Abstract
This study evaluates a methodology for using IKONOS stereo imagery to determine the height and position of buildings in dense residential areas. The method was tested on three selected sites in an area of 8.5 km long by 7 km wide and covered by two overlapping (97% overlap) IKONOS images. The images were oriented using rational function models in addition to ground control points. Buildings were identified using an algorithm that utilized the Digital Surface Model (DSM) extracted from the images in addition to the image spectral properties. A digital terrain model was used with the DSM created from the IKONOS stereo imagery to compute building heights. Positional accuracy and building heights were evaluated using corner coordinates extracted from topographic maps and surveyed building heights. The results showed that the average building detection percentage for the test area was 82.6% with an average missing factor of 0.16. When the image rational polynomial coefficients were used to build the image model, results showed a horizontal accuracy of 2.42 and 2.39 m Root Mean Square Error (RMSE) for the easting and northing coordinates, respectively. When ground control points were used, the results improved to the sub-meter level. Differences between building heights extracted from the image model and the corresponding heights obtained through traditional ground surveying had a RMSE of 1.05 m.
Highlights
Building extraction from high resolution satellite imagery has been an active research topic for the last two decades
We developed a method for automatic building extraction that is contingent upon image classification and a digital surface model extracted from IKONOS stereo imagery
We examined the use of IKONOS stereo imagery to extract 3D building information in regards to height and planimetric position
Summary
Building extraction from high resolution satellite imagery has been an active research topic for the last two decades. The extraction of three-dimensional (3D) building information from high resolution imagery using aerial photos [1], high resolution satellite images [2,3,4], and combined LiDAR and aerial image data [5,6,7] has been popular. Due to their high resolution, panchromatic aerial images have been used as a single data source [8,9]. Fraser et al [10] compared buildings extracted from IKONOS imagery with those obtained using black and white aerial photographs
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