Taiwan: Three researchers at the National Central University (Jhongli, Taiwan) developed way of identifying altered features of urban areas by comparing existing building models with new LiDAR data points and aerial images. The researchers, Liang-Chien Chen, Li-Jer Lin, and Wen-Chi Chang, have improved on current methods in which changes are usually measured by spectral analysis of aerial images and LiDAR data.
In their technique, they sought to integrate the LiDAR data and aerial images into a single system that detects changes in a landscape by comparing old 3D building models with newly obtained imagery. To improve accuracy, they use a double-thresholding strategy.
To compare images taken at different times, researchers first registered the LiDAR data, aerial images, and building models to the same scale. They then determined any alterations by examining spectral information from aerial images, height differences between the LiDAR points and the building models and linear features of the aerial images. Spectral information helped to locate vegetation to exclude areas that contain no manmade structures. Next, they used LiDAR to detect the points that represent the roof planes of buildings. The height differences between these points and the building models become our primary indicators of new building features. They use line features of the aerial images for further refinement.
Based-on the comparison of data, images, and models; researchers categorised their findings as ‘unchanged,’ ‘main-structure changed,’ or ‘microstructure alterations.’ Since height difference was the major indicator of variation, they employed a double-thresholding strategy—e.g., setting an upper bound of 3m and a lower bound of 1m—to detect obviously changed and unchanged areas in buildings. The line-feature comparisons helped to further identify the areas of interest (the data set between the two thresholds), which are then singled out for additional study.