Mobility and transportation are indispensable pillars of modern societyand economy. Traffic, however, is also a source of environmentalpollution and a cause of injuries and deaths. Smart traffic managementattempts to optimize vehicle throughput while still mitigating theseadverse effects. And — traffic keeps on changing, be it on shortor long time scales. Road construction, major events, or disastersrequire rapid reaction. Political developments, like the expansionof the European Union have significantly changed the traffic scenariosin the member states. Therefore, data and models for traffic managementhave to be continuously updated.Today's road systems are equipped with a suite of sensors for monitoringtraffic status: induction loops, overhead radar sensors, video systemsare the most prominent examples. They all deliver accurate, reliable,timely, yet merely point-wise measurements. Airborne and spaceborneimaging systems on the other hand give us synoptic views of complextraffic situations and the associated context. These data are complementaryto the ones of the road sensors and can either be used in researchfor improving traffic models or as information source for operationalmonitoring systems. The context information delivered by imagingsystems is important in non-standard situations, like disasters ormajor events.With the recent advances in sensor technology, the automatic detection,characterization and monitoring of traffic using airborne and spacebornedata has become an emerging field of research. Approaches for vehicledetection and monitoring include not only video cameras but nearlythe whole range of available sensors such as optical aerial and satellitesensors, infrared cameras, SAR systems, and airborne LIDAR. Althoughairborne cameras are already in use and seem to be an obvious choice,satellite systems have entered the resolution regime required forvehicle detection. Sub-metric resolution is available in the opticaldomain. Interferometric radars are able to spot vehicles even atnight-time and under bad weather conditions. The first two satellites,the German TerraSAR-X and the Canadian Radarsat-2, to be equippedwith a vehicle detection capability are ready for launch. Therefore,we believe that this special issue comes at the right time to givean overview of state-of-the-art approaches for detection, tracking,and velocity estimation of moving objects based on air- and spaceborneremote sensing systems.After peer-reviewing the submissions in a team of 18 reviewers, tenpapers have been selected for publication and grouped according tothe sensor technologies used: most notably RGB cameras, infraredsensors, and Synthetic Aperture Radar (SAR) systems.The theme issue starts with an overview paper of Toth and Grejner-Brzezinska.They present and evaluate different methods for acquiring trafficparameters from airborne optical and LIDAR data and add an interestingdiscussion about limitations and potentials of these methods. Then,Reinartz et al. focus on accuracy aspects that must be met duringdata acquisition and data processing. They analyse the complete processingchain for deriving traffic parameters from photogrammetric imagesequences using semi- and fully-automatic techniques. A system forautomatic tracking of vehicles in aerial video images is presentedby Karimi et al. They use optical flow as basic algorithm for tracking,yet combine it with a scale-space approach to get appropriate initialvalues for tracking and for solving the employed differential equations.Finally, the group of approaches exploiting the visual spectral rangeis concluded by the article of Niu. With the incorporation of geometricdeformable models, he employs a common framework to simultaneouslyextract roads as well as vehicles.The paper of Kirchhof and Stilla introduces an approach for automaticvehicle detection and tracking in aerial oblique-view infrared videos.Infrared sensors are in particular appealing for traffic applicationsbecause of their night-imaging capabilities. The motion of the sensoris estimated using projective planar homographies.The final group of papers comprises those approaches which rely onradar and SAR data. Koch et al. present a fully Bayesian approachfor tracking ground-moving targets extracted from airborne radardata. Their approach shows that, through tracking of multiple hypothesesin multiple views, frequently used tracks (“roads‿) can be recoveredand partially occluded areas can be bridged. The paper of Suchandtet al. describes the first spaceborne SAR experiment ever for thedetection of vehicles and estimation of their velocity. InterferometricSAR data acquired during the Shuttle Radar Topography Mission (SRTM)have been processed with a number of modifications compared to standardSAR processing to extract vehicles from along-track interferometricSAR data. The validity of the experiment has been confirmed by ground-truthmeasurements during a SRTM pass. While this paper focuses on thefundamental issues of spaceborne SAR processing, the article of Meyeret al. deals with aspects of theoretical and empirical performancecharacterization of so-called Ground Moving Target Indication (GMTI)approaches when applied to data as, for instance, expected from TerraSAR-X.A special feature of the GMTI approaches developed in this contributionis the incorporation of external a-priori knowledge to set-up conditionalprobability functions, which help to better distinguish between movingand stationary objects. The line of spaceborne GMTI is continuedby the article of Bethke et al. It outlines the TRAMRAD-project thataddresses a visionary concept showing how air- and spaceborne trafficmonitoring could be realized in the future. Based on the experienceof the first phases of the project, which were devoted to spacebornetraffic monitoring, the authors present first studies on a futureairborne SAR system (F-SAR) with specific modes for GMTI.Although not dealing with vehicle traffic in particular, we includedalso work on ship traffic detection into this theme issue. Especiallywith the launch of the ENVISAT satellite, monitoring ship trafficfrom space has gained much attention over the past years and is partlybrought to practice. Due to the relatively low resolution of ENVISATASAR images Lopez-Martinez et al. developed a wavelet-based spotdetection scheme to extract ships from polarimetric SAR data of opensea as well as coastal areas.The articles illustrate the broad variety of approaches and methodsfor air- and spaceborne traffic monitoring. They also confirm thetrend that modeling and analyzing dynamic processes are gaining increasingattention in high resolution remote sensing. In other words: Photogrammetryand Remote Sensing continue their way towards the full exploitationof the 4th dimension, time.     «

Mobility and transportation are indispensable pillars of modern societyand economy. Traffic, however, is also a source of environmentalpollution and a cause of injuries and deaths. Smart traffic managementattempts to optimize vehicle throughput while still mitigating theseadverse effects. And — traffic keeps on changing, be it on shortor long time scales. Road construction, major events, or disastersrequire rapid reaction. Political developments, like the expansionof the European Union have sign...     »