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

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Title High-resolution mapping of forest carbon stock using Object-Based Image Analysis (OBIA) technique
 
Creator Pandey, S. K.
Chand, N.
Nandy, S.
Muminov, A.
Sharma, A.
Ghosh, Surajit
Srinet, R.
 
Subject forests
carbon stock assessments
mapping
satellite imagery
image analysis
techniques
estimation
 
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.
 
Date 2020-06
2021-11-30T22:30:34Z
2021-11-30T22:30:34Z
 
Type Journal Article
 
Identifier 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]
0255-660X
https://hdl.handle.net/10568/116417
https://vlibrary.iwmi.org/pdf/H050799.pdf
https://doi.org/10.1007/s12524-020-01121-8
H050799
 
Language en
 
Rights Copyrighted; all rights reserved
Limited Access
 
Format 48(6):865-875
 
Publisher Springer Science and Business Media LLC
 
Source Journal of the Indian Society of Remote Sensing