The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLVIII-M-7-2025
https://doi.org/10.5194/isprs-archives-XLVIII-M-7-2025-181-2025
https://doi.org/10.5194/isprs-archives-XLVIII-M-7-2025-181-2025
24 May 2025
 | 24 May 2025

Streamlining urban tree data collection: a case study on Olomouc housing estates

Matěj Kašpar and Aleš Létal

Keywords: Remote Sensing, Deep Learning, Tree Mapping, Greenery, UAS

Abstract. Data collection on urban greenery plays a key role in its management and in evaluating the benefits it provides to society, including ecological, aesthetic, and health-related advantages. To manage urban greenery effectively, it is essential to seek ways to optimize the process of its inventory and assessment. Technological advancements in data collection methods offer new possibilities for making these processes more efficient. The aim of this study was to utilize and integrate available technologies and methods for the inventory of urban greenery and to evaluate their effectiveness. The results show that the combination of drone imagery with open-source software tools and data provides an accurate and cost-effective solution for monitoring urban vegetation. In conclusion, the proposed methodology enables efficient and economically beneficial management of urban greenery, which supports its broader implementation in urban areas.

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