基于Landsat 8影像的黄河口悬浮物质量浓度遥感反演

doi:10.3969/j.issn.1001-909X.2018.01.004

摘要/Abstract

摘要： 悬浮物质量浓度是黄河口海域重要的水质和水环境监测参数之一,直接影响着水面以下光场的分布,进而影响水体的初级生产力和水域生态环境。本文基于2011年6—7月和11—12月共计89组现场实测悬浮物质量浓度和光谱数据,分析了黄河口及其附近海域不同悬浮物质量浓度的水体光谱特征,尝试利用多种波段组合建立悬浮物质量浓度遥感反演算法。结果表明865 nm波段与波段比655 nm/560 nm组合形式算法反演结果最优,算法相关系数R²为0.95,平均相对误差为25.65%。将算法应用于2014—2016年共7景Landsat 8 OLI遥感影像,分析了不同年份黄河口悬浮物质量浓度的时空分布特征,黄河口海域悬浮物质量浓度分布总体呈现近岸高,离岸低的特点,不同时期悬浮物质量浓度量值上有显著变化。

关键词: 黄河口, Landsat 8 OLI, 悬浮物, 遥感反演

Abstract: Suspended particulate matter (SPM) plays an important role in determining the light field under water, which then affects the primary production and waters ecological environment. Therefore, SPM concentration is one of the important parameters for water quality and hydrographic environment monitoring.Based on a total of 89 in-situ SPM concentration and spectral data collected from June to July and from November to December 2011, the spectral characteristics of suspended matter in the Yellow River Estuary and its adjacent waters were analyzed. And an empirical inversion algorithms for SPM concentration with different combinations of bands or band ratios was established. The result showed that the algorithm with combining the R_rs655/R_rs560 and R_rs865 was the best, the APD of algorithm was 25.65%, and the correlation was 0.95. Using the R_rs retrieved from Landsat 8 OLI data and the SPM algorithm, 7 maps of the SPM concentration in the Yellow River Estuary and its adjacent waters from 2014 to 2016 were obtained. The result indicated that the SPM concentration reduced gradually from the coastal to offshore waters, and the value of SPM concentration had significant changes during different periods.

Key words: Yellow River Estuary, Landsat 8 OLI, suspended particulate matter, remote sensing inversion

中图分类号:

周媛, 郝艳玲, 刘东伟, 崔廷伟, 于瑞宏, 张志磊. 基于Landsat 8影像的黄河口悬浮物质量浓度遥感反演[J]. 海洋学研究, 2018, 36(1): 35-45.

ZHOU Yuan, HAO Yan-ling, LIU Dong-wei, CUI Ting-wei, YU Rui-hong, ZHANG Zhi-lei. Estimation of suspended particulate matter concentration based on Landsat 8 data in the Yellow River Estuary[J]. Journal of Marine Sciences, 2018, 36(1): 35-45.

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