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Automation in 3-dimension (3D) object reconstruction is a relevant and challenging task, both from a practical and scientific point of view. This paper deals with two basic non-planar primitive objects--spatial polygons and 3D closed curves. To achieve 3D information from a pair of images, with known interior and exterior orientations, it is necessary to first extract t2D objects from each of the images separately, then match the objects to find homologues points between them, and finally reconstruct the 3D object. The matching problem between two objects derived from two different images, has a trivial solution: For each point in the first object the corresponding homologous point in the second object can be found by intersecting its epi-polar line and the second object in the second image space. However, because extraction of objects in the image space is performed automatically, the process often fails. For example, when there are a number of intersections per point there is no intersection at all, or there are more points than those existing in the "real" 3D object. To overcome these difficulties, innovative algorithms designed to enable a maximal matching between polygons or closed curves and to find homologues points between them were developed. The algorithms are iterative and are based on the "overlapping criterion" between the objects. According to this criterion, projection of two polygons or closed curves from the image space to any planar surface using the real depths leads to a maximal matching between the objects. The suggested process is based on the well known optimization model called "adjustment by conditions." One of the 2D polygons or closed curves is chosen as the static object and the other is the dynamic object. The unknowns in this model are the real depths of each point in the dynamic object. The points in the dynamic object are assigned a previously calculated average depth. In each iteration, these depths are updated until the conditional equation is optimized. During the iterations the dynamic object "slides" in the direction of the epi-polar line in the image space of the static object. The "slide" rate is not constant because it depends on the varying depths of each point. The iteration process stops when the maximum overlap between the static and dynamic objects is achieved in the image space of the static object. In this paper, the algorithms, the experiments, and the results are detailed. [ABSTRACT FROM AUTHOR]

The natural trend of megacities is to expand from their centers to outlying areas in order to accommodate rapid population growth. Urban areas situated near steep, mountainous terrain or water sources may suffer from landslides, which are one of the most common natural disasters. This paper outlines a new approach in which airborne laser altimetry is used to automatically identify and model landslide occurrences within the acquired data. Dense and accurate light detection and ranging (LiDAR) topographic observations are modeled and compared to an existing digital elevation model (DEM) of the area acquired at an earlier stage. The standard direct superimposition comparison mechanism, which ignores the datasets' inherent interrelations, usually results in an incorrect modeling outcome. A new modeling concept is proposed that initially monitors the inherent global incongruities by georeferencing the two datasets. These incongruities are then utilized in a novel geospatial matching procedure that makes it possible to achieve a precise and correct local modeling mechanism. The hierarchical comparison concept presented accurate results in automatic identification of landslide phenomena, making it possible to precisely assess their morphology. [ABSTRACT FROM AUTHOR]

Growing demand for efficient land use above and below the ground motivates the transition of cadastre and land-management systems from traditional two-dimensional systems to three-dimensional ones. This transition is required especially in sprawling urban areas that are turning into megacities. A major concern in realizing the 3D cadastre vision is tile development of efficient methods for attaching the third dimension to the existing 2D systems. In this regard, airborne laser technology that offers direct acquisition of dense and accurate 3D data appears to be the optimal means for this objective. Integration of surface data into objects and shapes, however, requires handling discrepancies between both datasets, which in turn can lead to incorrect assignment of height information. We present herein a methodology for fusing airborne laser-scanning-derived data into existing 2D cadastral systems. We demonstrate this integration in urban environments comprising high-rise buildings and open areas. Analysis of the data sources shows the necessity for such transformation, while the results demonstrate the appropriateness of the proposed fusion concept. [ABSTRACT FROM AUTHOR]

A pseudo-hydrologic method was developed for road extraction from medium-resolution satellite images. Transformation of image brightness into a Pseudo Digital Elevation Model (PDEM) allows emulation of hydrologic flow. Flow direction and flow accumulation are then calculated for each image pixel using hydrological GIS routines. Road segments are recognized by setting a minimal threshold to the pseudo-flow accumulation. Implementation of the technique to extract major roads and railways from a Spot-panchromatic image yielded high recognition accuracy (90 percent). In another experiment, this technique was used to extract roads in dense urban areas from multispectral IKONOS images. Moderate success (70 percent) was achieved in this task. [ABSTRACT FROM AUTHOR]

An introduction to articles published within the issue is presented, including one by Christodolos Psaltis and Charalabos Ioannidis about the need for an automated, robust, cost-effective, and quick method for informal building monitoring and another by Hartmut Mueller et al on the importance of the availability of integrated spatial information services for policy makers, planners, and managers, as well as citizens and organizations.