基于水体光学分类的鄱阳湖悬沙浓度反演方法研究
作者:
作者简介:

况润元 (1976-),男,江西宜春人,博士,副教授,主要从事水色遥感机理与应用、地理信息系统应用等方面的研究。 E-mail:rykuang@163.com.

中图分类号:

P332

基金项目:

国家自然科学基金资助项目(41101322);江西省教育厅科学技术研究项目(GJJ160617);


Study on Inversion Model of Suspended Sediment Concentration Based on Optical Classification of Water Body in Poyang Lake
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    摘要:

    鄱阳湖是我国重要的湿地生态系统,对调节流域的水沙变化有着重要作用。由于鄱阳湖湖区面积广,内部差异大,单一的悬浮泥沙反演模型不足以准确反演出湖区的悬浮泥沙浓度。以实测的反射光谱数据、泥沙浓度数据为基础,提出一种基于分类后的反演模型,即根据实测数据的光谱形态特征分类出5种典型的水体类型。在此基础上,将分类后的各类水体分别建立各自合适的反演模型进行反演。结果表明基于水体分类的经验模型反演达到满意效果,平均绝对误差为0.00217g/L,平均相对误差为3.022%。基于分类后的经验反演模型适用于鄱阳湖悬沙浓度分布的监测研究,有助于更加宏观、准确的掌握鄱阳湖泥沙浓度的空间分布和变化,为保持鄱阳湖资源的可持续开发与利用提供决策依据。

    Abstract:

    The Poyang Lake is an important wetland ecosystem in China,which plays an important role in regulating the change of water and sediment.Because of large area and large internal differences of the Poyang Lake, a single suspended sediment inversion model is not enough to inverse the suspended sediment concentration.Therefore, this paper used a inversion model based on the classification with the measured reflectance spectra data and the sediment concentration data. It is said that according to the classification of spectral morphological characteristics of the measured data from 5 typical types of water bodies. On this basis, the classification of the various types of water were established respectively for the inversion of the appropriate inversion model. The results show that the empirical model retrieval based on water classification achieves satisfactory results, the average absolute error is 0.00217g/L, and the average relative error is 3.022%. Therefore, the empirical inversion model based on classification is applied to monitor the distribution of suspended sediment concentration in the Poyang Lake. This study will help to grasp the spatial distribution and change of the Poyang Lake sediment concentration, and provide decision basis for the sustainable development and utilization of the Poyang Lake resources.

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历史
  • 收稿日期:2017-01-26
  • 在线发布日期: 2022-06-22