Estimating biomass and carbon mitigation of temperate coniferous forests using spectral modeling and field inventory data

Abstract

Realizing the importance of forest carbon monitoring and reporting in climate change, the present study was conducted to derive spectrally modeled aboveground biomass and mitigation using Landsat data in combination with sampled field inventory data in the coniferous forests of Western Himalaya. After conducting preliminary survey in 2009, 90 quadrats (45 each for calibration and validation) of 0.1ha were laid in six forest types for recording field inventory data viz. diameter at breast height, height, slope and aspect. Biomass carbon (Mgha−1) was worked out for different forest types and crown density classes (open with 10–40% crown density and closed with >40% crown density) using recommended volume equations, ratios and factors. Biomass carbon map (aboveground+belowground) was generated for the entire region using geospatial techniques. Normalized difference vegetation index (NDVI) was generated and spectral values were extracted to establish relation (R2=0.72, p<0.01) with the field inventory data. The model developed was validated (R2=0.73, p<0.01) with 45 sample observations not used earlier for predicting and generating biomass carbon map (2009) for the entire region. The data from field based inventory indicates highest total biomass carbon (171.40, σ±23.19) Mgha−1 for Fir–Spruce (closed) which has relatively more mature girth classes and low tree density. This value was found to be significantly higher than other forest types. Lowest biomass carbon was observed for Blue Pine (open) (37.15, σ±11.82) Mgha−1. The NDVI values for the entire region ranged from 0 to 0.62 and consequently the spectrally derived aboveground biomass carbon varied from 0 to 600Mgha−1. The study demonstrates the application of mapping, spectral responses and sampled field inventory for type wise assessment of carbon mitigation in temperate coniferous forests of Himalayas.