Mojca Kosmatin Fras

Automated building extraction from IKONOS images in suburban areas

The article addresses automatic building extraction from IKONOS images in suburban areas. In the proposed approach, we used a stereo pair of IKONOS images. Automatic photogrammetric methods of image matching were used to generate a digital surface model (DSM) and a digital elevation model. In further processing, single-image methods were used. The orthophotos of individual bands were created. The initial building mask was generated from the calculated normalized DSM (nDSM). The calculated normalized difference vegetation index and the road data extracted from the existing topographical database were used to remove vegetation and traffic surfaces. The mask was further improved with our own combination of methods based on non-linear diffusion filtering, unsupervised classification, colour segmentation and region growing. The final mask was vectorized using the Hough transform. Compared with a reference building database, 83.2% of the buildings in the test area were detected using the proposed approach with a quality percentage (how likely a building pixel produced by an automatic approach is correct) of 49.46.

Automatic Orthorectification of High-Resolution Optical Satellite Images Using Vector Roads

This paper presents a completely automatic processing chain for orthorectification of optical pushbroom sensors. The procedure is robust and works without manual intervention from raw satellite image to orthoimage. It is modularly divided in four main steps: metadata extraction, automatic ground control point (GCP) extraction, geometric modeling, and orthorectification. The GCP extraction step uses georeferenced vector roads as a reference and produces a file with a list of points and their accuracy estimation. The physical geometric model is based on collinearity equations and works with sensor-corrected (level 1) optical satellite images. It models the sensor position and attitude with second-order piecewise polynomials depending on the acquisition time. The exterior orientation parameters are estimated in a least squares adjustment, employing random sample consensus and robust estimation algorithms for the removal of erroneous points and fine-tuning of the results. The images are finally orthorectified using a digital elevation model and positioned in a national coordinate system. The usability of the method is presented by testing three RapidEye images of regions with different terrain configurations. Several tests were carried out to verify the efficiency of the procedure and to make it more robust. Using the geometric model, subpixel accuracy on independent check points was achieved, and positional accuracy of orthoimages was around one pixel. The proposed procedure is general and can be easily adapted to various sensors.

Transition from 2D to 3D real property cadastre: The case of the Slovenian cadastre

Abstract The land administration system, providing a mechanism to support the management of real properties, is one of the most crucial infrastructures of any country. This infrastructure is needed to support planning and implementation of land-related policies, and in general to support human decisions and activities in our environment. The fundamental part of a modern land administration system is the land cadastre. Over the last decade, the demand for three-dimensional (3D) cadastre has increased significantly worldwide. The physical and legal complexities of the built and natural environment prompt new concepts and definitions of real property units in order to meet the demands of a todays society and to balance private and public spatial interests. Particularly in urban areas, including other areas with intensive human interventions into space, there is a tendency to use space above and below the Earths surface, above and below structures, etc. Complex 3D objects cannot be defined and registered as cadastral objects in the traditional 2D land cadastre and represented in a 2D cadastral map. For this purpose, next to the land cadastre, in 2000, Slovenia introduced the building cadastre. From the juridical point of view, the current cadastral system is not sufficient for all 3D situations. In this paper, we discuss upgrade possibilities of data models of the land cadastre and building cadastre to introduce a unique 3D real property cadastre in Slovenia. We believe that the data available in the current cadastres will significantly contribute toward the 3D real property cadastre and 3D graphical representation of cadastral data; nevertheless, some additional data are needed. The minimum data required could be provided already through the current cadastral procedures.

Classification based building detection from GeoEye-1 images

High-resolution satellite imagery is being increasingly employed for large-scale topographic mapping, and especially for updating spatial databases. GeoEye-1 is one of the latest in a series of commercial high-resolution earth observation satellites. The paper presents a method for building detection from GeoEye-1 imagery. The initial building mask was created with supervised classification based on the object approach. In the next steps the building mask was enhanced employing, unsupervised classification and region growing. The final results of the building detection are evaluated.

What about topography? Status and quality of topographic data in Slovenia

Topographic data, an important part of the National Spatial Data Infrastructure, have been given serious attention since Slovenias independence. It has become publicly available, updated and harmonised. Financing of topographic data in Slovenia has significantly decreased over the previous decade. As a result, the present status is far from acceptable or expected. The current status of the topographic data, as well as its quality and usability for potential users is discussed in this article. The overview starts with basic source data, aerial surveys, photographs and orthophotos. The quality of orthophotos largely depends on the DTM quality. Topographic data is nowadays organised in thematic datasets (geographical names, building cadastre, etc.) or joined in datasets of different levels of accuracy and details. The status in Slovenia is compared to those in some neighbouring and other comparable countries.