Traffic signs should provide clear signals for drivers and passengers under various environmental and geographic conditions. In foggy weather, the signal will be disturbed due to light scattering, which will cause obstacles to recognition. This study simulated a foggy environment in the laboratory, used a standard color card as the target, and introduced a colorimeter to record the color coordinates, then calculated the color difference and analyzed the four-color samples’ color properties in different lighting conditions. We found that as the relative visibility increases, the chromatic aberration of the sample will gradually decrease under different lighting conditions and reach zero when the relative visibility is higher than 70%. We found that the green and blue samples have better color coordinate retention capabilities than the fog’s red and yellow. We compared all tested light sources’ performance, and the results showed that 3000K LED and incandescent lamps are better than other light sources. This study will provide a data basis for the study of traffic safety and accident prevention.
The aim of this study is to assess the capability of estimating Leaf Area Index (LAI) from high spatial resolution multi-angular Vis-NIR remote sensing data of WiDAS (Wide-Angle Infrared Dual-mode Line/Area Array Scanner) imaging system by inverting the coupled radiative transfer models PROSPECT-SAILH. Based on simulations from SAILH canopy reflectance model and PROSPECT leaf optical properties model, a Look-up Table (LUT) which describes the relationship between multi-angular canopy reflectance and LAI has been produced. Then the LAI can be retrieved from LUT by directly matching canopy reflectance of six view directions and four spectral bands with LAI. The inversion results are validated by field data, and by comparing the retrieval results of single-angular remote sensing data with multi-angular remote sensing data, we can found that the view angle takes the obvious impact on the LAI retrieval of single-angular data and that high accurate LAI can be obtained from the high resolution multi-angular remote sensing technology.
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