Characterizing spatial variability in coastal wetland biomass across multiple scales using UAV and satellite imagery

Abstract

Abstract Coastal wetland biomass is an important indicator of wetland productivity, carbon storage, health, and vulnerability to climate change. The ability to estimate aboveground biomass (AGB) in wetlands at ecologically relevant scales is complicated by the spatial variability inherent to patterns in wetland vegetation and the biogeomorphic processes that help create them. Remote sensing provides an approach for mapping wetland biomass, but the spatial resolutions of satellite and airborne imagery often constrain the types of ecological patterns and processes that can be detected. Unmanned Aerial Vehicles (UAVs) have previously been used to capture fine‐scale (≤1 m) variability in AGB in coastal wetland settings. However, it remains unclear if a UAV approach to estimating wetland biomass is transferrable across diverse wetland sites or how it compares to commonly used satellite‐based approaches. Here, we test the capabilities of UAVs in remotely quantifying AGB and compare biomass estimation using UAV and Landsat satellite imagery (30 m resolution) in several wetland sites in Southern California. Field surveys highlight significant spatial variability in wetland plant community AGB and height that influence remote biomass estimation. Relationships between UAV vegetation indices and AGB were site‐specific and influenced by vegetation types. Biomass estimation using UAVs (r2 = 0.40, RMSE = 534.6 g m−2) showed better correlation with NDVI than a Landsat‐based approach (r2 = 0.26, RMSE = 596.8 g m−2). We found combining high‐resolution UAV AGB maps and Landsat NDVI to develop AGB models showed the highest correlation (r2 = 0.45, RMSE = 659.7 g m−2) and provided additional spatial information to aid scaling field data to satellite imagery. Overall, UAVs captured more spatial complexity in aboveground biomass at finer scales than is possible with moderate‐resolution Landsat pixels, indicating that UAVs can be used to characterize patterns of within‐marsh variability resulting from local‐scale (≤ 100s of meters) ecological processes.

Keywords

• Drones
• Landsat
• saltmarsh
• semivariogram
• spatial heterogeneity
• unmanned aerial systems