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Mapping tree carbon density using sentinel 2A sensor on Google Earth Engine in Darjeeling Himalayas: Implication for tree carbon management and climate change mitigation

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Title Mapping tree carbon density using sentinel 2A sensor on Google Earth Engine in Darjeeling Himalayas: Implication for tree carbon management and climate change mitigation
Not Available
 
Creator M. Singh
A. Arshad
A. Bijlwan
M. Tamang
N.N. Shahina
Ankur Biswas
Arpan Bhowmick
Vineeta
G.C. Banik
A.J. Nath
G. Shukla
S. Chakravarty
 
Subject Darjeeling himalayas
Carbon management
NDVI-Carbon modelling
Tree carbon density
Random forest
 
Description Not Available
The Himalayan region is a most fragile ecosystem globally. Trees make up around 90 % of the global biomass carbon pool and previous studies have shown that tree carbon balance cannot be easily assessed by conventional methods. Considering trees as a backbone of the forest ecosystem, present study assessed the heterogeneity in tree carbon density using field-inventoried data and NDVI-based modelling with Sentinel 2 A imagery on Google Earth Engine. The specific aim of the study was to assess the spatial distribution of tree carbon density in the Darjeeling Himalayas using Sentinel 2 A. The object-based classification of forest area using a random forest algorithm showed a high accuracy (Kappa coefficient value of 0.92, OOB error 0.17). The regression model using NDVI as a predictor of tree carbon demonstrated a good fit (R2 = 0.78) for predicting tree carbon density. Validation results show high accuracy of the regression model in predicting tree carbon density with a low RMSE of 9.39 Mg ha􀀀 1 (R2 = 0.80, % RMSE = 11.55 %). The classification of tree carbon density into five classes revealed that a significant proportion of the forest area (57.05 %) falls under moderate carbon density (50–75 Mg ha􀀀 1). In Darjeeling Himalayas, majority of forests are under the carbon density between 50 and 75 Mg ha􀀀 1. Improvement and conservation efforts must be directed for very low carbon density (01–25 Mg ha􀀀 1) areas covering 0.05 %, and high carbon density (75–100 Mg ha􀀀 1) covering 36.22 % of the forest area, respectively, to balance the overall carbon storage potential of the region.
Not Available
 
Date 2024-04-03T13:36:01Z
2024-04-03T13:36:01Z
2024-02-01
 
Type Journal
 
Identifier Singh, M., Arshad, A., Bijlwan, A., Tamang, M., Shahina, N.N., Biswas, A., Bhowmick, A., Vineeta, Banik, G.C., Nath, A.J., Shukla, G. and Chakravarty, S. (2024). Mapping tree carbon density using sentinel 2A sensor on Google Earth Engine in Darjeeling Himalayas: Implication for tree carbon management and climate change mitigation. Physics and Chemistry of the Earth, Parts A/B/C, 134, 103569. https://doi.org/10.1016/j.pce.2024.103569
1474-7065
http://krishi.icar.gov.in/jspui/handle/123456789/81808
 
Language English
 
Relation Not Available;
 
Publisher Not Available