Data fusion for high accuracy classification of urban areas

Agnieszka Jenerowicz; Romuald Kaczynski; Katarzyna Siok; Anna Schismak

doi:10.1117/12.2325809

9 October 2018 Data fusion for high accuracy classification of urban areas

Agnieszka Jenerowicz, Romuald Kaczynski, Katarzyna Siok, Anna Schismak

Proceedings Volume 10793, Remote Sensing Technologies and Applications in Urban Environments III; 1079315 (2018) https://doi.org/10.1117/12.2325809
Event: SPIE Remote Sensing, 2018, Berlin, Germany

Abstract

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.

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Agnieszka Jenerowicz, Romuald Kaczynski, Katarzyna Siok, and Anna Schismak "Data fusion for high accuracy classification of urban areas", Proc. SPIE 10793, Remote Sensing Technologies and Applications in Urban Environments III, 1079315 (9 October 2018); https://doi.org/10.1117/12.2325809

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KEYWORDS

Data modeling

Image segmentation

Remote sensing

Data integration

Data fusion

LIDAR

Synthetic aperture radar

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