Yaokai Liu
Chinese Academy of Sciences
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Publication
Featured researches published by Yaokai Liu.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | 2014
Yaokai Liu; Tianxing Wang; Lingling Ma; Ning Wang
Hyperspectral imaging has been widely applied in remote sensing scientific fields. For this study, hyperspectral imaging data covering the spectral region from 400 to 1000 nm were collected from an unmanned aerial vehicle visible/near-infrared imaging hyperspectrometer (UAV-VNIRIS). Theoretically, the spectral calibration parameters of the UAV-VNIRIS measured in the laboratory should be refined when applied to the hyperspectral data obtained from the UAV platform due to variations between the laboratory and actual flight environments. Therefore, accurate spectral calibration of the UAV-VNIRIS is essential to further applications of the hyperspectral data. Shifts in both the spectral center wavelength position and the full-width at half-maximum (FWHM) were retrieved using two different methods (Methods I and II) based on spectrum matching of atmospheric absorption features at oxygen bands near 760 nm and water vapor bands near 820 and 940 nm. Comparison of the spectral calibration results of these two methods over the calibration targets showed that the derived center wavelength and FWHM shifts are similar. For the UAV-VNIRIS observed data used here, the shifts in center wavelength derived from both Methods I and II over the three absorption bands are less than 0.13 nm, and less than 0.22 nm in terms of FWHM. The findings of this paper revealed: 1) the UAV-VNIRIS payload on the UAV platform performed well in terms of spectral calibration; and 2) the applied methods are effective for on-orbit spectral calibration of the hyper spectrometer.
international geoscience and remote sensing symposium | 2012
Jiqiang Zhao; Donghui Xie; Xihan Mu; Yaokai Liu; Guangjian Yan
Digital photography is now the most widely used method to obtain the Fractional Vegetation Cover (FVC) in field measurements. Its accuracy is affected by shooting conditions and classification methods of digital images. In this paper, we chose summer maize as the study plant, used computer simulation method to control the shooting conditions strictly and generate simulated scene. Then a physically based ray-tracing (PBRT) algorithm was used to render the scene to obtain simulated images under different shooting conditions. Supervised classification and CIE L*a*b* color space threshold method were used to extract FVC values from the simulated images. Comparing the extracted FVC values with the scenes true FVC value, we evaluated the FVC accuracy of different shooting conditions and classification methods. The results can act as a guidance of digital photography to obtain the FVC.
Journal of Applied Remote Sensing | 2015
Chuanrong Li; Lingling Ma; Caixia Gao; Lingli Tang; Ning Wang; Yaokai Liu; Yongguang Zhao; Shuai Dou; Dandan Zhang; Xiaohui Li
Abstract To regularly evaluate the optical payload performance (geometric, radiometric, and spatial resolution) and the data quality for high-resolution airborne and satellite imaging systems, two new permanent targets (the knife-edge target and the fan-shaped target) made of gravel and with the advantages of year-round availability, lower maintenance operations, and a long lifetime were established in the Academy of Opto-Electronics Baotou site in China. The spectral properties of these targets are investigated in this study. Note that the anisotropy factor at 550 nm for the white gravel is approximately 6%, 12.5% 16.5%, 17.5%, 11.5%, and 5% at the principal plane for the observer zenith angle of 60 deg, 50 deg, 40 deg, 30 deg, 20 deg, and 10 deg (backscatter), respectively. The corresponding value for the gray gravel is 20.8%, 24.8%, 29.4%, 23.8%, 13%, and 3.7%, respectively, and 62.8%, 65.7%, 59.2%, 40.3%, 22.3%, and 9.0%, respectively, for the black gravel. The anisotropy of the black gravel is larger than that of the gray and white gravel areas. The nonuniformity of the target reflectivity is within 2.5%. Furthermore, a calibration for the optical payloads onboard the GF-1 satellite is performed with the knife-edge target, and the uncertainty analysis demonstrates that the uncertainty for this calibration is < 2.12 % when the relative error for the surface reflectance measurement, the aerosol optical depth, and the total column water vapor are approximately 1%, 10%, and 10%, respectively.
Earth Observing Missions and Sensors: Development, Implementation, and Characterization III | 2014
Caixia Gao; Lingling Ma; Yaokai Liu; Ning Wang; Yonggang Qian; Lingli Tang; Chuanrong Li
Dynamic range and response linearity are two key parameters for impacting the quality of remote sensing image and subsequently the quantitative applications. Due to the space radiation and the degrading of electronic devices, the inflight dynamic range and response linearity of remote sensing payload are subject to change, and is essential to be assessed. Therefore, in this paper, with the aid of the permanent artificial target located in the AOE Baotou site in China, the two parameters for pan-chromatic camera (Pan) and the multi-spectral camera (Band 1-4) onboard GF-1 satellite are assessed with an extrapolation method using the in situ measurements and corresponding images acquired on November 4, 2013. The results show that the low point of the dynamic range for Pan band, Band 1, Band2, Band3 and Band4 is -24.08 W•sr-1m-2μm-1, -52.22 W•sr-1m-2μm-1, -35.20 W•sr-1m-2μm-1, -31.92 W•sr-1m-2μm-1, -24.07 W•sr-1m-2μm- 1 respectively; while the corresponding high point is 271.77 W•sr-1m-2μm-1, 401.58 W•sr-1m-2μm-1, 287.46 W•sr-1m- 2μm-1, 237.33W•sr-1m-2μm-1, 307.49W•sr-1m-2μm-1, respectively; meanwhile, it is demonstrated that all the sensors have a response linearity error of lower than 1%. Moreover, an analysis for this assessment is performed in terms of the uncertainties for surface reflectance measurement (1%), aerosol optical depth (10%), column water vapor (10%), MODTRAN model (1%) and solar irradiance (1%) using a simulation method with the aid of MODTRAN 4.0 model, and a total uncertainty of 2.12% is acquired.
