This paper presents a novel vehicle detection approach for detecting vehicles from static images using color and edges. Different from traditional methods, which use motion features to detect vehicles, this method introduces a new color transform model to find important "vehicle color" for quickly locating possible vehicle candidates. Since vehicles have various colors under different weather and lighting conditions, seldom works were proposed for the detection of vehicles using colors. The proposed new color transform model has excellent capabilities to identify vehicle pixels from background, even though the pixels are lighted under varying illuminations. After finding possible vehicle candidates, three important features, including corners, edge maps, and coefficients of wavelet transforms, are used for constructing a cascade multichannel classifier. According to this classifier, an effective scanning can be performed to verify all possible candidates quickly. The scanning process can be quickly achieved because most background pixels are eliminated in advance by the color feature. Experimental results show that the integration of global color features and local edge features is powerful in the detection of vehicles. The average accuracy rate of vehicle detection is 94.9%.

Ionospheric sporadic-E (Es) activity and global morphology were studied using the 50 Hz signal-to-noise ratio amplitude and excess phase measurements from the FormoSat-3/Constellation Observing System for Meteorology, Ionosphere and Climate (FS3/COSMIC) GPS radio occultation (RO) observations. The results are presented for data collected during the last sunspot cycle from mid-2006 to the end of 2017. The FS3/COSMIC generally performed more than 1000 complete E-region GPS RO observations per day, which were used to retrieve normalized L1-band amplitude standard deviation (SDL1) and relative electron density (N e) profiles successfully. More or less 31% of those observations were identified as Es events based on SDL1 and peak SDL1 altitude criteria. We found that the peak Es-event i values are approximately proportional to the logarithms of the corresponding peak N e differences. Five major geographical zones were identified, in which the seasonal and diurnal Es occurrence patterns are markedly different. These five zones include the geomagnetic equatorial zone (− 5° < magnetic latitude (ML) < 5°), two extended geomagnetic mid-latitude zones (15° < ML < 55°, and − 55° < ML < − 15°), and two auroral zones (70° < ML, and ML < − 70°). The Es climatology, namely its variations with each identified zone, altitude, season, and local time has been documented.

The Global Positioning System/Meteorology (GPS/MET) mission has been the first experiment to use a low Earth orbiting (LEO) satellite (the MicroLab-1) to receive multi-channel Global Positioning System (GPS) carrier phase signals and demonstrate active limb sounding of the Earth's atmosphere and ionosphere by radio occultation technique. Under the assumption of spherical symmetry at the locality of the occultation, the dual-band phase data have been processed to yield ray-path bending angle profiles, which have then been used to yield profiles of refractive index via the Abel integral transform. The refractivity profiles can then, in turn, yield profiles of ionospheric electron density and other atmospheric variables such as neutral atmospheric density, pressure, and temperature in the stratosphere and upper troposphere, and water vapor in the lower troposphere with the aid of independent temperature data. To approach a near real-time process, electron density profiles can also be derived by the Abel transform through the computation of total electron content (TEC) assuming straight-line propagation (neglecting bending). In order to assess the accuracy of the GPS/MET ionospheric electron density retrievals, coincidences of ionosonde data with GPS/MET occultations have been examined. The retrieved electron density profiles from GPS/MET TEC observations have been compared with ionogram inversion results derived from digital ionospheric sounders operated by the National Central University (the Chung-Li digisonde; 24.6• N, 121.0 • E) and by Utah State University (the Bear-Lake dynasonde; 41.9• N, 111.4• W). A fuzzy classification method for the automatic identification and scaling of ionogram traces has been applied to recorded ionograms, and then bottomside ionospheric electron density profiles are determined from true-height analysis. The comparison results show better agreement for both of the derived electron density profiles and the F 2 -layer critical frequency ( f o F 2 ) at midlatitude observations than at low-latitude observations. The rms f o F 2 differences from the GPS/MET retrievals are 0.61 MHz to the Bear-Lake dynasonde measurements and 1.62 MHz to the Chung-Li digisonde measurements.

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