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High-Resolution Mapping of Forest Carbon Stock Using Object-Based Image Analysis (OBIA) Technique

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Abstract

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.

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Acknowledgements

The authors are thankful to the Director, Indian Institute of Remote Sensing, Dehradun, and Centre for Space Science and Technology Education in Asia and the Pacific (CSSEATP), Dehradun, for his support during the study. The authors wish to acknowledge Divisional Forest Officer, Dehradun Forest Division and staff of Barkot Forest Range, Dehradun Forest Division, Government of Uttarakhand, India, and field staff of Barkot Flux Research Site for field support. Thanks are also due to the anonymous reviewers for a critical review of the manuscript.

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Authors and Affiliations

  1. Department of Botany, DAV PG College, Gorakhpur, 273001, India

    Sanjay Kumar Pandey

  2. Nepal Forester’s Association, Kathmandu, 44600, Nepal

    Narendra Chand

  3. Dept. of Space, Indian Institute of Remote Sensing, Indian Space Research Organisation, Govt. of India, Dehradun, 248001, India

    Subrata Nandy & Ritika Srinet

  4. Department of Agrometeorology, Agency for Hydrometeorology, Dushanbe, 734, Tajikistan

    Abulqosim Muminov

  5. PT. Riau Andalan Pulp and Paper, Pangkalan Kerinci, 28381, Indonesia

    Anchit Sharma

  6. International Water Management Institute, Colombo, Sri Lanka

    Surajit Ghosh

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  1. Sanjay Kumar Pandey
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Correspondence to Sanjay Kumar Pandey.

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Pandey, S.K., Chand, N., Nandy, S. et al. High-Resolution Mapping of Forest Carbon Stock Using Object-Based Image Analysis (OBIA) Technique. J Indian Soc Remote Sens 48, 865–875 (2020). https://doi.org/10.1007/s12524-020-01121-8

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  • DOI: https://doi.org/10.1007/s12524-020-01121-8

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