Biomass and Carbon Stock Quantification in Cork Oak Forest of Maamora Using a New Approach Based on the Combination of Aerial Laser Scanning Carried by Unmanned Aerial Vehicle and Terrestrial Laser Scanning Data

作     者：Sanaa, Fadil Imane, Sebari Mohamed, Bouhaloua Kenza, Ait El kadi Souhail, Kellouch Lfalah, Hamza Khadija, Meghraoui 

作者机构：IAV Hassan II Sch Geomat & Surveying Engn Dept Cartog & Photogrammetry Rabat 10000 Morocco Natl Agcy Water & Forests Rabat 10000 Morocco IAV Hassan II Dept Nat Resources & Environm Rabat 10000 Morocco AXIGEO Campanie Marrakech 40000 Morocco 

出 版 物：《FORESTS》 (森林)

年 卷 期：2022年第13卷第8期

页      面：1211页

核心收录：

学科分类：0907[农学-林学] 08[工学] 0829[工学-林业工程] 09[农学] 

主　　题：biomass carbon stock combination of ALS-UAV and TLS data segmentation tree Mediterranean region allometric equations Cork oak forest 

摘      要：The Mediterranean forests, particularly Cork oak (Quercus suber L., 1927), make a major contribution to the fight against climate change through Carbon sequestration. Hence, there is a great interest in the accurate quantification of biomass and carbon stock. In this context, this study aims at assessing the performance of a new approach, based on the combination of Unmanned aerial vehicle airborne Aerial laser scanning (ALS-UAV) and Terrestrial laser scanning (TLS) data, in the determination of dendrometric parameters (Circumference at 1.30 m and Tree Height), and consequently the estimation of biomass and carbon stock, considering field data as reference. This study takes the Maamora forest in Morocco as an example of a Mediterranean Cork oak forest. The methodology consists of collecting data at three levels: the entire area level for an ALS-UAV scan, the plot and tree levels for TLS surveys, as well as field data collection. Afterwards, dendrometric parameters (Circumference at 1.30 m and the Tree height) were estimated using individual tree segmentation and biomass;the carbon stock (aboveground, belowground, and total) was estimated using allometric equations. The comparison of the estimated dendrometric parameters with those measured in the field shows a strong relationship, with a Pearson coefficient of 0.86 and 0.83, a correlation coefficient (R-2) of 0.81 and 0.71, and a Root mean square error (RMSE) of 1.84 cm and 0.47 m, respectively. Concerning the biomass and carbon stock estimation, the proposed approach gives a satisfactory accuracy, with a Pearson coefficient of 0.77, an R2 of 0.83, and an RMSE of 36.40 kg for biomass and 20.24 kg for carbon stock.