Hyperspectral images have wide applications in the fields of geology,mineral exploration,agriculture,forestry and environmental studies etc.due to their narrow band width with numerous channels.However,these images co...Hyperspectral images have wide applications in the fields of geology,mineral exploration,agriculture,forestry and environmental studies etc.due to their narrow band width with numerous channels.However,these images commonly suffer from atmospheric effects,thereby limiting their use.In such a situation,atmospheric correction becomes a necessary pre-requisite for any further processing and accurate interpretation of spectra of different surface materials/objects.In the present study,two very advance atmospheric approaches i.e.QUAC and FLAASH have been applied on the hyperspectral remote sensing imagery.The spectra of vegetation,man-made structure and different minerals from the Gadag area of Karnataka,were extracted from the raw image and also from the QUAC and FLAASH corrected images.These spectra were compared among themselves and also with the existing USGS and JHU spectral library.FLAASH is rigorous atmospheric algorithm and requires various parameters to perform but it has capability to compensate the effects of atmospheric absorption.These absorption curves in any spectra play an important role in identification of the compositions.Therefore,the presence of unwanted absorption features can lead to wrong interpretation and identification of mineral composition.FLAASH also has an advantage of spectral polishing which provides smooth spectral curves which helps in accurate identification of composition of minerals.Therefore,this study recommends that FLAASH is better than QUAC for atmospheric correction and correct interpretation and identification of composition of any object or minerals.展开更多
To acquire high-quality operational data products for Chinese in-orbit and scheduled ocean color sensors, the performances of two operational atmospheric correction(AC) algorithms(ESA MEGS 7.4.1 and NASA Sea DAS 6.1) ...To acquire high-quality operational data products for Chinese in-orbit and scheduled ocean color sensors, the performances of two operational atmospheric correction(AC) algorithms(ESA MEGS 7.4.1 and NASA Sea DAS 6.1) were evaluated over the East China Seas(ECS) using MERIS data. The spectral remote sensing reflectance R_(rs)(λ), aerosol optical thickness(AOT), and ?ngstr?m exponent(α) retrieved using the two algorithms were validated using in situ measurements obtained between May 2002 and October 2009. Match-ups of R_(rs), AOT, and α between the in situ and MERIS data were obtained through strict exclusion criteria. Statistical analysis of R_(rs)(λ) showed a mean percentage difference(MPD) of 9%–13% in the 490–560 nm spectral range, and significant overestimation was observed at 413 nm(MPD>72%). The AOTs were overestimated(MPD>32%), and although the ESA algorithm outperformed the NASA algorithm in the blue-green bands, the situation was reversed in the red-near-infrared bands. The value of α was obviously underestimated by the ESA algorithm(MPD=41%) but not by the NASA algorithm(MPD=35%). To clarify why the NASA algorithm performed better in the retrieval of α, scatter plots of the α single scattering albedo(SSA) density were prepared. These α-SSA density scatter plots showed that the applicability of the aerosol models used by the NASA algorithm over the ECS is better than that used by the ESA algorithm, although neither aerosol model is suitable for the ECS region. The results of this study provide a reference to both data users and data agencies regarding the use of operational data products and the investigation into the improvement of current AC schemes over the ECS.展开更多
The purpose of this research is to improve the retrieval accuracy for the suspended sediment concentration(SSC) from in situ and satellite remote sensing measurements in turbid East China estuarine and coastal waters....The purpose of this research is to improve the retrieval accuracy for the suspended sediment concentration(SSC) from in situ and satellite remote sensing measurements in turbid East China estuarine and coastal waters. For this aim, three important tasks are formulated and solved: 1) an estimation of remote-sensing reflectance spectra R_(rs)(λ) after atmospheric correction; 2) an estimation of R_(rs)(λ) from the radiometric signals above the air-water surface; and 3) an estimation of SSC from R_(rs)(λ). Six different models for radiometric R_(rs)(λ) determination and 28 models for SSC versus R_(rs)(λ) are analyzed based on the field observations made in the Changjiang River estuary and its adjacent coastal area. The SSC images based on the above-mentioned analysis are generated for the area.展开更多
