Determining urban trees carbon storage using LiDAR data: a case study in Istanbul with a new Python plugin: trees carbon storage with a new Python plugin

Understanding the carbon capacity of urban forests is important for combating climate change and supporting city policies. This study examined two models: the CUFR Tree Carbon Calculator (CTCC) used in the US and the Turkey-Specific Literature-Based Model (TLBM). It uses Light Detection and Ranging (LiDAR) and field data for analysis, which is the first study conducted under Turkish conditions. The findings showed a high correlation (R 2 ≥ 0.89) between the two models in absolute estimates, indicating that the models have similar trends. However, there were significant differences between the two models, both in total values and based on species. This revealed that the CTCC model is applicable under Turkish conditions, but its performance may vary depending on the species and the data source. Another part of this study is the introduction of the Python-based TreeCarbon plugin, which practically calculates the carbon stock within individual trees. This tool operates in both desktop and mobile versions, and, thanks to its simple interface, provides ease of use for multidisciplinary users with limited technical expertise. The mobile version, with its integration of basic tree parameters, enables instant results to be produced in the field. This research further emphasizes that model performance depends on species and local conditions, thereby supporting the development of carbon-neutral city policies.