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B2: ID.10705 OPAC
Wind-driven Phytoplankton Blooms in the Open Oceans and Their Mechanisms --Remote Sensing Marine Ecology
Chinese Academy of Sciences, China, People's Republic of;
Marine phytoplankton blooms not only can increase the primary production but also could result in negative ecological consequence, e.g., Harmful Algal Blooms (HABs). According to the classic theory for the formation of algal blooms “critical depth” and “eutrophication”, oligotrophic sea area is usually difficult to form a large area of algal blooms, and actually the traditional observation is only sporadic capture to the existence of algal blooms. Taking full advantages of multiple data of satellite remote sensing, this study: 1), introduces “Wind-driven algal blooms in open oceans: observation and mechanisms” It explained except classic coastal Ekman transport, the wind through a variety of mechanisms affecting the formation of algal blooms. Proposed a conceptual model of “Strong wind -upwelling-nutrient-phytoplankton blooms” in Western South China Sea (SCS) to assess role of wind-induced advection transport in phytoplankton bloom formation. It illustrates the nutrient resources that support long-term offshore phytoplankton blooms in the western SCS; 2), Proposal of the theory that “typhoons cause vertical mixing, induce phytoplankton blooms”, and quantify their important contribution to marine primary production; Proposal a new ecological index for typhoon. Proposed remote sensing inversion models. 3), Finding of the spatial and temporal distributions pattern of harmful algal bloom (HAB)，and species variations of HAB in the South Yellow Sea and East China Sea, and in the Pearl River estuary, and their oceanic dynamic mechanisms related with monsoon; The project proposed “wind-pump” mechanism integrates theoretical system combing “ocean dynamics, development of algal blooms, and impact on primary production”, which will benefit fisheries management. It also developed a new interdisciplinary subject “Remote Sensing Marine Ecology”(RSME) via .
Oil Spill Detection by Imaging Radars: Challenges and Pitfalls
1University of Hamburg, Germany; 2Jet Propulsion Laboratory, NASA, Pasadena, USA; 3Ocean University of China, Qingdao, China;
Imaging radars, like real aperture radars (RAR) and synthetic aperture radars (SARs), are the preferred remote sensing instruments for oil spill detection because they yield images independent of the time of the day and of cloud coverage. However, identifying mineral oil in radar images of the sea surface is not straightforward. Often black features visible on radar images, which are believed to be radar signatures of mineral oil, turn out to be radar signatures of “oil spill look-alikes”. Mineral oil films become visible on SAR images as dark areas denoting areas of reduced radar backscattering or reduced normalized radar cross section (NRCS). But dark areas can also originate also from other phenomena, the most important one being natural surface films, also called biogenic slicks, secreted by biota in the water column, like plankton or fish. The main challenge is to develop oil spill detection algorithms using SAR images to discriminate between sea areas covered with mineral oil and biogenic surface films, which form monomolecular layers and which can damp the short-scale surface waves responsible for the radar backscattering as strongly as mineral oil films. In this paper we critically review the present status of discriminating between these two types of surface using single-frequency/single-polarization as well as polarimetric SAR images. First, we shortly review standard discrimination criteria based on 1) the reduction of the NRCS, 2) differences in the geometry and shape of the surface film areas, and 3) differences in texture. We argue that discrimination algorithms that are based purely on imaging processing techniques often lead to false classifications (false alarms). Then we address discrimination criteria that are based on statistical behavior of the radar backscattering. We explain previous observations that there are differences in the statistics of radar backscattering from mineral oil films and biogenic slicks by differences in the physico-chemical properties of both types of surface films: The thickness of mineral oil films usually varies within an oil patch leading the variations in the viscous damping of the short surface waves (Bragg waves) responsible for the radar backscattering. In contrast to mineral oil films/emulsions, biogenic slicks cannot form multi-layers and exist on the sea surface only as monomolecular layers. Thus, Bragg waves on sea surfaces covered with biogenic slicks are uniformly damped, while the ones on sea surfaces covered with mineral oil films are nun-uniformly damped. This explanation contradicts previous explanations that the difference is due non-Bragg scattering from oil covered surfaces. Furthermore, we review discrimination criteria based on the difference of the dielectric constant and oil. We argue that discrimination is only possible when the oil layer or water-emulsion
Monitoring the coral reef of Xisha Islands using remote sensing
South China Sea Institute of Oceanology, Chinese Academy Of Sciences, China, People's Republic of;
Remote sensing is an effective way to monitor the structure of coral reef and it's variability. Compared with remote sensing classification on other research area, such as land cover classification, it is not easy to identify the benthic types of the coral reef because of the biodiversity of coral reefs and the influence of the water column on the optical signals. The coral reef of Xisha Islands is the most representative in China. In this study, we evaluated the applicability of GF-2 and Sentinel-2 for benthic habitat mapping of Yongle atoll, one of the biggest atoll in Xisha Islands. We integrated object-based image analysis and Support Vector Machine classifier (SVM) in classification. Compared with the traditional maximum likelihood method, our method shows more accurate result. The informative objected-based benthic maps was produced and a comparison was made on the classification results. The study provides an important technique for monitoring coral reef ecosystem in Xisha Islands.
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Conference: 2016 Dragon 3 Final Results Symposium
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