8 November 2014 Mapping afforestation and forest biomass using time-series Landsat stacks
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Abstract
Satellite data can adequately capture forest dynamics over larger areas. Firstly, the Landsat ground surface reflectance (GSR) images from 1974 to 2013 were collected and processed based on 6S atmospheric transfer code and a relative reflectance normalization algorithm. Subsequently, we developed a vegetation change tracking method to reconstruct the forest change history (afforestation and deforestation) from the dense time-series Landsat GSR images, and the afforestation age was successfully retrieved from the Landsat time-series stacks in the last forty years and shown to be consistent with the surveyed tree ages. Then, the above ground biomass (AGB) regression models were greatly improved by integrating the simple ratio vegetation index (SR) and tree age. Finally, the forest AGB images were mapped at eight epochs from 1985 to 2013 using SR and afforestation age. The total forest AGB in six counties of Yulin District increased by 20.8 G kg, from 5.8 G kg in 1986 to 26.6 G kg in 2013, a total increase of 360%. For the forest area, the forest AGB density increased from 15.72 t/ha in 1986 to 44.53 t/ha in 2013, with an annual rate of about 1 t/ha. The results present a noticeable carbon increment for the planted artificial forest in Yulin District over the last four decades.
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Liangyun Liu, Dailiang Peng, Zhihui Wang, Yong Hu, "Mapping afforestation and forest biomass using time-series Landsat stacks", Proc. SPIE 9260, Land Surface Remote Sensing II, 92601V (8 November 2014); doi: 10.1117/12.2069479; https://doi.org/10.1117/12.2069479
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