The absorption spectrum of phytoplankton is an important bio-optical parameter for ocean color hyperspectral remote sensing;its magnitude and shape can be aff ected considerably by pigment composition and concentratio...The absorption spectrum of phytoplankton is an important bio-optical parameter for ocean color hyperspectral remote sensing;its magnitude and shape can be aff ected considerably by pigment composition and concentration. We conducted Gaussian decomposition to the absorption spectra of phytoplankton pigment and studied the spectral components of the phytoplankton, in which the package effect was investigated using pigment concentration data and phytoplankton absorption spectra. The decomposition results were compared with the corresponding concentrations of the five main pigment groups (chlorophylls a , b , and c , photo-synthetic carotenoids (PSC), and photo-protective carotenoids (PPC)). The results indicate that the majority of residual errors in the Gaussian decomposition are <0.001 m^-1 , and R 2 of the power regression between characteristic bands and HPLC pigment concentrations (except for chlorophyll b) was 0.65 or greater for surface water samples at autumn cruise. In addition, we determined a strong predictive capability for chlorophylls a , c , PPC, and PSC. We also tested the estimation of pigment concentrations from the empirical specific absorption coeffi cient of pigment composition. The empirical decomposition showed that the Ficek model was the closest to the original spectra with the smallest residual errors.The pigment decomposition results and HPLC measurements of pigment concentration are in a high consistency as the scatter plots are distributed largely near the 1:1 line in spite of prominent seasonal variations. The Wozniak model showed a better fit than the Ficek model for Ch1 a , and the median relative error was small. The pigment component information estimated from the phytoplankton absorption spectra can help better remote sensing of hyperspectral ocean color that related to the changes in phytoplankton communities and varieties.展开更多
The absorption coefficient of water is an important bio-optical parameter for water optics and water color remote sensing. However, scattering correction is essential to obtain accurate absorption coefficient values i...The absorption coefficient of water is an important bio-optical parameter for water optics and water color remote sensing. However, scattering correction is essential to obtain accurate absorption coefficient values in situ using the nine-wavelength absorption and attenuation meter AC9. Establishing the correction always fails in Case 2 water when the correction assumes zero absorption in the near-infrared(NIR) region and underestimates the absorption coefficient in the red region, which affect processes such as semi-analytical remote sensing inversion. In this study, the scattering contribution was evaluated by an exponential fitting approach using AC9 measurements at seven wavelengths(412, 440, 488, 510, 532, 555, and 715 nm) and by applying scattering correction. The correction was applied to representative in situ data of moderately turbid coastal water, highly turbid coastal water, eutrophic inland water, and turbid inland water. The results suggest that the absorption levels in the red and NIR regions are significantly higher than those obtained using standard scattering error correction procedures. Knowledge of the deviation between this method and the commonly used scattering correction methods will facilitate the evaluation of the effect on satellite remote sensing of water constituents and general optical research using different scatteringcorrection methods.展开更多
With the rapid increase of Unmanned Aircraft Vehicle(UAV) numbers,the contradiction between extensive flight demands and limited low-altitude airspace resources has become increasingly prominent.To ensure the safety a...With the rapid increase of Unmanned Aircraft Vehicle(UAV) numbers,the contradiction between extensive flight demands and limited low-altitude airspace resources has become increasingly prominent.To ensure the safety and efficiency of low-altitude UAV operations,the low-altitude UAV public air route creatively proposed by the Chinese Academy of Sciences(CAS) and supported by the Civil Aviation Administration of China(CAAC) has been gradually recognized.However,present planning research on UAV low-altitude air route is not enough to explore how to use the ground transportation infrastructure,how to closely combine the surface pattern characteristics,and how to form the mechanism of "network".Based on the solution proposed in the early stage and related researches,this paper further deepens the exploration of the low-altitude public air route network and the implementation of key technologies and steps with an actual case study in Tianjin,China.Firstly,a path-planning environment consisting of favorable spaces,obstacle spaces,and mobile communication spaces for UAV flights was pre-constructed.Subsequently,air routes were planned by using the conflict detection and path re-planning algorithm.Our study also assessed the network by computing the population exposure risk index(PERI) and found that the index value was greatly reduced after the construction of the network,indicating that the network can effectively reduce the operational risk.In this study,a low-altitude UAV air route network in an actual region was constructed using multidisciplinary approaches such as remote sensing,geographic information,aviation,and transportation;it indirectly verified the rationality of the outcomes.This can provide practical solutions to low-altitude traffic problems in urban areas.展开更多
基金Supported by the National Natural Science Foundation of China(Nos.91638201,41276184,41771388 41471308,41571361,41701402)the Strategic Priority Research Program of Chinese Academy of Sciences(No.XDA2003030201)+2 种基金the National Key Research and Development Program of China(Nos.2017YFB0503005,2016YFC1400903,2016YFB0501502)the High Resolution Earth Observation Systems of National Science and Technology Major Projects(No.41-Y20A31-9003-15/17)the China-Sri Lanka Joint Research and Demonstration Center for Water Technology,and the State Development and Reform Commission’s Special Financial Projects(No.2017ST000602)
