Tropical Geography ›› 2023, Vol. 43 ›› Issue (1): 12-22.

### Individual Tree Crown Delineation and Aboveground Biomass Estimation of Sonneratia apetala Based on Unmanned Aerial Vehicle Remote Sensing Images

Chuying Yu1,2(), Hui Gong3, Jingjing Cao1,2, Yanjun Liu1,2, Kai Liu1,2()

1. 1.School of Geography and Planning, Sun Yat-sen University//Provincial Engineering Research Center for Public Security and Disaster//Guangdong Key Laboratory for Urbanization and GeoSimulation, Guangzhou 510006, China
2.Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519000, China
3.Guangzhou Urban Planning & Design Survey Research Institute, Guangzhou 510060, China
• Received:2022-09-24 Revised:2022-11-03 Online:2023-01-05 Published:2023-02-03
• Contact: Kai Liu E-mail:yuchy5@mail2.sysu.edu.cn;liuk6@mail.sysu.edu.cn

Abstract:

Accurate mangrove biomass measurement is necessary for the management and protection of mangrove ecosystems. Sonneratia apetala was the first high-quality mangrove species to be introduced for mangrove restoration in China. Compared with other mangrove species, Sonneratia apetala has higher productivity and can store large amounts of carbon in its living biomass. However, accurate depiction of the single-wood canopy of Sonneratia apetala is challenging because of its high clumping density and intricate canopy structure. While traditional satellite remote sensing focuses on regional or larger-scale monitoring needs, the newly emerged Unmanned Aerial Vehicle (UAV) remote sensing has significant advantages for monitoring mangroves at finer scales. However, few studies have used UAV data for mangrove biomass analyses. In this study, we successfully used consumer-grade UAV data to estimate the height and aboveground biomass (AGB) of Sonneratia apetala on Qi'ao Island, Zhuhai, Guangdong Province. We used a variable window filter algorithm to detect the treetops. Individual tree canopy segmentation was performed using the seed region-growing algorithm. Additionally, we constructed a regression equation for height (H) and diameter at breast height (DBH) of Sonneratia apetala in the study area and optimized the traditional allometric equation. Finally, mangrove AGB was estimated at the tree level using the optimized allometric equation, and the results indicated that the AGB of Sonneratia apetala could be accurately extracted using UAV images. The accuracy of the tree delineation was 67%, the correlation between H and DBH was DBH = 2.2726H-6.4415, and the correlation coefficient R2 was 0.8713. The aboveground mass of a single wood of Sonneratia apetala in the study area ranged from 29.60 to 388.44 kg, with a mean value of 145.72 kg and a total aboveground mass of 368.97 t. Partial spatial clustering was observed in the distribution of the aboveground mass of Sonneratia apetala in the study area, with a Moran's I index value of 0.594. The aboveground mass of Sonneratia apetala at the edge of the area and in the window part of the area was found to be smaller, mainly for two possible reasons. First, the natural death of Sonneratia apetala in part of the study area created a window, but its surrounding seedlings were still in the biomass accumulation stage. Second, the aboveground mass of Sonneratia apetala at the edges of the study area is often lost due to its vulnerable nature and anthropogenic factors. The average number of Sonneratia apetala in each quadrat was 6.3 and the AGB in the study area ranged from 2.99 to 247.24 t/hm2, with a mean value of 92.14 t/hm2. The estimated AGB based on UAV data was consistently lower than that generated from field data. The methods described in this study offer the possibility of easily repeatable, low-cost UAV surveys, providing a faster and more economical approach for monitoring mangrove forests than traditional ground surveys. These results may assist in decision-making regarding ecological monitoring, resource use, mangrove introduction, and scientific advancement of mangroves in China.

CLC Number:

• S718.5