Proceedings Article | 9 October 2018
KEYWORDS: Data modeling, Image segmentation, Remote sensing, Data integration, Data fusion, Synthetic aperture radar, LIDAR, Analytical research, Image processing, Image classification
Remote sensing is one of the most dynamically developing fields of science, and due to its versatility, it can be applicable in many different areas of interest, i.e., biomedical science, forestry, water monitoring, agriculture, urban planning. At present, land cover classification, and precise classification of urban areas is extremely significant regarding environmental protection, particularly in relation to environmental protection and detection and identification of the roofing materials, i.e. roofs covered with asbestos, due to the mandatory removal of asbestos from the environment. Thus the use of advanced remote sensing techniques and various data can significantly accelerate and facilitate this process, depending on the data types and used algorithms. In this paper, the authors present the comparison of object classifications and object identification of chosen urban area- in the north part of Warsaw, Poland. As a basis for the analysis, data from different types of sensors were used, i.e., optical multispectral, SAR data, and LiDAR data. The results of this experiment can be useful when choosing data and methods for accurate and precise land cover classification, and particularly for rapid inventory of roofs’ coverages. The preliminary results shown in the paper demonstrate the potentiality of the joint processing of different remote sensing data.
