In applications of high-resolution spaceborne imagery, different users have different requirements for accuracy and the form of the product. The commercial high-resolution satellites use their own geometric product level to adapt to different users. But various satellites have different geometric product levels. To establish a suitable optical pushbroom satellite geometry product level becomes the key to the development of optical satellite technical issues placed before us. This paper presents a geometric product level as standard and the production methods of the Sensor Corrected level and the Geocoded Ellipsoid Corrected level are given based on the standard. A case study using the ALOS satellite has been used to test the methods. Experimental results show that the Sensor Corrected Level Product performs very well in image stitching, and the Geocoded Ellipsoid Corrected Level Product solves the low accuracy of the RFM (rational function model) caused by the jumping of exterior orientation elements.
Using simultaneously collected remote sensing data and field measurements, this study firstly assessed the consistency and applicability of China high-resolution earth observation system satellite 1 (GF-1) wide field of view (WFV) camera, environment and disaster monitoring and forecasting satellite (HJ-1) charge coupled device (CCD), and Landsat-8 operational land imager (OLI) data for estimating the leaf area index (LAI) of winter wheat via reflectance and vegetation indices (VIs). The accuracies of these LAI estimates were then assessed through comparison with an empirical model and the PROSAIL radiative transfer model. The effects of radiation calibration, spectral response functions, and spatial resolution on discrepancies in the LAI estimates between the different sensors were also analyzed. The results yielded the following observations: (1) The correlation between reflectance from different sensors is relative good, with the adjusted coefficients of determination (R2) between 0.375 to 0.818. The differences in reflectance are ranging from 0.002 to 0.054. The correlation between VIs from different sensors is high with the R2 between 0.729 and 0.933. The differences in the VIs are ranging from 0.07 to 0.156. These results show the three sensors' images can all be used for cross calibration of the reflectance and VIs. (2) The four VIs from the three sensors are all demonstrated to be highly correlated with LAI (R2 between 0.703 and 0.849). The linear models associated with the 2-band enhanced vegetation index (EVI2), which feature the highest R2 (higher than 0.746) and the lowest root mean square errors (RMSE) (less than 0.21), were selected to estimate the winter wheat LAI. The accuracy of the estimated LAI from Landsat-8 was the highest, with the relative errors (RE) of 2.18% and an RMSE of 0.13, while the HJ-1 was the lowest, with the RE of 2.43% and the RMSE of 0.15. (3) The inversion errors in the different sensors' LAI estimates using the PROSAIL model are small. The accuracy of the GF-1 is the highest with the RE of 3.44%, and the RMSE of 0.22, whereas that of the HJ-1 is the lowest with the RE of 4.95%, and the RMSE of 0.26. (4) The effects of the spectral response function and radiation calibration for the different sensors are small and can be ignored, but the effects of spatial resolution are significant and must be taken into consideration in practical applications.
In virtue of its special merit,laser-fuze has an increasingly extensive application on air-to-air missile.How to settle the conflict between target identification and anti-jamming on the premise of meeting certain probability of fuze actuation is a major problem faced on any laser-fuze designer.In this article,a new method is presented from system disign angle.
Dataset used in the paper "Estimation of Terrestrial Water Storage variations in Sichuan-Yunnan region from GPS observations using Independent Component Analysis"
To address the issue of widespread missing chlorophyll-a (Chl-a) concentration data in ocean water caused by environmental factors such as solar radiation and cloud cover during satellite remote sensing monitoring, this study focused on the Beibu Gulf area and used the empirical orthogonal function data interpolation method (DINEOF) based on Himawari-8 chlorophyll-a daily product data to interpolate the missing data. The study made adjustments to the original interpolation method by modifying the number of time sequences in the reconstructed dataset to improve the accuracy and efficiency of the interpolation reconstruction. In testing the accuracy of the adjusted DINEOF reconstruction method, the study replaced the existing data in the research area with null values to represent missing data for interpolation reconstruction. The results showed that the adjustments made to the research method improved the accuracy and efficiency of the interpolation reconstruction, with MAE, RMSE and R2 values of 0.372 mg/m3 , 0.522 mg/m3 , and 0.917, respectively.
Considering that the atmospheric refraction and aberration of light (AOL) bend the path of light and thus affect the geolocation accuracy, a rigorous imaging geometric model with corrections of atmospheric refraction and AOL is proposed to improve the accuracy of geolocation for GaoFen-7 (GF-7) images without ground control points (GCPs). The correction of atmospheric refraction is calculated using simplified two-layer atmospheric refraction model, while the correction of AOL is calculated using the satellite altitude and velocity. Then, the rigorous imaging geometric model is refined with both corrections. 68 scenes of GF-7 satellite backward images in ten regions with different roll off-nadir angles are selected to compare and detect the variation of accuracy with and without the corrections. The results show that the average geolocation accuracy is improved by 0.14 meters in object space, and about 0.20 pixels in image space if the corrections of atmospheric refraction and AOL are taken into the geometric model. The average improvement of RMSEs is about 1.00 pixels and the ratio of improved scenes reaches 88.89% when the roll off-nadir angle is larger than 15°, whereas there is no need to consider atmospheric refraction and AOL if the off-nadir angle is smaller than 5°. The methodology and results can provide support for the need of corrections for high-precision positioning, and the promotion of GF-7 imagery.
This paper evaluates the flow field characteristics of a bottom-supported aquaculture platform under uniform flow based on numerical simulation and model experiments. A numerical method combined with the realizable k-ε turbulence model and the porous media model is established to describe the flow. The fish net is simplified by a porous media and the main framework is modelled as rigid wall conditions. Model tests are conducted, and the experiment data validate numerical simulation results, exhibiting good agreement. The influences of some key parameters on the flow field are investigated by the present numerical model, such as incoming flow velocity, angle of attack, and with or without nets. The findings highlight that the double-layer nets will promote velocity attenuation and create a low-velocity wake region downstream of the platform. Conversely, the impact of the bottom fish net on the velocity attenuation is deemed insignificant. The angle of attack has an obvious effect on velocity distribution but has little effect on wake width, and a higher incoming flow velocity will lead to greater velocity attenuation. It should be noted that the tail vortices generated by the oversized centre column may affect the flow field and structural safety.
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