浒苔遥感监测研究进展

浒苔大规模集聚形成的绿潮灾害是海洋生态系统主要生态环境问题之一,基于卫星遥感影像监测浒苔及其扩展动态已成为一种及时有效的手段。对国内外浒苔遥感监测方面文献进行归纳整理,认为光学遥感数据、多波段比值法是最常用的遥感数据和监测方法。对遥感监测浒苔机理进行了阐述,并对分类方法进行评价认为监督分类法解译精度不高。目前单波段阈值法和多波段比值法应用广泛,但在监测漂浮浒苔和混合象元解译存在不足。辐射传输模型法能有效提高信息解译的精度,但还处于起步阶段。遥感监测浒苔灾害的未来发展需要提高影像空间分辨率,深入研究监测方法,进行多种平台和多源遥感数据相结合,并由定性走向定量,从而建立健全遥感监测预警系统。

Advances in the monitoring of Enteromorpha prolifera using remote sensing

Eutrophication of sea water has been regard as one of the major problems that are harmful to our environment and society. Green tide, which is caused by the proliferation of Enteromorpha prolifera, has a major impact on marine ecosystems. Proliferation of Enteromorpha prolifera is the main cause of the green tide. Monitoring the populations of E. prolifera and their dynamic are crucial in the prevention of green tide. Satellite remote sensing image is widely used in the monitoring of E. prolifera because of its timeliness and effectiveness. In this review, we discussed the current research on monitoring of E. prolifera using remote sensing. We considered the optical remote sensing data to be the most popular data used by recent rearchs, and the multi-band ratio method as the most commonly adopted monitoring method. We also discussed the mechanism of monitoring of E. prolifera using remote sensing found that the precision in the interpretation of remote sensing data was relatively low when using the supervision classification method. The single-band threshold method and multi-band ratio method have been widely used despite their shortage in monitoring of the floats of E. prolifera and interpretation of mixed pixels. The radiative transfer model method can improve the accuracy of information interpretation; however, being a newly developed method, it needs further improvements. For better monitoring of E. prolifera, the spatial resolution of images need to be improved in future research. Combining multiple platforms and multi-source remote sensing data are important aspects that could provide more accurate data from E. prolifera monitoring. Further studies on monitoring methods are required to achieve a timely and effective monitoring. Most importantly, we should replace the current qualitative analysis with a quantitative one in order to perfect the remote sensing monitoring and finally establish the early warning system.