international geoscience and remote sensing symposium | 2011
Yaokai Liu; Ronghai Hu; Xihan Mu; Guangjian Yan
Gap fraction is a very important parameter to the indirect estimation of the true Leaf Area Index. In this paper, we combined the multispectral digital imageries (RGB color imagery and Near-Infrared imagery), which were obtained from a new device called Multispectral Canopy Imager (MCI), to estimate gap fraction. A new method incorporated with CIE L*a*b* color space has also been proposed to segment the multispectral digital imagery. The preliminary results of the estimated gap fraction have been showed in the conclusions section and been proved to be very well.
international geoscience and remote sensing symposium | 2010
Xihan Mu; Yaokai Liu; Guangjian Yan; Yanjuan Yao
Fractional vegetation cover (FVC) is widely relevant for land surface process [1]. In this paper, an algorithm is addressed on FVC retrieval, with the combination of MODIS and Huan Jing satellite (HJ), which is a newly launched constellation by China. In the developed model, we considered angular effect and utilized spatial and temporal information to a great extent. MODIS and HJ surface reflectance products provide data supply for the algorithm and play cooperative roles. A vegetation growth model was introduced to constrain the uncertainty of HJ data in a temporal scale. The uncertainty of using this algorithm was assessed by error propagation theory and field experiments. Retrieved FVC became more reasonable after consideration of the correlation among time series observations and the introduction of more observational data. A priori information is necessary to constrain the inversion process.
Optics Express | 2016
Yonggang Qian; Ning Wang; Lingling Ma; Yaokai Liu; Hua Wu; Bo-Hui Tang; Lingli Tang; Chuanrong Li
Land surface temperature (LST) is one of the key parameters in the physics of land surface processes at local/global scales. In this paper, a LST retrieval method was proposed from airborne multispectral scanner data comparing one mid-infrared (MIR) channel and one thermal infrared (TIR) channel with the land surface emissivity given as a priori knowledge. To remove the influence of the direct solar radiance efficiently, a relationship between the direct solar radiance and water vapor content and the view zenith angle and solar zenith angle was established. Then, LST could be retrieved with a split-window algorithm from MIR/TIR data. Finally, the proposed algorithm was applied to the actual airborne flight data and validated with in situ measurements of land surface types in the Baotou site in China on 17 October 2014. The results demonstrate that the difference between the retrieved and in situ LST was less than 1.5 K. The bais, RMSE, and standard deviation of the retrieved LST were 0.156 K, 0.883 K, and 0.869 K, respectively, for samples.
international geoscience and remote sensing symposium | 2012
Yongsheng Zhou; Qi Wang; Lingling Ma; Chuanrong Li; Lingli Tang; Yaokai Liu
Microwave staring correlation (MSC) imaging is a new type of active high-resolution microwave imaging technique. Image quality assessment is of vital for developing and monitoring any remote imaging system. This paper presented the image quality analysis for this imaging technique by theoretical analysis and simulation. MSC imaging method was introduced firstly. Then, image properties were analyzed and compared with SAR image. Speckle noise effect and side lobe of point target effect, which are intrinsic properties of SAR image, do not exist in MSC image. The quality metrics of MSC image were presented. IRW-Staring time ratio was proposed to describe the image property that image resolution improves with the number of received signals used in the image reconstruction procedure. Finally, the effects of different system parameters on the image quality were investigated via simulation experiments. The analysis results could be helpful for future imaging algorithm development and system design.
international geoscience and remote sensing symposium | 2017
Yonggang Qian; Kun Li; Ning Wang; Lingling Ma; Yaokai Liu; Wei Li; Lu Ren; Shi Qiu; Chuanrong Li; Lingli Tang
This paper addressed the retrieval of land surface temperature (LST) from combined mid-infrared and thermal infrared data of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-Orbiting Partnership (S-NPP). To efficiently remove the effect of the direct solar radiance, a relationship between direct solar radiance and water vapor content, view zenith angle and solar zenith angle is proposed to improve the retrieve accuracy. Then, a split-window algorithm from combined mid-infrared and thermal infrared data is used to correct for the atmospheric effects and retrieve the LST with the aid of emissivity provide by VIIRS product. Finally, comparison of the standard VIIRS LST product and the retrieved LST from the proposed algorithm, a good agreement was shown. Analysis indicated the root mean square error (RMSE) of the LST over these land cover types is 2.04K for desert and 1.84K for vegetation, respectively.
international geoscience and remote sensing symposium | 2017
Yaokai Liu; Chuanrong Li; Lingling Ma; Ning Wang; Yonggang Qian; Lingli Tang
In this study, the automatic reflectance-based method is used to vicarious radiometrically calibrate the satellite optical sensors using the desert target located in the Baotou site in China. The ground reflected radiance of the desert target were collected automatically using an automatic observation system. The reflectance of the desert target was calculated with the radiance collected with the automatic observation system and the total irradiance simulated from MODTRAN code based on the atmospheric parameters. Then, the TOA radiance can be predicted with MODTRAN code based on the calculated desert reflectance. The automatic reflectance-based approach was applied to the Landsat 8/OLI sensors, and the TOA radiances calibrated by our method were also compared with the observed TOA radiance calibrated with on-board calibrator. Preliminary results show a good consistent and the mean relative difference of the multispectral channels is less than 5%. Uncertainty analysis also show that the TOA radiance overall uncertainty is less than 4% due to the source including the atmospheric characteristics, surface characteristics, and the selected calibration model.