Automatic Building Extraction with Multi-sensor Data Using Rule-based Classification
| Autor: | Melis Uzar |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Atmospheric Science
business.product_category Fuzzy classification Applied Mathematics 0208 environmental biotechnology Reference data (financial markets) Rule-based system 02 engineering and technology 010502 geochemistry & geophysics computer.software_genre 01 natural sciences Fuzzy logic 020801 environmental engineering Geography Lidar Inertial measurement unit Assisted GPS Data mining Computers in Earth Sciences business computer 0105 earth and related environmental sciences General Environmental Science Digital camera |
| Zdroj: | European Journal of Remote Sensing. 47:1-18 |
| ISSN: | 2279-7254 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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