficient and the compression modulus; a good positive power function correlation between the liquid limit and the plastic limit, a perfect positive linear correlation between the water content and the void ratio, and a perfect polynomial function correlation between the miniature vane shear strength and the pocket penetration resistance. In general, compared with sediments in the Zhe-Min coastal area, sediments in the central South Yellow Sea possess high water content, high void ratio, low density, high plasticity, high compressibility, low shear strength. The causes of the differences between physical-mechanical properties of sediments are analyzed from the topographic features, material sources, hydrodynamic conditions, deposition rate, and material composition. Compared with the Zhe-Min coastal area, the central South Yellow Sea is far from the Mainland and low-lying; has poor hydrodynamic condition; the materials diffused to the area are less and dominated by fine clay, have the high content of smectite and organic matters. These factors lead to sediments of the central South Yellow Sea has the higher water content, the higher plasticity, the lower density, and the lower strength than sediments in the Zhe-Min coastal area.
2017, 36(7): 86-94.
doi: 10.1007/s13131-017-1086-z
Abstract:
Oil spills pose a major threat to ocean ecosystems and their health. Synthetic aperture radar (SAR) sensors can detect oil spills on the sea surface. These oil spills appear as dark spots in SAR images. However, dark formations can be caused by a number of phenomena. It is aimed to distinguishing oil spills or look-alike objects. A novel method based on a bidimensional empirical mode decomposition is proposed. The selected dark formations are first decomposed into several bidimensional intrinsic mode functions and the residue. Subsequently, 64 dimension feature sets are calculated using the Hilbert spectral analysis and five new features are extracted with a relief algorithm. Mahalanobis distances are then used for classification. Three data sets containing oil spills or look-alikes are used to test the accuracy rate of the method. The accuracy rate is more than 90%. The experimental results demonstrate that the novel method can detect oil spills validly and accurately.
Oil spills pose a major threat to ocean ecosystems and their health. Synthetic aperture radar (SAR) sensors can detect oil spills on the sea surface. These oil spills appear as dark spots in SAR images. However, dark formations can be caused by a number of phenomena. It is aimed to distinguishing oil spills or look-alike objects. A novel method based on a bidimensional empirical mode decomposition is proposed. The selected dark formations are first decomposed into several bidimensional intrinsic mode functions and the residue. Subsequently, 64 dimension feature sets are calculated using the Hilbert spectral analysis and five new features are extracted with a relief algorithm. Mahalanobis distances are then used for classification. Three data sets containing oil spills or look-alikes are used to test the accuracy rate of the method. The accuracy rate is more than 90%. The experimental results demonstrate that the novel method can detect oil spills validly and accurately.
2017, 36(7): 95-101.
doi: 10.1007/s13131-017-1089-9
Abstract:
The purpose is to study the accuracy of ocean wave parameters retrieved from C-band VV-polarization Sentinel-1 Synthetic Aperture Radar (SAR) images, including both significant wave height (SWH) and mean wave period (MWP), which are both calculated from a SAR-derived wave spectrum. The wind direction from in situ buoys is used and then the wind speed is retrieved by using a new C-band geophysical model function (GMF) model, denoted as C-SARMOD. Continuously, an algorithm parameterized first-guess spectra method (PFSM) is employed to retrieve the SWH and the MWP by using the SAR-derived wind speed. Forty–five VV-polarization Sentinel-1 SAR images are collected, which cover the in situ buoys around US coastal waters. A total of 52 subscenes are selected from those images. The retrieval results are compared with the measurements from in situ buoys. The comparison performs good for a wind retrieval, showing a 1.6 m/s standard deviation (STD) of the wind speed, while a 0.54 m STD of the SWH and a 2.14 s STD of the MWP are exhibited with an acceptable error. Additional 50 images taken in China’s seas were also implemented by using the algorithm PFSM, showing a 0.67 m STD of the SWH and a 2.21 s STD of the MWP compared with European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis grids wave data. The results indicate that the algorithm PFSM works for the wave retrieval from VV-polarization Sentinel-1 SAR image through SAR-derived wind speed by using the new GMF C-SARMOD.
The purpose is to study the accuracy of ocean wave parameters retrieved from C-band VV-polarization Sentinel-1 Synthetic Aperture Radar (SAR) images, including both significant wave height (SWH) and mean wave period (MWP), which are both calculated from a SAR-derived wave spectrum. The wind direction from in situ buoys is used and then the wind speed is retrieved by using a new C-band geophysical model function (GMF) model, denoted as C-SARMOD. Continuously, an algorithm parameterized first-guess spectra method (PFSM) is employed to retrieve the SWH and the MWP by using the SAR-derived wind speed. Forty–five VV-polarization Sentinel-1 SAR images are collected, which cover the in situ buoys around US coastal waters. A total of 52 subscenes are selected from those images. The retrieval results are compared with the measurements from in situ buoys. The comparison performs good for a wind retrieval, showing a 1.6 m/s standard deviation (STD) of the wind speed, while a 0.54 m STD of the SWH and a 2.14 s STD of the MWP are exhibited with an acceptable error. Additional 50 images taken in China’s seas were also implemented by using the algorithm PFSM, showing a 0.67 m STD of the SWH and a 2.21 s STD of the MWP compared with European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis grids wave data. The results indicate that the algorithm PFSM works for the wave retrieval from VV-polarization Sentinel-1 SAR image through SAR-derived wind speed by using the new GMF C-SARMOD.
