| dc.description.abstract | This research aimed to explore the potential of
remote sensing techniques in estimating Above Ground
Biomass (AGB) values over the Sinharaja forest area in
Sri Lanka. Sentinel-1&2 satellite images were used to
extract AGB values, and the accuracy was validated using
field measurements. Statistical analysis including
correlation and regression analysis were employed to
investigate the relationship between the estimated AGB
values and field measurements. The results revealed a
strong positive correlation between Sentinel-1 Estimated
AGB and field-calculated AGB, while the correlation
between Sentinel-2 Estimated AGB and field-calculated
AGB was relatively weak. Non-linear regression analysis
was also conducted to explore the relationship between
the AGB values, which revealed a quadratic relationship
between Sentinel-2 Estimated AGB and field-calculated
AGB. Non-linear regression analysis was not conducted
between sentinel-1 and field-calculated AGB data.
Because there was strong positive correlation. This study
conducted an annual analysis of above-ground biomass
(AGB) along Neluwa, Lankagama, and Deniyaya roads
within Sinharaja Forest. By comparing AGB values from
2018 to 2022, significant decreases were observed in
2019, indicating a critical year for deforestation activity.
These findings provide valuable insights for conservation
efforts and measures to mitigate further forest
degradation and protect the ecosystem. The study suggests
that remote sensing techniques can be used as a reliable
and cost-effective method to estimate AGB values in dense
forest areas, particularly when field measurements are
difficult to obtain. However, higher resolution
multispectral satellite images or advanced techniques can
be used for more accurate results. Overall, the study
provides valuable insights for forest management and
conservation practices | en_US |
