Terrestrial Laser scanning to support carbon estimation in nature conservation area: A case study of Haagse Bos and Snippert Forest, Netherlands

Forests have the ability to sequester and store carbon in the living biomass. This make forests play a crucial role in climate change. Thus, estimating aboveground forest biomass and carbon stocks is one of the most important element for measuring and monitoring carbon stock under the REDD+ mechanism. This study aims to estimate above-ground biomass (AGB) and carbon stock based on allometric equations in the temperate forest of nature conservation area of Haagse Bos and Snippert Forest, the Netherland. Terrestrial Laser Scanner (TLS) in a multiple-scan design to measure diameter at breast height (DBH) and tree height of all trees within 500 m2 sample plots was used. Results of this study show that TLS can detect trees correctly with a success rate of 97% compared with field measurement. The highest success rate of trees detection are 98.3% for evergreen forest followed by 98% for broadleaf forest and 91.9% for mixed forest. Very strong relationship was found between the DBH measured with the TLS data and field measurements of plot values with R² of 0.96 and RMSE of 2.42 cm. However, comparing tree height of TLS data and field measurement, a reasonable relationship with R² of 0.61 and RMSE of 3.66 m were found. The above ground carbon (AGC) stocks in study area estimated from field measurement was 103.7 ton/ha., while the AGC stocks estimated from TLS data was 104 ton/ha. The result of mean AGC stock from field measurement and TLS data in evergreen forest were 61 ton/ha and 65 ton/ha, respectively. In broadleaf forest were 145 ton/ha and 151 ton/ha, respectively. However, in mixed forest were 106 ton/ha and 117 ton/ha, respectively. The results show that TLS data are very suitable and had a high agreement with ground truth for estimation of aboveground biomass and carbon stock.