High-resolution mapping of forest carbon stock using Object-Based Image Analysis (OBIA) technique
This study assessed and mapped the aboveground tree carbon stock using very high-resolution satellite imagery (VHRS)—WorldView-2 in Barkot forest of Uttarakhand, India. The image was pan-sharpened to get the spectrally and spatially good-quality image. High-pass filter technique of pan-sharpening wa...
| Autores principales: | , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Springer
2020
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/116417 |
| _version_ | 1855524960265568256 |
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| author | Pandey, S. K. Chand, N. Nandy, S. Muminov, A. Sharma, A. Ghosh, Surajit Srinet, R. |
| author_browse | Chand, N. Ghosh, Surajit Muminov, A. Nandy, S. Pandey, S. K. Sharma, A. Srinet, R. |
| author_facet | Pandey, S. K. Chand, N. Nandy, S. Muminov, A. Sharma, A. Ghosh, Surajit Srinet, R. |
| author_sort | Pandey, S. K. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | This study assessed and mapped the aboveground tree carbon stock using very high-resolution satellite imagery (VHRS)—WorldView-2 in Barkot forest of Uttarakhand, India. The image was pan-sharpened to get the spectrally and spatially good-quality image. High-pass filter technique of pan-sharpening was found to be the best in this study. Object-based image analysis (OBIA) was carried out for image segmentation and classification. Multi-resolution image segmentation yielded 74% accuracy. The segmented image was classified into sal (Shorea robusta), teak (Tectona grandis) and shadow. The classification accuracy was found to be 83%. The relationship between crown projection area (CPA) and carbon was established in the field for both sal and teak trees. Using the relationship between CPA and carbon, the classified CPA map was converted to carbon stock of individual trees. Mean value of carbon stock per tree for sal was found to be 621 kg, whereas for teak it was 703 kg per tree. The study highlighted the utility of OBIA and VHRS imagery for mapping high-resolution carbon stock of forest. |
| format | Journal Article |
| id | CGSpace116417 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | Springer |
| publisherStr | Springer |
| record_format | dspace |
| spelling | CGSpace1164172025-05-20T05:38:06Z High-resolution mapping of forest carbon stock using Object-Based Image Analysis (OBIA) technique Pandey, S. K. Chand, N. Nandy, S. Muminov, A. Sharma, A. Ghosh, Surajit Srinet, R. forests carbon stock assessments mapping satellite imagery image analysis techniques estimation This study assessed and mapped the aboveground tree carbon stock using very high-resolution satellite imagery (VHRS)—WorldView-2 in Barkot forest of Uttarakhand, India. The image was pan-sharpened to get the spectrally and spatially good-quality image. High-pass filter technique of pan-sharpening was found to be the best in this study. Object-based image analysis (OBIA) was carried out for image segmentation and classification. Multi-resolution image segmentation yielded 74% accuracy. The segmented image was classified into sal (Shorea robusta), teak (Tectona grandis) and shadow. The classification accuracy was found to be 83%. The relationship between crown projection area (CPA) and carbon was established in the field for both sal and teak trees. Using the relationship between CPA and carbon, the classified CPA map was converted to carbon stock of individual trees. Mean value of carbon stock per tree for sal was found to be 621 kg, whereas for teak it was 703 kg per tree. The study highlighted the utility of OBIA and VHRS imagery for mapping high-resolution carbon stock of forest. 2020-06 2021-11-30T22:30:34Z 2021-11-30T22:30:34Z Journal Article https://hdl.handle.net/10568/116417 en Limited Access Springer Pandey, S. K.; Chand, N.; Nandy, S.; Muminov, A.; Sharma, A.; Ghosh, Surajit; Srinet, R. 2020. High-resolution mapping of forest carbon stock using Object-Based Image Analysis (OBIA) technique. Journal of the Indian Society of Remote Sensing, 48(6):865-875. [doi: https://doi.org/10.1007/s12524-020-01121-8] |
| spellingShingle | forests carbon stock assessments mapping satellite imagery image analysis techniques estimation Pandey, S. K. Chand, N. Nandy, S. Muminov, A. Sharma, A. Ghosh, Surajit Srinet, R. High-resolution mapping of forest carbon stock using Object-Based Image Analysis (OBIA) technique |
| title | High-resolution mapping of forest carbon stock using Object-Based Image Analysis (OBIA) technique |
| title_full | High-resolution mapping of forest carbon stock using Object-Based Image Analysis (OBIA) technique |
| title_fullStr | High-resolution mapping of forest carbon stock using Object-Based Image Analysis (OBIA) technique |
| title_full_unstemmed | High-resolution mapping of forest carbon stock using Object-Based Image Analysis (OBIA) technique |
| title_short | High-resolution mapping of forest carbon stock using Object-Based Image Analysis (OBIA) technique |
| title_sort | high resolution mapping of forest carbon stock using object based image analysis obia technique |
| topic | forests carbon stock assessments mapping satellite imagery image analysis techniques estimation |
| url | https://hdl.handle.net/10568/116417 |
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