AERIAL IMAGE SEGMENTATION IN URBAN ENVIRONMENT FOR VEGETATION MONITORING
| Autor: | J. Martins, D. A. Sant’Ana, J. Marcato Junior, H. Pistori, W. N. Gonçalves |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: | |
| Zdroj: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-3-W12-2020, Pp 349-353 (2020) |
| Druh dokumentu: | article |
| ISSN: | 1682-1750 2194-9034 |
| DOI: | 10.5194/isprs-archives-XLII-3-W12-2020-349-2020 |
| Popis: | Urban forests are crucial for the population well-being and improvement of the quality of life. For example, they contribute to the rain damping and to the improvement of the local climate. Therefore a correct and accurate mapping of this resource is fundamental for its correct management. We investigated a method that combines machine learning and SLIC superpixel techniques using different Superpixels (k) number to map trees in the metropolitan region of the municipality of Campo Grande-MS, Brazil with aerial orthoimages with GSD (Ground Sample Distance) of 10 cm. The combination of superpixels and machine learning algorithms were checked out with a set of weka classifiers and achieved good results i.e. F-1 %98.2, MCC %88.4 and Accuracy of %96.8, supporting that this method is efficient when used for urban trees mapping. |
| Databáze: | Directory of Open Access Journals |
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