Traffic Flow Estimation from Single Satellite Images

Exploiting a special focal plane assembly of most satellites allows for the extraction of moving objects from only one multispectral satellite image. Push broom scanners as used on most earth observation satellites are composed of usually more than one CCD line – mostly one for multispectral and one for panchromatic acquisistion. Some sensors even have clearly separated CCD lines for different multispectral channels. Such satellites are for example WorldView-2 or RapidEye. During the Level-0-processing of the satellite data these bands get coregistered on the same ground level which leads to correct multispectral and exactly fitting pan images. But if objects are very high above the coregistering plane or are moving significantly in between the short acquisition time gap these objects get registered on different points in different channels. Measuring relative distances of these objects between these channels and knowing the acquisition time gap allows retrieving the speed of the objects or the height above the coregistering plane. In this paper we present our developed method in general for different satellite systems – namely RapidEye, WorldView-2 and the new Pl´eiades system. The main challenge in most cases is nevertheless the missing knowledge of the acquisition time gap between the different CCD lines and often even of the focal plane assembly. So we also present our approach to receive a coarse focal plane assembly model together with a most likely estimation of the acqusition time gaps for the different systems

From Airborne Digital Raw Data to Image Maps

Recent airborne remote sensing applications show a tendency from an interpretation of single image strips to an evaluation of extended image maps for further usage in data fusion and GIS applications. Most of the problems during the mosaicking process are caused by geometric ortho-rectification errors, radiation variations across the single image strips and between adjacent image strips. The proposed procedure for generating ortho-rectified image maps consists of the following three steps. Within an image strip radiometric normalization is performed using an image-based empirical radiometric correction method, which accounts for sensor viewing angle effects. Individual strips are then ortho-rectified applying the direct georeferencing approach by using the onboard IGI CCNS/AEROcontrol-IIb system for the GPS/IMU integration and a digital elevation model. To remove the between-strip radiometric variations we propose to use a radiometric correction method, which is based on the information contained in the overlapping region of the image strips. The processing of data acquired by airborne multi-spectral scanner DAEDALUS AADS 1268 ATM show the effectiveness and potential of the proposed method especially for the thematic analysis applications

Automatic traffic monitoring with an airborne wide-angle digital camera system for estimation of travel times

Knowledge of accurate travel times between various origins and destinations is a valuable information for daily commuters as well as for security related organizations (BOS) during emergencies, disasters, or big events. In this paper, we present a method for automatic estimation of travel times based on image series acquired from the recently developed optical wide angle frame sensor system (3K = “3-Kopf”), which consists of three non-metric off-the-shelf cameras (Canon EOS 1Ds Mark II, 16 MPixel). For the calculation of overall travel times, we sum up averaged travel times derived from individual vehicle velocities to pass defined road segments. The vehicle velocities are derived from vehicle positions in two consecutive geocoded images by calculating its distance covered over time elapsed. In this context, we present an automatic image analysis method to derive vehicle positions and vehicle distances involving knowledge based road detection algorithm followed by vehicle detection and vehicle tracking algorithms. For road detection, we combine an edge detector based on Deriche filters with information from a road database. The extracted edges combined with the road database information have been used for road surface masking. Within these masked segments, we extract vehicle edges to obtain small vehicle shapes and we select those lying on the road. For the vehicle tracking, we consider the detected vehicle positions and the movement direction from the road database which leads to many possible matching pairs on consecutive images. To find correct vehicle pairs, a matching in the frequency domain (phase correlation) is used and those pairs with the highest correlation are accepted. For the validation of the proposed methods, a flight and ground truth campaign along a 16 km motorway segment in the south of Munich was conducted in September 2006 during rush hour

Spectral Signature of Forest Damage.

The change of spectral signature by forest damage is analysed for spruce and beech. Reflectance spectra of branches and components like individual needles, leaves etc from trees of different degrees of damage were measured in the 400 to 780 nm region at different fields of view. A linear superposition model is used to simulate averaged branch spectra from the spectral signature of components. The histological background of the change of spectral signature is discussed