Automatic Building Extraction with Multi-sensor Data Using Rule-based Classification
This paper presents a new approach for automatic building extraction using a rule-based classification method with a multi-sensor system that includes light detection and ranging (LiDAR), a digital camera, and a GPS/IMU positioned on the same platform. The LiDAR data (elevation and intensity) and or...
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| Veröffentlicht in: | European journal of remote sensing 2014-01, Vol.47 (1), p.1-18 |
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| container_title | European journal of remote sensing |
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| creator | Uzar, Melis |
| description | This paper presents a new approach for automatic building extraction using a rule-based classification method with a multi-sensor system that includes light detection and ranging (LiDAR), a digital camera, and a GPS/IMU positioned on the same platform. The LiDAR data (elevation and intensity) and ortho-image are used to develop a rule set defined by parameter analyses during the segmentation and fuzzy classification processes to improve the building extraction results. The proposed approach was tested using the data derived from a multi-sensor system in Sivas, Turkey. Moreover, analyses of completeness (81.71%) and correctness (87.64%) were performed by automatic comparison of the extracted buildings and reference data. |
| doi_str_mv | 10.5721/EuJRS20144701 |
| format | Article |
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| ispartof | European journal of remote sensing, 2014-01, Vol.47 (1), p.1-18 |
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| language | eng |
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| source | DOAJ Directory of Open Access Journals; Access via Taylor & Francis (Open Access Collection) |
| subjects | building extraction Buildings Classification Digital cameras fuzzy logic Fuzzy sets Global positioning systems GPS Image segmentation intensity LiDAR rule-based classification Satellite navigation systems segmentation Sensors |
| title | Automatic Building Extraction with Multi-sensor Data Using Rule-based Classification |
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