Version 1
: Received: 31 October 2023 / Approved: 1 November 2023 / Online: 1 November 2023 (04:10:24 CET)
How to cite:
Gafurov, A.; Prokhorov, V.; Kozhevnikova, M.; Usmanov, B. Forest Communities Spatial Modeling as a Basis for Assessing the Sequestration Potential of Ecosystems (Republic of Tatarstan, Russia). Preprints2023, 2023110008. https://doi.org/10.20944/preprints202311.0008.v1
Gafurov, A.; Prokhorov, V.; Kozhevnikova, M.; Usmanov, B. Forest Communities Spatial Modeling as a Basis for Assessing the Sequestration Potential of Ecosystems (Republic of Tatarstan, Russia). Preprints 2023, 2023110008. https://doi.org/10.20944/preprints202311.0008.v1
Gafurov, A.; Prokhorov, V.; Kozhevnikova, M.; Usmanov, B. Forest Communities Spatial Modeling as a Basis for Assessing the Sequestration Potential of Ecosystems (Republic of Tatarstan, Russia). Preprints2023, 2023110008. https://doi.org/10.20944/preprints202311.0008.v1
APA Style
Gafurov, A., Prokhorov, V., Kozhevnikova, M., & Usmanov, B. (2023). Forest Communities Spatial Modeling as a Basis for Assessing the Sequestration Potential of Ecosystems (Republic of Tatarstan, Russia). Preprints. https://doi.org/10.20944/preprints202311.0008.v1
Chicago/Turabian Style
Gafurov, A., Maria Kozhevnikova and Bulat Usmanov. 2023 "Forest Communities Spatial Modeling as a Basis for Assessing the Sequestration Potential of Ecosystems (Republic of Tatarstan, Russia)" Preprints. https://doi.org/10.20944/preprints202311.0008.v1
Abstract
For the territory of the Republic of Tatarstan (Russia), a spatial model of forest communities was built as a basis for assessing the sequestration potential of ecosystems. Combination of multi-temporal and multi-spectral satellite imagery from the Landsat 8 and Landsat 9 platform as input data and Google Earth Engine cloud platform were used. The set of 292 vegetation indices and metrics computed from the pre-processed imagery, were combined into dataset. The Weka X-Means clustering algorithm was trained and applied to study area. The unsupervised classification was carried out by vegetation classes in the Braun-Blanquet system. The results of unsupervised classification were verified using data from more than 17,000 relevés with geographic references from the Flora database. For automatic classification, the EuroVeg Checklist expert system in the JUICE 7.1 package was used. The proposed methodology for obtaining initial data and unsupervised classification, supported by an automated expert system, made it possible to obtain a picture of the vegetation distribution in the study area with sufficient accuracy, and in the future, it will be used to assess the sequestration potential of the ecosystems of the region under study.
Environmental and Earth Sciences, Environmental Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