Parameter optimization of nodes communication is the foundation of underwater sensor networks.The packet size is an important indicator of the impact of communication performance.As a result,the optimal packet size se...Parameter optimization of nodes communication is the foundation of underwater sensor networks.The packet size is an important indicator of the impact of communication performance.As a result,the optimal packet size selection is a critical issue in improving the communication performance.This paper aims to make a model reflecting the communication characteristics as the optimization target,because underwater sensor networks have the characteristics of high time delay,high energy consumption and high bit error rate.Finally,simulation experiments and theory have demonstrated the effectiveness and timeliness of simultaneous perturbation stochastic approximation(SPSA) algorithm.展开更多
We employ the in-site automated observation radiometric calibration(AORC) approach to perform vicarious calibration, which does not require the manual efforts of a field team to measure the surface conditions. By us...We employ the in-site automated observation radiometric calibration(AORC) approach to perform vicarious calibration, which does not require the manual efforts of a field team to measure the surface conditions. By using an automated test-site radiometer(ATR), the surface radiance at any moment in time can be obtained. This Letter describes the AORC approach and makes use of data to compute top-of-atmosphere radiance and compare it to measurements from the Moderate Resolution Imaging Spectroradiometer. The result shows that the relative deviation is less than 5% and the uncertainty is less than 6.2%, which indicates that the in-site AORC maintains an accuracy level on par with traditional calibration.展开更多
An optical hydrogen sulfide(H_2S) sensor based on wavelength modulation spectroscopy with the second harmonic(2f) corrected by the first harmonic(1f) signal(WMS-2f/1f) is developed using a distributed feedback(DFB) la...An optical hydrogen sulfide(H_2S) sensor based on wavelength modulation spectroscopy with the second harmonic(2f) corrected by the first harmonic(1f) signal(WMS-2f/1f) is developed using a distributed feedback(DFB) laser emitting at 1.578 μm and a homemade gas cell with 1-m-long optical path length. The novel sensor is constructed by an electrical cabinet and an optical reflecting and receiving end. The DFB laser is employed for targeting a strong H_2S line at 6 336.62 cm^(-1) in the fundamental absorption band of H_2S. The sensor performance, including the minimum detection limit and the stability, can be improved by reducing the laser intensity drift and common mode noise by means of the WMS-2f/1f technique. The experimental results indicate that the linearity and response time of the sensor are 0.999 26 and 6 s(in concentration range of 15.2—45.6 mg/m^3), respectively. The maximum relative deviation for continuous detection(60 min) of 30.4 mg/m^3 H_2S is 0.48% and the minimum detection limit obtained by Allan variance is 79 μg/m^3 with optimal integration time of 32 s. The optical H_2S sensor can be applied to environmental monitoring and industrial production, and it has significance for real-time online detection in many fields.展开更多
文摘Hyperspectral images have wide applications in the fields of geology,mineral exploration,agriculture,forestry and environmental studies etc.due to their narrow band width with numerous channels.However,these images commonly suffer from atmospheric effects,thereby limiting their use.In such a situation,atmospheric correction becomes a necessary pre-requisite for any further processing and accurate interpretation of spectra of different surface materials/objects.In the present study,two very advance atmospheric approaches i.e.QUAC and FLAASH have been applied on the hyperspectral remote sensing imagery.The spectra of vegetation,man-made structure and different minerals from the Gadag area of Karnataka,were extracted from the raw image and also from the QUAC and FLAASH corrected images.These spectra were compared among themselves and also with the existing USGS and JHU spectral library.FLAASH is rigorous atmospheric algorithm and requires various parameters to perform but it has capability to compensate the effects of atmospheric absorption.These absorption curves in any spectra play an important role in identification of the compositions.Therefore,the presence of unwanted absorption features can lead to wrong interpretation and identification of mineral composition.FLAASH also has an advantage of spectral polishing which provides smooth spectral curves which helps in accurate identification of composition of minerals.Therefore,this study recommends that FLAASH is better than QUAC for atmospheric correction and correct interpretation and identification of composition of any object or minerals.
