Based on GOCI data and the built-in CO2 algorithm, this paper investigated the spatial-temporal distribution characteristics of chlorophyll-a in offshore waters of Yantai and Weihai from 2014 to 2016. Results showed: The chlorophyll-a concentration in the study area has a significant spatial-temporal characteristics, showed a decreased tendency from estuary to offshore area in general. While the lowest value major in the north open seas, the highest value appeared in Sishili Bay and the coastal zone along Weihai, even extended to the western coastal area of Shandong Peninsula. The spatial difference of the concentration of chlorophyll-a in summer was significantly higher than that in winter, and the enrichment effect increased with the increase of temperature. From the perspective of temporal distribution, the chlorophyll-a level was highest in August and lowest in February, and there are small but obvious double peaks in the spring and autumn of May and October. Our work indicated that chlorophyll a concentration level in the study area showed a gradual upward trend in recent 3 years.
Since 2008, the Green Tide has been continuously erupted for 10 years in Yellow Sea. Relevant studies have proved that the source of the green tide burst is the laver rafts in the radiated sand area. In this study, UAV (Unmanned Aerial Vehicle ) and S2A (Sentinel Satellite) data were used to monitor and estimate the biomass of Green tide algae on the rafts of seaweed. Using UAV imagery combined with high-resolution satellite data and field survey data, Accurately monitoring and assessing the biomass of green tide algae in the radiation sandy area can provide a scientific basis for the prevention and early warning of the Southern Yellow Sea green tide disasters.
This paper conducted dynamic monitoring over the green tide (large green alga—Ulva prolifera)
occurred in the Yellow Sea in 2014 to 2016 by the use of multi-source remote sensing data, including GF-1
WFV, HJ-1A/1B CCD, CBERS-04 WFI, Landsat-7 ETM+ and Landsta-8 OLI, and by the combination of
VB-FAH (index of Virtual-Baseline Floating macroAlgae Height) with manual assisted interpretation
based on remote sensing and geographic information system technologies. The result shows that unmanned
aerial vehicle (UAV) and shipborne platform could accurately monitor the distribution of Ulva prolifera in
small spaces, and therefore provide validation data for the result of remote sensing monitoring over Ulva
prolifera. The result of this research can provide effective information support for the prevention and
control of Ulva prolifera.
In recent years, satellite remote sensing have been widely used in dynamic monitoring of Green Tide. However, the images captured by unmanned aerial vehicles (UAV) are rarely used in floating green tide monitoring. In this paper, a quad-rotor unmanned aerial vehicle was used to mapping the coverage of green tide on the seabeach in Haiyang with three algorithms based on RGB image.The conclusions are as follows: there is discrepancy in both maximum value band among RGB and the difference in the green band for a true color aerial photograph taken from a UAV; the best index for floating green tide mapping on seabeach is GLI. It is possible to have a comprehensive, objective and scientific understanding of the floating green tide mapping with aid of UAV based on RGB image in the seabeach.
Coastal wetland is a net carbon sink with a high carbon density. However, coastal reclamation
directly changes the structure of coastal wetland ecosystem and consequent carbon sink function.
The aim of this work was to estimate the reclamation-induced carbon loss in coastal wetlands
using time series GF-1 WVF data. For this purpose, GF-1 WVF imageries of 2013 (before
reclamation) and 2017 (after reclamation) in the Yangtze Estuary were collected and analyzed
combined with field monitoring. Results showed that the converted coastal wetland area occupied
up to 61.60% between 2013 and 2017. Carbon estimation indicated that the coastal wetland before
reclamation had greater potential contribution to the global warming mitigation than the wetland
reclamation to other land cover types. Finally the vulnerability of carbon stores and uncertain
analysis with remote sensing technology in coastal wetlands environment were discussed. We
emphasized that long-term monitoring of coastal wetlands and its carbon dynamic are urgently
needed, because so many uncertain factors exist in short-term monitoring.
This paper monitored the outbreak of green tide in the Yellow Sea, China, in 2014 based on GOCI remote sensing image and NDVI extraction method, combined with GIS (Geographical Information System) and visual interpretation technologies. The results show: the green tide is firstly found in the open waters near Yancheng, Jiangsu Province in mid May, and drifted from the southwest to the northeast direction. When reached the neighboring waters between Jiangsu and Shandong in early June, the green tide entered an outbreak stage and reached the maximum coverage area of 2206.54 km2 in 18, June. In early July, the green tide began into a recession stage until all died in early August while its frontline preserved in Yantai – Weihai – Qingdao. Our work shows GOCI image with high temporal resolution is available for the study of migration path and drift speed of green tide.
Previous studies have shown that Terra moderate resolution imaging spectroradiometer (MODIS) has low detection and characterization efficiency when mapping a green tide (Ulva prolifera) in the Yellow Sea. To quantify the uncertainty in mapping of the green tide using MODIS data, comparisons were conducted between quasi synchronous MODIS images and in situ observation data, as well as an unmanned aerial vehicle (UAV) image. The results show that MODIS images could detect the location of large (>100 m) floating green algae patches with good positional accuracy but tended to ignore the existence of small patches less than 10 m in width. The floating macroalgae area extracted using MODIS was several times larger than the area mapped using the UAV image. The Sentinel-2 multispectral instrument, the Chinese high-resolution GF-1 wide field camera, and the Chinese HJ-1 charge-coupled device are recommended for early green tide detection, whereas MODIS is suitable for green tide monitoring. The UAV could also play an important role in regional green tide monitoring with the advantages of flexibility, smaller dimensions, high spatial resolution, and low cost.
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