基于Landsat-8 OLI数据的乌梁素海总溶解性固体质量浓度遥感反演

阿如娜; 青  松; 包玉海

引用本文:	阿如娜,青松,包玉海.基于Landsat-8 OLI数据的乌梁素海总溶解性固体质量浓度遥感反演[J].灌溉排水学报,2018,37(4):99-105.
	A Runa,QING Song,BAO Yuhai.基于Landsat-8 OLI数据的乌梁素海总溶解性固体质量浓度遥感反演[J].灌溉排水学报,2018,37(4):99-105.

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基于Landsat-8 OLI数据的乌梁素海总溶解性固体质量浓度遥感反演
阿如娜，青松，包玉海
内蒙古师范大学地理科学学院，呼和浩特 010022；内蒙古自治区遥感与地理信息系统重点实验室，呼和浩特 010022

摘要:

【目的】探究研究区总溶解性固体（TDS）质量浓度分布，为水环境质量评价提供依据。【方法】利用2013年和2015年乌梁素海实测TDS质量浓度和遥感反射率数据，建立并检验了TDS质量浓度多元线性回归模型，将模型应用于大气校正后的Landsat-8 OLI数据，分析了乌梁素海TDS质量浓度时空分布特征。【结果】建立的多元线性回归模型均方根误差为0.455 g/L，平均相对误差为13%，决定系数R2为0.594。经误差敏感性检验及区域适用性检验表明，该算法适用于乌梁素海开阔水体TDS质量浓度遥感反演。乌梁素海TDS质量浓度无明显的时间循环变化特征；中部开阔水体TDS质量浓度低；北部、东部沿岸及南部部分水域TDS质量浓度反演结果有较大误差。主要原因是北部、东部和南部受底质、藻华及沉水植被的影响较大。【结论】建立的模型可用于乌梁素海TDS质量浓度的遥感反演。

关键词: 总溶解固体； OLI；反演；回归模型；乌梁素海

DOI：10.13522/j.cnki.ggps.2017.0266

分类号:

基金项目:

Estimating the Concentration of Dissolved Solid in the Wuliangsuhai Lake Based on the Landsat-8 OLI Images

A Runa, QING Song, BAO Yuhai

College of Geographical Science, Inner Mongolia Normal University, Hohhot 010022, China;Inner Mongolian Key Laboratory of Remote Sensing and Geographical Information System, Hohhot 010022, China

Abstract:

【Objective】 The objective of this paper is to investigate the distribution of total dissolved solids (TDS) in the Wuliangsuhai Lake in attempts to provide baseline data for quality assessment of its water environment.【Method】 We developed and tested a multi-linear regression model based on the remote sensing reflectance and the TDS concentration measured in 2013 and 2015 in the lake. The root mean square error of the model was 0.455 g/L with R2 being 0.594 and an average relative error of 13%. Error sensitivity analysis and suitability analysis reveled that this regression model was accurate to retrieve the TDS in the lake. The model was used with the Landsat-8 OLI data to calculate the spatiotemporal distribution of TDS in the Lake. 【Result】 There was no noticeable temporal cycle in the TDS concentration and the TDS was low in center of the lake. The errors of the model were high for the northern and southern lake, as well as the area along the east coast due to the effect of bottom reflectance, algal blooms and submerged vegetation. 【Conclusion】 Overall, the model worked well and has implications in using remote sensing technology to assess surface water quality.

Key words: total dissolved solid; OLI; retrieval; regression model; Wuliangsuhai Lake