基金Supported by the State Key Program of National Natural Science Foundation of China(No.60638020)the State Scholarship Fund of the China Scholarship Council(CSC)+1 种基金the National Natural Science Foundation of China(Nos.41321004,41276028,41206006,41306192,41306035)the Natural Science Foundation of Zhejiang Province(No.LY15D060001)
文摘To acquire high-quality operational data products for Chinese in-orbit and scheduled ocean color sensors, the performances of two operational atmospheric correction(AC) algorithms(ESA MEGS 7.4.1 and NASA Sea DAS 6.1) were evaluated over the East China Seas(ECS) using MERIS data. The spectral remote sensing reflectance R_(rs)(λ), aerosol optical thickness(AOT), and ?ngstr?m exponent(α) retrieved using the two algorithms were validated using in situ measurements obtained between May 2002 and October 2009. Match-ups of R_(rs), AOT, and α between the in situ and MERIS data were obtained through strict exclusion criteria. Statistical analysis of R_(rs)(λ) showed a mean percentage difference(MPD) of 9%–13% in the 490–560 nm spectral range, and significant overestimation was observed at 413 nm(MPD>72%). The AOTs were overestimated(MPD>32%), and although the ESA algorithm outperformed the NASA algorithm in the blue-green bands, the situation was reversed in the red-near-infrared bands. The value of α was obviously underestimated by the ESA algorithm(MPD=41%) but not by the NASA algorithm(MPD=35%). To clarify why the NASA algorithm performed better in the retrieval of α, scatter plots of the α single scattering albedo(SSA) density were prepared. These α-SSA density scatter plots showed that the applicability of the aerosol models used by the NASA algorithm over the ECS is better than that used by the ESA algorithm, although neither aerosol model is suitable for the ECS region. The results of this study provide a reference to both data users and data agencies regarding the use of operational data products and the investigation into the improvement of current AC schemes over the ECS.
基金Supported by the National Natural Science Foundation of China,NSFC(Nos.41371346,41271375)the Doctoral Fund of Ministry of Education of China(No.20120076110009)
文摘The purpose of this research is to improve the retrieval accuracy for the suspended sediment concentration(SSC) from in situ and satellite remote sensing measurements in turbid East China estuarine and coastal waters. For this aim, three important tasks are formulated and solved: 1) an estimation of remote-sensing reflectance spectra R_(rs)(λ) after atmospheric correction; 2) an estimation of R_(rs)(λ) from the radiometric signals above the air-water surface; and 3) an estimation of SSC from R_(rs)(λ). Six different models for radiometric R_(rs)(λ) determination and 28 models for SSC versus R_(rs)(λ) are analyzed based on the field observations made in the Changjiang River estuary and its adjacent coastal area. The SSC images based on the above-mentioned analysis are generated for the area.
文摘Parameter optimization of nodes communication is the foundation of underwater sensor networks.The packet size is an important indicator of the impact of communication performance.As a result,the optimal packet size selection is a critical issue in improving the communication performance.This paper aims to make a model reflecting the communication characteristics as the optimization target,because underwater sensor networks have the characteristics of high time delay,high energy consumption and high bit error rate.Finally,simulation experiments and theory have demonstrated the effectiveness and timeliness of simultaneous perturbation stochastic approximation(SPSA) algorithm.
基金supported by the National “863” Program of China(No.2015AA123702)the National Natural Science Foundation of China(Nos.11204318 and61275173)
文摘We employ the in-site automated observation radiometric calibration(AORC) approach to perform vicarious calibration, which does not require the manual efforts of a field team to measure the surface conditions. By using an automated test-site radiometer(ATR), the surface radiance at any moment in time can be obtained. This Letter describes the AORC approach and makes use of data to compute top-of-atmosphere radiance and compare it to measurements from the Moderate Resolution Imaging Spectroradiometer. The result shows that the relative deviation is less than 5% and the uncertainty is less than 6.2%, which indicates that the in-site AORC maintains an accuracy level on par with traditional calibration.
基金supported by the National Natural Science Foundation of China(Nos.60808020 and 61078041)the Natural Science Foundation of Tianjin(Nos.16JCQNJC02100,15JCYBJC51700 and 16JCYBJC15400)the National Science and Technology Support(No.2014BAH03F01)
文摘An optical hydrogen sulfide(H_2S) sensor based on wavelength modulation spectroscopy with the second harmonic(2f) corrected by the first harmonic(1f) signal(WMS-2f/1f) is developed using a distributed feedback(DFB) laser emitting at 1.578 μm and a homemade gas cell with 1-m-long optical path length. The novel sensor is constructed by an electrical cabinet and an optical reflecting and receiving end. The DFB laser is employed for targeting a strong H_2S line at 6 336.62 cm^(-1) in the fundamental absorption band of H_2S. The sensor performance, including the minimum detection limit and the stability, can be improved by reducing the laser intensity drift and common mode noise by means of the WMS-2f/1f technique. The experimental results indicate that the linearity and response time of the sensor are 0.999 26 and 6 s(in concentration range of 15.2—45.6 mg/m^3), respectively. The maximum relative deviation for continuous detection(60 min) of 30.4 mg/m^3 H_2S is 0.48% and the minimum detection limit obtained by Allan variance is 79 μg/m^3 with optimal integration time of 32 s. The optical H_2S sensor can be applied to environmental monitoring and industrial production, and it has significance for real-time online detection in many fields.