In developing countries, urban areas have high building densities with complex building pattern. Therefore, detecting and classifying building data can be challenging as it is difficults to separate between the building and non-building area. The buildings object from coarse ALS data which have noisy content and complexity of urban area were obtained by using information provided by topographic…
The demand for up-to-date spatial data is growing very high in this rapidly changing world. Updating the autoritative spatial data is not always associated with the updating of well established existing spatial data, but it can be extended into the additional collection of new specific themed spatial data. Unforunately, authorities who produce golden standard spatial data cannot fill those nee…
Airbone LIDAR data classification using machine learning algorithm has been a hot topic within the geospasial information community. LIDAR data interpretation based on point clouds is a major domain of automatic mapping. With the rapid development of urban areas, updating database of the geospasial information is urgently needed. Usually, updating of the geospatial information use manual inter…