Multi-Sensor Remote Sensing of Mangrove Resilience and Stress After the 2019 Northeast Brazil Oil Spill

Mangrove forests provide important coastal protection, biodiversity support and blue-carbon storage, yet they are highly sensitive to pollution-driven disturbances. The 2019 oil spill along the Brazilian northeast coast represents one of the largest recent environmental disasters in the South Atlantic, highlighting the need for scalable monitoring approaches capable of detecting both immediate impacts and delayed ecosystem responses. Beginning in late August 2019, petroleum residues reached hundreds of beaches and estuaries across multiple Brazilian states, affecting extensive intertidal habitats including mangrove-fringed shorelines; despite subsequent investigations, the spill’s source has not been conclusively established to date. Here we assess mangrove canopy dynamics following the spill using a multispectral, multi-resolution remote sensing framework that integrates satellite imagery and uncrewed aerial system (UAS) observations.

We analyzed time series of vegetation indices (NDVI, NDWI and chlorophyll-related indices) derived from PlanetScope, WorldView, Sentinel and UAS multispectral imagery for two affected mangrove areas in Pernambuco State, Brazil (Itamaraca and Carneiros, North and South coast respectively), covering the period 2018–2024. To enable cross-sensor comparison across different spatial resolutions, index distributions were harmonized relative to reference acquisitions. Pre- and post-spill windows were evaluated to capture short-term responses and longer-term trajectories. Tree-level structural data (height) were incorporated to test whether canopy condition changes were size-dependent such as other geographical parameters (zonation). Statistical analyses included parametric and non-parametric pre/post contrasts, trend evaluation across irregular acquisition intervals, and correlation and regression analyses linking tree height to spectral change metrics.

Across both sites, short-term analyses show no clear evidence of abrupt canopy degradation in moths immediately following the spill. In contrast, long-term trajectories reveal (years) a persistent decline in NDVI coupled with stable or slightly increasing NDWI, consistent with chronic physiological stress or progressive canopy thinning rather than acute dieback. The magnitude of long-term greenness loss is significantly greater in Itamaracá (North Coast) compared to Carneiros (South Coast), demonstrating spatial variation in exposure and/or ecosystem resilience. Additionally, emergency cleaning programs conducted primarily by local communities may have played an important role in influencing forest conditions. Height-dependent analyses further suggest that taller trees in Itamaracá experienced stronger post-spill declines, whereas responses in Carneiros were weaker and less structured by tree size. There was a slightly stronger decline in NDVI in the parts of the basin farthest from the tidal channels, likely because oil tended to linger longer in these areas.

These results demonstrate the value of multispectral, multi-resolution monitoring—combining frequent satellite coverage with targeted UAS surveys—for detecting subtle, delayed ecosystem responses to environmental disasters, supporting more effective impact assessment and evidence-based protection of sensitive coastal ecosystems.