Unmanned aerial vehicle remotely sensed datasets, a reference dataset for coastal topography change and shoreline analysis

To analyze tendency of temporal and spatial change of coast using long-term topography and shoreline change data is important. In this study, high-resolution digital elevation model and orthorectified image data were generated using rotary-wing UAV(unmanned aerial vehicle) system for coastal topography and shoreline change analysis. The UAV system has advantage of low cost and high efficiency compared to satellite remote sensing platform so UAV system easily acquire time series image data. The spatial resolution of generated digital elevation model and orthorectified images are very high, in centimeter. Therefore, the above image data can be used in various fields of remote sensing and geography such as detailed coastal topography

Red tide dataset in the waters around the Korean Peninsula

Red tide blooms are increasing worldwide. Since 1995, Margalefidium polykrikoides blooms have occurred frequently in the waters around the Korean Peninsula. These blooms generally appear first on the South Sea of Korea in summer. When they occur on a large scale, they extend to the East Sea of Korea and the West Sea of Korea, causing great damage to fisheries and marine ecosystems. Harmless red tide can also adversely affect the environment of the waters by causing oxygen depletion in waters when occurring at high density. Currently, the National Institute of Fisheries Science (NIFS) is providing the daily red tide report based on M. polykrikoides red tide species. This report contains red tide species, location, and cell abundance information, but is limited to use as cell abundance data based on exact location. In addition, the waters around the Korean peninsula have different characteristics, so that the optical characteristics and seawater environment are different for each water. In the East Sea in Aug. 2013, the West Sea in Aug. 2016, the South Sea in Aug. 2018, and the South Sea in Aug. and Sep. 2019, during red tide season, dataset were obtained for red tide cell abundance, spectrum, chlorophyll concentration, and suspended particulate matter concentration. Noctiluca scintillans species were observed in the field survey conducted in 2016, and M. polykrikoides was mainly found in the other field surveys. Location-based red tide cell abundance data and seawater environment information obtained during red tide occurrence will be useful data for the construction of red tide warning system to reduce damage due to red tide blooms

Synergistic Effect of Multi-Sensor Data on the Detection of Margalefidinium polykrikoides in the South Sea of Korea

Since 1995, Margalefidinium polykrikoides blooms have occurred frequently in the waters around the Korean peninsula. In the South Sea of Korea (SSK), large-scale M. polykrikoides blooms form offshore and are often transported to the coast, where they gradually accumulate. The objective of this study was to investigate the synergistic effect of multi-sensor data for identifying M. polykrikoides blooms in the SSK from July 2018 to August 2018. We found that the Spectral Shape values calculated from in situ spectra and M. polykrikoides cell abundances in the SSK were highly correlated. Comparing red tide spectra from near-coincident multi-sensor data, remote-sensing reflectance (Rrs) spectra were similar to the spectra of in situ measurements from blue to green wavelengths. Rrs true-color composite images and Spectral Shape images of each sensor showed a clear pattern of M. polykrikoides patches, although there were some limitations for detecting red tide patches in coastal areas. We confirmed the complementarity of red tide data extracted from each sensor using an integrated red tide map. Statistical assessment showed that the sensitivity of red tide detection increased when multi-sensor data were used rather than single-sensor data. These results provide useful information for the application of multi-sensor for red tide detection

Submicron aerosol size distributions and cloud condensation nuclei concentrations measured at Gosan, Korea, during the Atmospheric Brown Clouds–East Asian Regional Experiment 2005

International audienc

Statistical Analysis for Tidal Flat Classification and Topography Using Multitemporal SAR Backscattering Coefficients

