Comparison of forest tree parameters extracted from uav optical and tls data in both tropical rain and temperate forests

There is a great need for a cost-effective and accurate method to assess the parameters for estimating above-ground biomass (AGB)/carbon stock, both in complex multi-layered tropical rain-forest and in temperate forests. The tree height and Diameter at Breast Height (DBH) are important forest parameters required as inputs for biomass estimation equation and can be obtained through various methods such as direct field measurement. However, measuring tree height and DBH by field surveying is time-consuming, limited to inaccessible areas and rather expensive. With the advancement of remote sensing technology, various datasets have been used to assess AGB including airborne LiDAR or sometimes called Airborne Laser Scanner (ALS) but this data is not always available and expensive to acquire for regular monitoring. The emergent of Unmanned Aerial Vehicle (UAV) and Terrestrial Laser Scanner (TLS) technologies, which operate from air and ground respectively, can provide accurate information of upper and lower canopy layers at a reasonable cost for regular monitoring of carbon stock. However, both are associated with the limitation of foliage coverage in the complex multi-layer tropical forest which can underestimate AGB when used separately. This study aimed at establishing a cost-effective method that ensures reasonable accuracy for regular assessment of tree parameters in tropical rain-forest and temperate forests for AGB/carbon estimation for REDD+ and its MRV system by complementing UAV imagery and TLS data. Furthermore, a comparison between the techniques and modeling approach in both the tropical and temperate forest are discussed. Moreover, a comparison is made of the effect of the structure and the condition of both tropical rain and temperate forests on the results extracted from UAV and TLS.