High-resolution mapping of forest carbon stock using Object-Based Image Analysis (OBIA) technique

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cg.coverage.countryIndia
cg.coverage.iso3166-alpha2IN
cg.coverage.regionSouthern Asia
cg.coverage.subregionUttarakhand
cg.coverage.subregionBarkot Forest
cg.creator.identifierSurajit Ghosh: 0000-0002-3928-2135en
cg.identifier.doihttps://doi.org/10.1007/s12524-020-01121-8en
cg.identifier.iwmilibraryH050799en
cg.isijournalISI Journalen
cg.issn0255-660Xen
cg.issue6en
cg.journalJournal of the Indian Society of Remote Sensingen
cg.reviewStatusPeer Reviewen
cg.volume48en
dc.contributor.authorPandey, S. K.en
dc.contributor.authorChand, N.en
dc.contributor.authorNandy, S.en
dc.contributor.authorMuminov, A.en
dc.contributor.authorSharma, A.en
dc.contributor.authorGhosh, Surajiten
dc.contributor.authorSrinet, R.en
dc.date.accessioned2021-11-30T22:30:34Zen
dc.date.available2021-11-30T22:30:34Zen
dc.identifier.urihttps://hdl.handle.net/10568/116417
dc.titleHigh-resolution mapping of forest carbon stock using Object-Based Image Analysis (OBIA) techniqueen
dcterms.abstractThis 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.en
dcterms.accessRightsLimited Access
dcterms.available2020-06-12en
dcterms.bibliographicCitationPandey, 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]en
dcterms.extentp. 865-875en
dcterms.issued2020-06en
dcterms.languageen
dcterms.licenseCopyrighted; all rights reserved
dcterms.publisherSpringeren
dcterms.subjectforestsen
dcterms.subjectcarbon stock assessmentsen
dcterms.subjectmappingen
dcterms.subjectsatellite imageryen
dcterms.subjectimage analysisen
dcterms.subjecttechniquesen
dcterms.subjectestimationen
dcterms.typeJournal Article

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