首页|融合GF-1和高光谱的内陆水体叶绿素a浓度反演

融合GF-1和高光谱的内陆水体叶绿素a浓度反演

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通过对含叶绿素a水体反射光谱特征分析,融合国产高分卫星和近地高光谱数据开展内陆水体水质遥感监测工作,形成了叶绿素a浓度遥感反演技术方法.利用GF-1 遥感数据特征波段,与实测近地高光谱数据进行相关性分析,构建叶绿素a浓度联合反演估计模型,其相关性系数达到 0.794.将实测值与预测值进行线性拟合,其拟合优度达到 0.780 5,两者间均方根误差为 2.11,平均相对误差为 20.56%,基本满足水库叶绿素a含量遥感反演需求.选取湖南省典型水库,通过标准化分级,监测水库叶绿素a浓度空间分布情况,为后期快速掌握内陆水体污染控制、风险评估等提供技术支撑.
Retrieval of Chlorophyll-a Concentration in Inland Water by Integrating GF-1 and Hyperspectral
Through the analysis of the characteristics of the reflection spectrum of the water containing Chlorophyll-a and the remote sensing monitoring of inland water quality by integrating the domestic high-resolution satellite and the near earth hyperspectral data,a remote sensing inversion method of Chlorophyll-a concentration is formed.Based on the correlation analysis between the characteristic band of GF-1 remote sensing data and the measured near earth hyperspectral data,a joint inversion estimation model of Chlorophyll-a concentration is constructed,and the correlation coefficient is 0.794.The linear fitting between the measured and predicted data shows that the good-ness of fit is 0.780 5,the root mean square error is 2.11 and the average relative error is 20.56%,which basically meets the needs of remote sensing inversion of Chlorophyll-a concentration in the reservoir.Typical reservoirs in Hunan Province are selected to monitor the spatial distribution of Chlorophyll-a concentration through standardized classification,so as to provide technical support for quickly mastering inland water pollution control and risk as-sessment in the later period.

Chlorophyll-aremote sensing monitoring of water qualityGF-1near-earth hyperspectralremote sensing inversion

曹诚、郝建明、吴朝辉、彭宇、朱亮

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湖南省第二测绘院,湖南 长沙 410119

重庆市万盛经开区国土房管局,重庆 400800

中铁二院(成都)咨询监理有限责任公司,四川 成都 610036

叶绿素a 水质遥感监测 高分一号 近地高光谱 遥感反演

2024

测绘科学技术学报
信息工程大学科研部

测绘科学技术学报

影响因子:0.594
ISSN:1673-6338
年,卷(期):2024.40(4)