2017, 36(7): 102-109.
doi: 10.1007/s13131-017-1088-x
Abstract:
A spatial resolution effect of remote sensing bathymetry is an important scientific problem. The in situ measured water depth data and images of Dongdao Island are used to study the effect of water depth inversion from different spatial resolution remote sensing images. The research experiments are divided into five groups including QuickBird and WorldView-2 remote sensing images with their original spatial resolution (2.4/2.0 m) and four kinds of reducing spatial resolution (4, 8, 16 and 32 m), and the water depth control and checking points are set up to carry out remote sensing water depth inversion. The experiment results indicate that the accuracy of the water depth remote sensing inversion increases first as the spatial resolution decreases from 2.4/2.0 to 4, 8 and 16 m. And then the accuracy decreases along with the decreasing spatial resolution. When the spatial resolution of the image is 16 m, the inversion error is minimum. In this case, when the spatial resolution of the remote sensing image is 16 m, the mean relative errors (MRE) of QuickBird and WorldView-2 bathymetry are 21.2% and 13.1%, compared with the maximum error are decreased by 14.7% and 2.9% respectively; the mean absolute errors (MAE) are 2.0 and 1.4 m, compared with the maximum are decreased by 1.0 and 0.5 m respectively. The results provide an important reference for the selection of remote sensing data in the study and application of the remote sensing bathymetry.
A spatial resolution effect of remote sensing bathymetry is an important scientific problem. The in situ measured water depth data and images of Dongdao Island are used to study the effect of water depth inversion from different spatial resolution remote sensing images. The research experiments are divided into five groups including QuickBird and WorldView-2 remote sensing images with their original spatial resolution (2.4/2.0 m) and four kinds of reducing spatial resolution (4, 8, 16 and 32 m), and the water depth control and checking points are set up to carry out remote sensing water depth inversion. The experiment results indicate that the accuracy of the water depth remote sensing inversion increases first as the spatial resolution decreases from 2.4/2.0 to 4, 8 and 16 m. And then the accuracy decreases along with the decreasing spatial resolution. When the spatial resolution of the image is 16 m, the inversion error is minimum. In this case, when the spatial resolution of the remote sensing image is 16 m, the mean relative errors (MRE) of QuickBird and WorldView-2 bathymetry are 21.2% and 13.1%, compared with the maximum error are decreased by 14.7% and 2.9% respectively; the mean absolute errors (MAE) are 2.0 and 1.4 m, compared with the maximum are decreased by 1.0 and 0.5 m respectively. The results provide an important reference for the selection of remote sensing data in the study and application of the remote sensing bathymetry.
2017, 36(7): 110-118.
doi: 10.1007/s13131-017-1087-y
Abstract:
Time-series InSAR analysis (e.g., permanent scatterers (PSInSAR)) has been proven as an effective technology in monitoring ground deformation over urban areas. However, it is a big challenge to apply this technology in coastal regions due to the lack of man-made targets. An distributed scatterers interferometric synthetic aperture radar (DSInSAR) is developed to solve the problem of insufficient samples and low reliability in monitoring coastal lowland subsidence, by applying a spatially adaptive filter and an eigendecomposition algorithm to estimating the optimal phase of statistically homogeneous distributed scatterers (DSs). Twenty-four scenes of COSMO-SkyMed images acquired between 2013 and 2015 are used to retrieve the land subsidence over the Shangyu District on south coast of the Hangzhou Bay, Zhejiang Province, China. The spatial pattern of the land subsidence obtained by the PS-InSAR and the DSInSAR coincides with each other, but the density of the DSs is three point five times higher than the permanent scatterers (PSs). Validated by precise levelling data over the same period, the DSInSAR method achieves an accuracy of ±5.0 mm/a which is superior to the PS-InSAR with ±5.5 mm/a. The land subsidence in the Shangyu District is mainly distributed in the urban areas, industrial towns and land reclamation zones, with a maximum subsidence rate –30.2 mm/a. The analysis of geological data, field investigation and historical reclamation data indicates that human activities and natural compaction of reclamation material are major causes of the detected land subsidence. The results demonstrate that the DSInSAR method has a great potential in monitoring the coastal lowland subsidence and can be used to further investigate subsidence-related environmental issues in coastal regions.
Time-series InSAR analysis (e.g., permanent scatterers (PSInSAR)) has been proven as an effective technology in monitoring ground deformation over urban areas. However, it is a big challenge to apply this technology in coastal regions due to the lack of man-made targets. An distributed scatterers interferometric synthetic aperture radar (DSInSAR) is developed to solve the problem of insufficient samples and low reliability in monitoring coastal lowland subsidence, by applying a spatially adaptive filter and an eigendecomposition algorithm to estimating the optimal phase of statistically homogeneous distributed scatterers (DSs). Twenty-four scenes of COSMO-SkyMed images acquired between 2013 and 2015 are used to retrieve the land subsidence over the Shangyu District on south coast of the Hangzhou Bay, Zhejiang Province, China. The spatial pattern of the land subsidence obtained by the PS-InSAR and the DSInSAR coincides with each other, but the density of the DSs is three point five times higher than the permanent scatterers (PSs). Validated by precise levelling data over the same period, the DSInSAR method achieves an accuracy of ±5.0 mm/a which is superior to the PS-InSAR with ±5.5 mm/a. The land subsidence in the Shangyu District is mainly distributed in the urban areas, industrial towns and land reclamation zones, with a maximum subsidence rate –30.2 mm/a. The analysis of geological data, field investigation and historical reclamation data indicates that human activities and natural compaction of reclamation material are major causes of the detected land subsidence. The results demonstrate that the DSInSAR method has a great potential in monitoring the coastal lowland subsidence and can be used to further investigate subsidence-related environmental issues in coastal regions.
