Academic Journal
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.
| Title: | 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. |
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| Authors: | Doğan, Nuray Baş |
| Source: | Open Geosciences; Jan2026, Vol. 18 Issue 1, p1-15, 15p |
| Subject Terms: | Carbon sequestration, LIDAR, Phenotypic plasticity, Climate change, Cities & towns, Python programming language, Urban trees, Carbon sequestration in forests |
| Geographic Terms: | Istanbul (Türkiye) |
| Abstract: | 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 (R2 ≥ 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. [ABSTRACT FROM AUTHOR] |
| Copyright of Open Geosciences is the property of De Gruyter and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Complementary Index |
| FullText | Links: – Type: other Text: Availability: 0 |
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| Header | DbId: edb DbLabel: Complementary Index An: 191185580 RelevancyScore: 1041 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 1041.06604003906 |
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| Items | – Name: Title Label: Title Group: Ti Data: 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. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Doğan%2C+Nuray+Baş%22">Doğan, Nuray Baş</searchLink> – Name: TitleSource Label: Source Group: Src Data: Open Geosciences; Jan2026, Vol. 18 Issue 1, p1-15, 15p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Carbon+sequestration%22">Carbon sequestration</searchLink><br /><searchLink fieldCode="DE" term="%22LIDAR%22">LIDAR</searchLink><br /><searchLink fieldCode="DE" term="%22Phenotypic+plasticity%22">Phenotypic plasticity</searchLink><br /><searchLink fieldCode="DE" term="%22Climate+change%22">Climate change</searchLink><br /><searchLink fieldCode="DE" term="%22Cities+%26+towns%22">Cities & towns</searchLink><br /><searchLink fieldCode="DE" term="%22Python+programming+language%22">Python programming language</searchLink><br /><searchLink fieldCode="DE" term="%22Urban+trees%22">Urban trees</searchLink><br /><searchLink fieldCode="DE" term="%22Carbon+sequestration+in+forests%22">Carbon sequestration in forests</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Istanbul+%28Türkiye%29%22">Istanbul (Türkiye)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: 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<superscript>2</superscript> ≥ 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. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Open Geosciences is the property of De Gruyter and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1515/geo-2025-0932 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 15 StartPage: 1 Subjects: – SubjectFull: Istanbul (Türkiye) Type: general – SubjectFull: Carbon sequestration Type: general – SubjectFull: LIDAR Type: general – SubjectFull: Phenotypic plasticity Type: general – SubjectFull: Climate change Type: general – SubjectFull: Cities & towns Type: general – SubjectFull: Python programming language Type: general – SubjectFull: Urban trees Type: general – SubjectFull: Carbon sequestration in forests Type: general Titles: – TitleFull: 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. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Doğan, Nuray Baş IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: Jan2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 23915447 Numbering: – Type: volume Value: 18 – Type: issue Value: 1 Titles: – TitleFull: Open Geosciences Type: main |
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