Estimating mangrove aboveground biomass from airborne LiDAR data: a case study from the Zambezi River delta

Mangroves are ecologically and economically important forested wetlands with the highest carbon (C) density of all terrestrial ecosystems. Because of their exceptionally large C stocks and importance as a coastal buffer, their protection and restoration has been proposed as effective mitigation strategy for climate change. The inclusion of mangroves in mitigation strategies requires the quantification of C stocks (both above and belowground) and changes to accurately calculate emissions and sequestration. A growing number of countries are becoming interested in using mitigation initiatives, such as REDD+, in these unique coastal forests. However, it is not yet clear how methods to measure C traditionally used for other ecosystems can be modified to estimate biomass in mangroves with the precision and accuracy needed for these initiatives. Airborne lidar (ALS) data has often been proposed as the most accurate way for larger-scale assessments but, the application of ALS for coastal wetlands is scarce, primarily due to a lack of contemporaneous ALS and field measurements. Here, we evaluated the variability in field and lidar-based estimates of aboveground biomass (AGB) through the combination of different local and regional allometric models and standardized height metrics that are comparable across spatial resolutions and sensor types. The end result being a simplified approach for accurately estimating mangrove AGB at large-scales and determining the uncertainty by combining multiple allometric models. We then quantified wall-to-wall aboveground biomass stocks of a tall mangrove forest in the Zambezi Delta, Mozambique. Our results indicate that the Lidar H100 height metric correlates well with AGB estimates, with R2 between 0.80 and 0.88 and RMSE of 33% or less. When comparing lidar H100 AGB derived from three allometric models, mean AGB values range from 192 Mg. ha-1 up to 252 Mg. ha-1. We suggest the best model to predict AGB was based on the East Africa specific allometry and a power based regression that used Lidar H100 as the height input with a R2 of 0.85 and a RMSE of 122 Mg.ha-1 or 33%. The total AGB of the lidar inventoried mangrove area (6654 ha) was 1,350,902 Mg with a mean AGB 203 Mg. ha-1. Because the allometry suggested here was developed using standardized height metrics, it is recommended that the models can generate AGB estimates using other remote sensing instruments that are more readily accessible over other mangrove ecosystems on a large scale, and as part of future carbon monitoring efforts in mangroves

Estimating mangrove canopy height and above-ground biomass in the Everglades National Park with airborne LiDAR and TanDEM-X data

Mangrove forests are important natural ecosystems due to their ability to capture and store large amounts of carbon. Forest structural parameters, such as canopy height and above-ground biomass (AGB), provide a good measure for monitoring temporal changes in carbon content. The protected coastal mangrove forest of the Everglades National Park (ENP) provides an ideal location for studying these processes, as harmful human activities are minimal. We estimated mangrove canopy height and AGB in the ENP using Airborne LiDAR/Laser (ALS) and TanDEM-X (TDX) datasets acquired between 2011 and 2013. Analysis of both datasets revealed that mangrove canopy height can reach up to ~25 m and AGB can reach up to ~250 Mg·ha-1. In general, mangroves ranging from 9 m to 12 m in stature dominate the forest canopy. The comparison of ALS and TDX canopy height observations yielded an R2 = 0.85 and Root Mean Square Error (RMSE) = 1.96 m. Compared to a previous study based on data acquired during 2000-2004, our analysis shows an increase in mangrove stature and AGB, suggesting that ENP mangrove forests are continuing to accumulate biomass. Our results suggest that ENP mangrove forests have managed to recover from natural disturbances, such as HurricaneWilma

Assessing Mangrove Above-Ground Biomass and Structure using Terrestrial Laser Scanning: A Case Study in the Everglades National Park

Mangroves are among the ecosystems with the highest potential for carbon sequestration and storage. In these ecosystems and others above-ground biomass (AGB) is often used to estimate above-ground carbon content. We used a Leica-ScanStation-C10 Terrestrial Laser Scanner (TLS) to estimate the volume and AGB of 40 mangrove trees distributed in three different mangrove sites located along Shark River Slough (SRS), in the western Everglades National Park. To estimate the volumetric shape of mangroves, we modeled stems as tapered geometrical surfaces called frustums of paraboloids and prop roots (Rhizophora mangle) as toroids and cylinders. AGB was estimated by multiplying the TLS-derived volume by wood specific density. Our TLS method for the SRS sites resulted in AGB estimates in the range of: 3.9 ± 0.4 to 31.3 ± 3.4 kg per tree in the short mangrove (\u3c5 m) site, 27.4 ± 3.0 to 119.1 ± 12.9 kg per tree in the intermediate (\u3c13 m) site and 52.1 ± 6.7 to 1756.5 ± 189.7 kg per tree in the tall (13–23 m) mangrove site. Our quantitative results: (1) enabled us to develop site-specific allometric relationships for tree diameter and AGB and (2) suggested that TLS is a promising alternative to destructive sampling