本研究以黄河三角洲滨海盐渍土为例,尝试使用HICO(Hyperspectral Imager for the Coastal Ocean)高光谱影像结合现场实测高光谱数据进行表层土壤全盐含量的反演。采用波段组合的方法建立光谱参量,通过相关分析筛选出敏感光谱参量,以决...本研究以黄河三角洲滨海盐渍土为例,尝试使用HICO(Hyperspectral Imager for the Coastal Ocean)高光谱影像结合现场实测高光谱数据进行表层土壤全盐含量的反演。采用波段组合的方法建立光谱参量,通过相关分析筛选出敏感光谱参量,以决定系数R2选出最佳模型;利用HICO影像反射率与实测高光谱反射率之间的关系,对模型进行修正,并应用于影像。研究发现,比值(RI)、差值(DI)波段组合方法建立的光谱参量与表层土壤全盐含量的相关性明显提高。DI_((845,473))、DI_((839,490))、DI_((845,496))及DI_((839,501))的幂函数模型效果最好,且验证决定系数R^2均大于0.86,相对分析误差RPD>3,RMSE较小。此外,HICO遥感影像的模型反演结果较为一致,能够反映表层土壤全盐含量的分布。研究显示,利用高光谱数据进行表层土壤全盐含量的反演建模具有可行性,可为区域表层土壤全盐含量的定量反演提供参考。展开更多
The Spratly(Nansha) Islands in the South China Sea have considerable economic and important militarily strategic status.Ocean color remote sensing is an effective mean of surveying and research and especially it is us...The Spratly(Nansha) Islands in the South China Sea have considerable economic and important militarily strategic status.Ocean color remote sensing is an effective mean of surveying and research and especially it is useful for areas that are difficult to access,such as Thitu Island and its reef in the Spratly Islands.The Hyper-spectral Optimization Process Exemplar(HOPE) model,developed by Lee et al.(1999) is a rapid and robust bathymetry method that uses hyper-spectral remote sensing.In this study,using Hyperion hyper-spectral sensor data and HOPE,we derive bathymetry and bottom albedo measurements around Thitu Island and its reef.We compare the distribution of bottom depths from C-MAP with that derived from the Hyperion data.The retrieved bathymetry results correlate well with the distribution obtained from the bathymetry contour from 2.0 to 20 m.The average difference between Hyperion and C-MAP for two selected transects was 17.1%(n=59,R=0.848,RMSE=2.342) and 10.9%(n=59,R2=0.834,RMSE=0.463).The retrieved bottom albedo is homogeneous in the lagoon and significantly non-homogeneous around the lagoon.These results indicate that HOPE could be very useful for bathymetry studies for the islands of the South China Sea.展开更多
文摘本研究以黄河三角洲滨海盐渍土为例,尝试使用HICO(Hyperspectral Imager for the Coastal Ocean)高光谱影像结合现场实测高光谱数据进行表层土壤全盐含量的反演。采用波段组合的方法建立光谱参量,通过相关分析筛选出敏感光谱参量,以决定系数R2选出最佳模型;利用HICO影像反射率与实测高光谱反射率之间的关系,对模型进行修正,并应用于影像。研究发现,比值(RI)、差值(DI)波段组合方法建立的光谱参量与表层土壤全盐含量的相关性明显提高。DI_((845,473))、DI_((839,490))、DI_((845,496))及DI_((839,501))的幂函数模型效果最好,且验证决定系数R^2均大于0.86,相对分析误差RPD>3,RMSE较小。此外,HICO遥感影像的模型反演结果较为一致,能够反映表层土壤全盐含量的分布。研究显示,利用高光谱数据进行表层土壤全盐含量的反演建模具有可行性,可为区域表层土壤全盐含量的定量反演提供参考。
基金Supported by the National Science Foundation for Young Scientists of China(No.40906087)
文摘The Spratly(Nansha) Islands in the South China Sea have considerable economic and important militarily strategic status.Ocean color remote sensing is an effective mean of surveying and research and especially it is useful for areas that are difficult to access,such as Thitu Island and its reef in the Spratly Islands.The Hyper-spectral Optimization Process Exemplar(HOPE) model,developed by Lee et al.(1999) is a rapid and robust bathymetry method that uses hyper-spectral remote sensing.In this study,using Hyperion hyper-spectral sensor data and HOPE,we derive bathymetry and bottom albedo measurements around Thitu Island and its reef.We compare the distribution of bottom depths from C-MAP with that derived from the Hyperion data.The retrieved bathymetry results correlate well with the distribution obtained from the bathymetry contour from 2.0 to 20 m.The average difference between Hyperion and C-MAP for two selected transects was 17.1%(n=59,R=0.848,RMSE=2.342) and 10.9%(n=59,R2=0.834,RMSE=0.463).The retrieved bottom albedo is homogeneous in the lagoon and significantly non-homogeneous around the lagoon.These results indicate that HOPE could be very useful for bathymetry studies for the islands of the South China Sea.