Coastal zones are very dynamic natural systems that experience short-term and long-term morphological changes. Their highly dynamic behavior requires frequent monitoring. Tidal flat topography for a large spatial coverage has been generated mainly by the waterline extraction method from multitemporal remote sensing observations. Despite the efficiency and robustness of the waterline extraction method, the waterline-based digital elevation model (DEM) is limited to representing small scale topographic features, such as localized tidal tributaries. Tidal flats show a rapid increase in SAR backscattering coefficients when the tide height is lower than the tidal flat topography compared to when the tidal flat is covered by water. This leads to a tidal flat with a distinct statistical behavior on the temporal variability of our multitemporal SAR backscattering coefficients. Therefore, this study aims to suggest a new method that can overcome the constraints of the waterline-based method by using a pixel-based DEM generation algorithm. Jenks Natural Break (JNB) optimization was applied to distinguish the tidal flat from land and ocean using multitemporal Senitnel-1 SAR data for the years 2014–2020. We also implemented a logistic model to characterize the temporal evolution of the SAR backscattering coefficients along with the tide heights and estimated intertidal topography. The Sentinel-1 DEM from the JNB classification and logistic function was evaluated by an airborne Lidar DEM. Our pixel-based DEM outperformed the waterline-based Landsat DEM. This study demonstrates that our statistical approach to intertidal classification and topography serves to monitor the near real-time spatiotemporal distribution changes of tidal flats through continuous and stable SAR data collection on local and regional scales

Synergistic effects of elevated carbon dioxide and sodium hypochlorite on survival and impairment of three phytoplankton species

Sodium hypochlorite (NaOCl) is widely used to disinfect seawater in power plant cooling systems in order to reduce biofouling, and in ballast water treatment systems to prevent transport of exotic marine species. While the toxicity of NaOCl is expected to increase by ongoing ocean acidification, and many experimental studies have shown how algal calcification, photosynthesis and growth respond to ocean acidification, no studies have investigated the relationship between NaOCl toxicity and increased CO2. Therefore, we investigated whether the impacts of NaOCl on survival, chlorophyll a (Chl-a), and effective quantum yield in three marine phytoplankton belonging to different taxonomic classes are increased under high CO2 levels. Our results show that all biological parameters of the three species decreased under increasing NaOCl concentration, but increasing CO2 concentration alone (from 450 to 715 mu atm) had no effect on any of these parameters in the organisms. However, due to the synergistic effects between NaOCl and CO2, the survival and Chl-a content in two of the species, Thalassiosira eccentrica and Heterosigma akashiwo, were significantly reduced under high CO2 when NaOCl was also elevated. The results show that combined exposure to high CO2 and NaOCl results in increasing toxicity of NaOCl in some marine phytoplankton. Consequently, greater caution with use of NaOCl will be required, as its use is widespread in coastal waters.N

Statistical Analysis for Tidal Flat Classification and Topography Using Multitemporal SAR Backscattering Coefficients

Coastal zones are very dynamic natural systems that experience short-term and long-term morphological changes. Their highly dynamic behavior requires frequent monitoring. Tidal flat topography for a large spatial coverage has been generated mainly by the waterline extraction method from multitemporal remote sensing observations. Despite the efficiency and robustness of the waterline extraction method, the waterline-based digital elevation model (DEM) is limited to representing small scale topographic features, such as localized tidal tributaries. Tidal flats show a rapid increase in SAR backscattering coefficients when the tide height is lower than the tidal flat topography compared to when the tidal flat is covered by water. This leads to a tidal flat with a distinct statistical behavior on the temporal variability of our multitemporal SAR backscattering coefficients. Therefore, this study aims to suggest a new method that can overcome the constraints of the waterline-based method by using a pixel-based DEM generation algorithm. Jenks Natural Break (JNB) optimization was applied to distinguish the tidal flat from land and ocean using multitemporal Senitnel-1 SAR data for the years 2014–2020. We also implemented a logistic model to characterize the temporal evolution of the SAR backscattering coefficients along with the tide heights and estimated intertidal topography. The Sentinel-1 DEM from the JNB classification and logistic function was evaluated by an airborne Lidar DEM. Our pixel-based DEM outperformed the waterline-based Landsat DEM. This study demonstrates that our statistical approach to intertidal classification and topography serves to monitor the near real-time spatiotemporal distribution changes of tidal flats through continuous and stable SAR data collection on local and regional scales