Improving ecological indicators of mangrove canopy height and aboveground biomass through multi-source data fusion on the Amazon coast

Abstract

Reliable ecological indicators of mangrove structure and carbon storage are essential for monitoring coastal ecosystem conditions, yet their accuracy remains uncertain in tall, structurally heterogeneous forests, where Earth observation products differ in sensor physics, spatial resolution, and acquisition dates. Here, we present a multi-scale framework to evaluate, calibrate, and improve two widely used ecological indicators of mangrove condition—canopy height and aboveground biomass (AGB)—across approximately 7000 ha of mangroves in the Marapanim estuary, northern Brazil. The framework integrates UAV photogrammetry, radar-derived digital elevation models (TanDEM-X and SRTM), and field measurements to quantify cross-scale discrepancies and identify the main sources of uncertainty affecting indicator retrieval. High-resolution UAV canopy-height models revealed exceptionally tall Avicennia forests reaching up to 53 m, among the tallest mangroves reported globally. At the local scale, mean AGB reached approximately 648 Mg ha −1 in the southern Avicennia -dominated sector and 430 Mg ha −1 in the northern mixed Rhizophora–Avicennia sector, with local maxima of ∼800 Mg ha −1 . In contrast, radar-derived products yielded substantially lower estimates of canopy height and biomass, with height differences of 8–10 m in tall and structurally heterogeneous stands. These discrepancies reflect the combined effects of sensor-dependent canopy representation, spatial averaging, and temporal mismatch between historical radar acquisitions and recent UAV observations. To improve the ecological interpretation of these products, we implemented a calibration strategy linking field and UAV measurements to satellite observations and complemented it with UAV-based three-dimensional volumetric reconstruction of individual trees as an independent structural check on allometric biomass estimates. Our results show that canopy height and AGB derived from coarse-resolution radar products can systematically underestimate mangrove structural condition and carbon storage in tall forests unless locally calibrated. Beyond documenting exceptionally tall and carbon-dense Amazonian mangroves, this study provides a transferable framework for evaluating and improving ecological indicators of forest structure and biomass in complex coastal ecosystems.

Plant phenotyping relevance

UAV photogrammetry・レーダー・現地測定を統合し、マングローブの樹冠高と地上部バイオマスという植物形質の推定を評価・較正・改善する方法論が研究の中心である。

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