Automated Tree Detection Using Image Processing and Multisource Data
This paper presents a method for the automatic detection and assessment of trees and tree-covered areas in Katowice, the capital of the Upper Silesian Industrial Region in southern Poland. The proposed approach utilizes satellite imagery and height maps, employing image-processing techniques and int...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/2/667 |
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| author | Grzegorz Dziczkowski Barbara Probierz Przemysław Juszczuk Piotr Stefański Tomasz Jach Szymon Głowania Jan Kozak |
| author_facet | Grzegorz Dziczkowski Barbara Probierz Przemysław Juszczuk Piotr Stefański Tomasz Jach Szymon Głowania Jan Kozak |
| author_sort | Grzegorz Dziczkowski |
| collection | DOAJ |
| description | This paper presents a method for the automatic detection and assessment of trees and tree-covered areas in Katowice, the capital of the Upper Silesian Industrial Region in southern Poland. The proposed approach utilizes satellite imagery and height maps, employing image-processing techniques and integrating data from various sources. We developed a data pipeline for gathering and pre-processing information, including vegetation data and numerical land-cover models, which were used to derive a new method for tree detection. Our findings confirm that automatic tree detection can significantly enhance the efficiency of urban tree management processes, contributing to the creation of greener and more resident-friendly cities. |
| format | Article |
| id | doaj-art-ad1e7c81c1be43d89df421b841883d55 |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-ad1e7c81c1be43d89df421b841883d552025-01-24T13:20:22ZengMDPI AGApplied Sciences2076-34172025-01-0115266710.3390/app15020667Automated Tree Detection Using Image Processing and Multisource DataGrzegorz Dziczkowski0Barbara Probierz1Przemysław Juszczuk2Piotr Stefański3Tomasz Jach4Szymon Głowania5Jan Kozak6Department of Machine Learning, University of Economics in Katowice, 1 Maja 50, 40-287 Katowice, PolandDepartment of Machine Learning, University of Economics in Katowice, 1 Maja 50, 40-287 Katowice, PolandDepartment of Machine Learning, University of Economics in Katowice, 1 Maja 50, 40-287 Katowice, PolandDepartment of Machine Learning, University of Economics in Katowice, 1 Maja 50, 40-287 Katowice, PolandDepartment of Machine Learning, University of Economics in Katowice, 1 Maja 50, 40-287 Katowice, PolandDepartment of Machine Learning, University of Economics in Katowice, 1 Maja 50, 40-287 Katowice, PolandDepartment of Machine Learning, University of Economics in Katowice, 1 Maja 50, 40-287 Katowice, PolandThis paper presents a method for the automatic detection and assessment of trees and tree-covered areas in Katowice, the capital of the Upper Silesian Industrial Region in southern Poland. The proposed approach utilizes satellite imagery and height maps, employing image-processing techniques and integrating data from various sources. We developed a data pipeline for gathering and pre-processing information, including vegetation data and numerical land-cover models, which were used to derive a new method for tree detection. Our findings confirm that automatic tree detection can significantly enhance the efficiency of urban tree management processes, contributing to the creation of greener and more resident-friendly cities.https://www.mdpi.com/2076-3417/15/2/667image processingdata integrationurban forestryremote sensingsustainable development |
| spellingShingle | Grzegorz Dziczkowski Barbara Probierz Przemysław Juszczuk Piotr Stefański Tomasz Jach Szymon Głowania Jan Kozak Automated Tree Detection Using Image Processing and Multisource Data Applied Sciences image processing data integration urban forestry remote sensing sustainable development |
| title | Automated Tree Detection Using Image Processing and Multisource Data |
| title_full | Automated Tree Detection Using Image Processing and Multisource Data |
| title_fullStr | Automated Tree Detection Using Image Processing and Multisource Data |
| title_full_unstemmed | Automated Tree Detection Using Image Processing and Multisource Data |
| title_short | Automated Tree Detection Using Image Processing and Multisource Data |
| title_sort | automated tree detection using image processing and multisource data |
| topic | image processing data integration urban forestry remote sensing sustainable development |
| url | https://www.mdpi.com/2076-3417/15/2/667 |
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