Publication: Path loss prediction for low-rise buildings with image classification on 2-D aerial photographs
Issued Date
2009-01-01
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ISSN
15598985
10704698
10704698
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2-s2.0-70349555764
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Mahidol University
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SCOPUS
Bibliographic Citation
Progress in Electromagnetics Research. Vol.95, (2009), 135-152
Suggested Citation
S. Phaiboon, P. Phokharatkul Path loss prediction for low-rise buildings with image classification on 2-D aerial photographs. Progress in Electromagnetics Research. Vol.95, (2009), 135-152. doi:10.2528/PIER09061101 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/27572
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Title
Path loss prediction for low-rise buildings with image classification on 2-D aerial photographs
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Abstract
This paper presents a radio wave propagation prediction method for low-rise buildings using 2-D aerial images taken from the actual areas. The prediction procedure was done in three steps. Firstly, the images were classified in order to identify the objects by Color Temperature Properties with Maximum Likelihood Algorithm (CTP MLA). The objects in the images consist of buildings, trees, roads, water and plain. These objects influence wave propagation highly. The MLA classification is a common supervised image segmentation technique in remote sensing domain. However it still needs human editing in case of classification errors. Secondly, the appropriate path loss models were selected to predict path loss. The original Xia path loss model was modified to include the effects of airy buildings and vegetation around the buildings. Finally, preliminary tests provide a better solution compared with measured path losses with the root mean square error (RMSE) and maximum relative error (MRE) of 3.47 and 0.31, respectively. Therefore, the positions for micro-cell base stations could be designed on a 2-D aerial map.