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The study observed a positive correlation between the illuminant color temperatures and the optimal display color temperatures (r=0.89, p<0.05). The subjects were asked to assess the optimal level of the display color temperatures based on their mental representation of the ideal white point. The illuminant conditions varied with combinations of color temperature (2600 to 20,100 K) and illuminance level (30 to 3100 lx) that simulated daily lighting experiences. The display stimuli were composed of 14 nuanced whites varying in color temperature from 2900 to 18,900 K. For visual examination, subjects evaluated 14 display stimuli presented on the Samsung Galaxy S3 under 19 ambient illuminants. The study aims to investigate the user-preferred color temperature adjustment for smartphone displays by observing the effect of the illuminant's chromaticity and intensity on the optimal white points preferred by users. User-preferred color temperature adjustment for smartphone display under varying illuminants Our results were very promising, indicating that quantitative UAV based remote sensing could be operational in diverse conditions, which is prerequisite for many environmental remote sensing applications. In the corrected data, the homogeneity was 0.10-0.12 with a correction based on broadband irradiance measured in UAV, 0.07-0.09 with a correction based on spectral irradiance measurement on ground, and 0.05-0.08 with a radiometric block adjustment based on image data. Internal homogeneity of the original image data (average coefficient of variation in overlapping images) was 0.14-0.18. We tested the methods in a precision agriculture application using realistic data collected in difficult illumination conditions. A new method that is based on insitu measurement of irradiance either in UAV platform or in ground was developed. Our objective was to investigate methods for quantitative radiometric processing of images taken under varying illumination conditions, thus expanding the range of weather conditions during which successful imaging flights can be made. On field the weather conditions vary and the UAV operator often has to decide between flight in sub optimal conditions and no flight. These images can be assembled in spectral data cubes with stereoscopic overlaps. This new technology produces tens of successive images of the scene at different wavelength bands in very short time. For applications requiring more detailed spectral information about the surface, a new Fabry-Perot interferometer based spectral imaging technology has been developed. For applications requiring aerial images, a simple consumer camera provides acceptable data. The progress of small payload UAVs has introduced greater demand for light weight aerial payloads. Rapidly developing unmanned aerial vehicles (UAV) have provided the remote sensing community with a new rapidly deployable tool for small area monitoring. Spectral Imaging from Uavs Under Varying Illumination Conditions