Certification of carbon credit using airborne lidar

Abstract

The Kyoto Protocol recognizes afforestation, reforestation, and forest management as forest sink activities. There has been, however, no standard and accurate certification method established for carbon credit. Lidar (Light Detection and Ranging) can be a good certification tool to prove the amount of carbon stock of forest, because lidar measurement is the most accurate to detect carbon change among remotely sensed data. The certification of forest carbon stock needs to monitor the change of stem volume and forest management activities such as thinning and pruning. Airborne lidar can provide the accurate tree parameters as well as forest management activities. Our study area is located at Sanmu city in Chiba Prefecture, Japan. The research area is used to be a good timber production place of Japanese cedar (Cryptomeria japonica). But most area is abandoned for a long time and is infected by tree disease, because timber production is not profitable and stands are not managed well. The infected trees have cracks on the stem causes the degradation of timber quality and prevent the normal growth of stem volume. To certify the carbon credit in this region, identification of damaged trees is required. Previous research shows the crown properties are significant variables to estimate stem volume. In this study crown volume is quantified by airborne lidar and used to get the relationship with stem volume. The healthy trees are better suited for generating carbon credit more. Then monitoring the tree health condition is desirable from airborne lidar analysis. The estimation of crown volume in this study is given by a computer graphic technique using radial basis function and isosurface. As the result, there is high correlation between field and airborne lidar measurement to get R2 of 0.91 and R2 of 0.75 for tree height and crown base respectively. Crown volume estimated by the wrapped surface is compared with stem volume derived from field measured tree height and stem diameter. The result shows that crown size is diminished after the crack appears on the stem surface f infected trees. Crown volume estimation derived by lidar has a good potential for identifying tree disease infection.