Although airborne hyperspectral data with detailed spatial and spectral information has demonstrated significant potential for tree species classification,it has not been widely used over large areas.A comprehensive p...Although airborne hyperspectral data with detailed spatial and spectral information has demonstrated significant potential for tree species classification,it has not been widely used over large areas.A comprehensive process based on multi-flightline airborne hyperspectral data is lacking over large,forested areas influenced by both the effects of bidirectional reflectance distribution function(BRDF)and cloud shadow contamination.In this study,hyperspectral data were collected over the Mengjiagang Forest Farm in Northeast China in the summer of 2017 using the Chinese Academy of Forestry's LiDAR,CCD,and hyperspectral systems(CAF-LiCHy).After BRDF correction and cloud shadow detection processing,a tree species classification workflow was developed for sunlit and cloud-shaded forest areas with input features of minimum noise fraction reduced bands,spectral vegetation indices,and texture information.Results indicate that BRDF-corrected sunlit hyperspectral data can provide a stable and high classification accuracy based on representative training data.Cloud-shaded pixels also have good spectral separability for species classification.The red-edge spectral information and ratio-based spectral indices with high importance scores are recommended as input features for species classification under varying light conditions.According to the classification accuracies through field survey data at multiple spatial scales,it was found that species classification within an extensive forest area using airborne hyperspectral data under various illuminations can be successfully carried out using the effective radiometric consistency process and feature selection strategy.展开更多
室外BRDF（Bidirectional reflectance distribution function）测量随着遥感的发展越来越重要。室外测量要求测量周期短、测量点多、光谱分辨率高。为了满足这一要求,设计了室外高光谱BRDF自动测量系统。系统主要由自动测量架和光谱仪...室外BRDF（Bidirectional reflectance distribution function）测量随着遥感的发展越来越重要。室外测量要求测量周期短、测量点多、光谱分辨率高。为了满足这一要求,设计了室外高光谱BRDF自动测量系统。系统主要由自动测量架和光谱仪器组成。测量架半径为2m,主要由天顶弧轨道、方位圆轨道、伺服电机、PLC组成。光谱仪器包括一台亮度计和一台照度计,亮度计测量反射亮度,被固定在测量架小车平台上,照度计测量入射照度。两台光谱仪器采用相同的平场凹面光栅分光、线阵列探测器探测。光谱测量范围为400~2500nm,光谱分辨率为3.5nm（400~1000nm）、12nm（1000~2500nm）。系统在工控机的控制下完成自动测量。在自动默认状态下测量周期大约为10min。展开更多
基金supported by the National Natural Science Foundation of China (Grant No.42101403)the National Key Researchand Development Program of China (Grant No.2017YFD0600404)。
文摘Although airborne hyperspectral data with detailed spatial and spectral information has demonstrated significant potential for tree species classification,it has not been widely used over large areas.A comprehensive process based on multi-flightline airborne hyperspectral data is lacking over large,forested areas influenced by both the effects of bidirectional reflectance distribution function(BRDF)and cloud shadow contamination.In this study,hyperspectral data were collected over the Mengjiagang Forest Farm in Northeast China in the summer of 2017 using the Chinese Academy of Forestry's LiDAR,CCD,and hyperspectral systems(CAF-LiCHy).After BRDF correction and cloud shadow detection processing,a tree species classification workflow was developed for sunlit and cloud-shaded forest areas with input features of minimum noise fraction reduced bands,spectral vegetation indices,and texture information.Results indicate that BRDF-corrected sunlit hyperspectral data can provide a stable and high classification accuracy based on representative training data.Cloud-shaded pixels also have good spectral separability for species classification.The red-edge spectral information and ratio-based spectral indices with high importance scores are recommended as input features for species classification under varying light conditions.According to the classification accuracies through field survey data at multiple spatial scales,it was found that species classification within an extensive forest area using airborne hyperspectral data under various illuminations can be successfully carried out using the effective radiometric consistency process and feature selection strategy.
文摘室外BRDF（Bidirectional reflectance distribution function）测量随着遥感的发展越来越重要。室外测量要求测量周期短、测量点多、光谱分辨率高。为了满足这一要求,设计了室外高光谱BRDF自动测量系统。系统主要由自动测量架和光谱仪器组成。测量架半径为2m,主要由天顶弧轨道、方位圆轨道、伺服电机、PLC组成。光谱仪器包括一台亮度计和一台照度计,亮度计测量反射亮度,被固定在测量架小车平台上,照度计测量入射照度。两台光谱仪器采用相同的平场凹面光栅分光、线阵列探测器探测。光谱测量范围为400~2500nm,光谱分辨率为3.5nm（400~1000nm）、12nm（1000~2500nm）。系统在工控机的控制下完成自动测量。在自动默认状态下测量周期大约为10min。
