基于国产卫星多光谱影像的河流水体浊度遥感联合反演研究

肖潇; 徐坚; 赵登忠; 赵保成; 徐健; 程学军; 李国忠

doi:10.11988/ckyyb.20200337

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raybet体育在线院报 ›› 2021, Vol. 38 ›› Issue (6) : 128-136. DOI: 10.11988/ckyyb.20200337

信息技术应用

基于国产卫星多光谱影像的河流水体浊度遥感联合反演研究

肖潇¹, 徐坚^1,2,3, 赵登忠^1,3, 赵保成^1,3, 徐健^1,3, 程学军^1,3, 李国忠^1,3

作者信息 +

Combined Remote Sensing Retrieval of River Turbidity Based on Chinese Satellite data

XIAO Xiao¹, XU Jian^1,2,3, ZHAO Deng-zhong^1,3, ZHAO Bao-cheng^1,3, XU Jian^1,3, CHENG Xue-jun^1,3, LI Guo-zhong^1,3

Author information +

文章历史 +

摘要

基于集合建模思想,在水体光谱特征分析与敏感波段选择基础上,集成多种遥感反演模型优势,构建了河流水体浊度多光谱遥感联合反演模型(Combined Model-BP,CM-BP)。选择汉江中下游典型河段为研究区,利用2012—2013年原位观测数据,以具有较高时间分辨率和空间分辨率的国产卫星数据作为多光谱遥感数据源,测试评估了CM-BP浊度遥感反演模型适用性,并与传统波段组合模型进行精度比较,基于反演结果分析了研究区浊度时空分布特征。结果表明:基于集合建模思想构建的CM-BP模型的反演精度、适应性及稳定性均高于波段组合模型;从光谱分辨率、时空分辨率等角度考虑,环境与灾害监测预报小卫星星座系统、高分一号卫星、资源三号等国产卫星多光谱遥感数据是河流水体水质反演优选数据源;国产卫星遥感数据可以满足河流水体水质高精度、实时性与大尺度等遥感反演需要,为河流水环境监测研究提供数据基础。

Abstract

Inspired by combined modeling idea, we constructed a CM-BP (Combined Model-Back Propagation) for multispectral remote-sensing retrieval of river water turbidity by integrating the advantages of multiple remote-sensing retrieval models based on analyzing spectral characteristics of water bodies and selecting sensitive bands. With the in-situ observation data in 2012-2013 in typical reaches of the middle and lower Hanjiang River as a case study, we tested and assessed the applicability of the proposed CM-BP with domestic satellite data of high temporal and spatial resolutions as multispectral remote-sensing data sources. Furthermore, we compared the proposed CM-BP with traditional band-combined models in terms of retrieval precision, and meanwhile dissected the temporal and spatial distribution characteristics of the turbidity of Hanjiang River based on retrieval results. Results demonstrated that CM-BP boasts higher retrieval accuracy, applicability and stability than band-combined models. From the perspectives of spectral, temporal and spatial resolutions, multispectral remote-sensing data of Chinese domestic satellites like environment and disaster monitoring and forecasting small-satellite constellation, GF-1, and ZY-3 can be considered as optimal data sources for water quality retrieval of river. Remote-sensing data from Chinese domestic satellites meets the demand in high-accuracy, real-time and large-scale of remote-sensing retrieval of river water quality, thus providing a data basis for environmental monitoring studies of river.

导出引用

肖潇, 徐坚, 赵登忠, 赵保成, 徐健, 程学军, 李国忠. 基于国产卫星多光谱影像的河流水体浊度遥感联合反演研究[J]. raybet体育在线院报. 2021, 38(6): 128-136 https://doi.org/10.11988/ckyyb.20200337

XIAO Xiao, XU Jian, ZHAO Deng-zhong, ZHAO Bao-cheng, XU Jian, CHENG Xue-jun, LI Guo-zhong. Combined Remote Sensing Retrieval of River Turbidity Based on Chinese Satellite data[J]. Journal of Changjiang River Scientific Research Institute. 2021, 38(6): 128-136 https://doi.org/10.11988/ckyyb.20200337

中图分类号： X825 TP75

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