文摘The absorption spectrum of phytoplankton is an important bio-optical parameter for ocean color hyperspectral remote sensing;its magnitude and shape can be aff ected considerably by pigment composition and concentration. We conducted Gaussian decomposition to the absorption spectra of phytoplankton pigment and studied the spectral components of the phytoplankton, in which the package effect was investigated using pigment concentration data and phytoplankton absorption spectra. The decomposition results were compared with the corresponding concentrations of the five main pigment groups (chlorophylls a , b , and c , photo-synthetic carotenoids (PSC), and photo-protective carotenoids (PPC)). The results indicate that the majority of residual errors in the Gaussian decomposition are <0.001 m^-1 , and R 2 of the power regression between characteristic bands and HPLC pigment concentrations (except for chlorophyll b) was 0.65 or greater for surface water samples at autumn cruise. In addition, we determined a strong predictive capability for chlorophylls a , c , PPC, and PSC. We also tested the estimation of pigment concentrations from the empirical specific absorption coeffi cient of pigment composition. The empirical decomposition showed that the Ficek model was the closest to the original spectra with the smallest residual errors.The pigment decomposition results and HPLC measurements of pigment concentration are in a high consistency as the scatter plots are distributed largely near the 1:1 line in spite of prominent seasonal variations. The Wozniak model showed a better fit than the Ficek model for Ch1 a , and the median relative error was small. The pigment component information estimated from the phytoplankton absorption spectra can help better remote sensing of hyperspectral ocean color that related to the changes in phytoplankton communities and varieties.
基金Supported by the National Key Research and Development Program of China(Nos.2016YFB0501502,2016YFC1400903,2016YFB0500304)the National Natural Science Foundation of China(Nos.91638201,41276184,41325004,41471308,41571361)+1 种基金the High Resolution Earth Observation Systems of National Science and Technology Major Projects(No.41-Y20A31-9003-15/17)the Director Foundation of Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences(No.Y6SJ2100CX)
文摘The absorption coefficient of water is an important bio-optical parameter for water optics and water color remote sensing. However, scattering correction is essential to obtain accurate absorption coefficient values in situ using the nine-wavelength absorption and attenuation meter AC9. Establishing the correction always fails in Case 2 water when the correction assumes zero absorption in the near-infrared(NIR) region and underestimates the absorption coefficient in the red region, which affect processes such as semi-analytical remote sensing inversion. In this study, the scattering contribution was evaluated by an exponential fitting approach using AC9 measurements at seven wavelengths(412, 440, 488, 510, 532, 555, and 715 nm) and by applying scattering correction. The correction was applied to representative in situ data of moderately turbid coastal water, highly turbid coastal water, eutrophic inland water, and turbid inland water. The results suggest that the absorption levels in the red and NIR regions are significantly higher than those obtained using standard scattering error correction procedures. Knowledge of the deviation between this method and the commonly used scattering correction methods will facilitate the evaluation of the effect on satellite remote sensing of water constituents and general optical research using different scatteringcorrection methods.
基金National Key Research and Development Program of China,No.2017YFB0503005Key Research Program of the Chinese Academy of Sciences,No.ZDRW-KT-2020-2+1 种基金National Natural Science Foundation of China,No.41971359,No.41771388Tianjin Intelligent Manufacturing Project Technology of Intelligent Networking by Autonomous Control UAVs for Observation and Application,No.Tianjin-IMP-2。
文摘With the rapid increase of Unmanned Aircraft Vehicle(UAV) numbers,the contradiction between extensive flight demands and limited low-altitude airspace resources has become increasingly prominent.To ensure the safety and efficiency of low-altitude UAV operations,the low-altitude UAV public air route creatively proposed by the Chinese Academy of Sciences(CAS) and supported by the Civil Aviation Administration of China(CAAC) has been gradually recognized.However,present planning research on UAV low-altitude air route is not enough to explore how to use the ground transportation infrastructure,how to closely combine the surface pattern characteristics,and how to form the mechanism of "network".Based on the solution proposed in the early stage and related researches,this paper further deepens the exploration of the low-altitude public air route network and the implementation of key technologies and steps with an actual case study in Tianjin,China.Firstly,a path-planning environment consisting of favorable spaces,obstacle spaces,and mobile communication spaces for UAV flights was pre-constructed.Subsequently,air routes were planned by using the conflict detection and path re-planning algorithm.Our study also assessed the network by computing the population exposure risk index(PERI) and found that the index value was greatly reduced after the construction of the network,indicating that the network can effectively reduce the operational risk.In this study,a low-altitude UAV air route network in an actual region was constructed using multidisciplinary approaches such as remote sensing,geographic information,aviation,and transportation;it indirectly verified the rationality of the outcomes.This can provide practical solutions to low-altitude traffic problems in urban areas.
