This study investigated how different remote sensing techniques can be combined to accurately monitor mangroves. In this paper, we present a framework to use drone imagery to calculate correction factors which can improve the accuracy of satellite-based mangrove extent. We focus on semi-arid dwarf mangroves of Baja California Sur, Mexico, where the mangroves tend to be stunted in height and found in small patches, as well as larger forests. Using a DJI Phantom 4 Pro, we imaged mangroves and labeled the extent by manual classification in QGIS. Using ArcGIS, we compared satellite-based mangrove extent maps from Global Mangrove Watch (GMW) in 2016 and Mexico’s national government agency (National Commission for the Knowledge and Use of Biodiversity, CONABIO) in 2015, with extent maps generated from in situ drone studies in 2018 and 2019. We found that satellite-based extent maps generally overestimated mangrove coverage compared to that of drone-based maps. To correct this overestimation, we developed a method to derive correction factors for GMW mangrove extent. These correction factors correspond to specific pixel patterns generated from a convolution analysis and mangrove coverage defined from drone imagery. We validated our model by using repeated k-fold cross-validation, producing an accuracy of 98.3% ± 2.1%. Overall, drones and satellites are complementary tools, and the rise of machine learning can help stakeholders further leverage the strengths of the two tools, to better monitor mangroves for local, national, and international management.

As the use of aerial tools such as unmanned aerial vehicles (UAVs) for mangrove monitoring gains in popularity, understanding who leads this research and where is critical for expanding efficient monitoring methods and achieving international commitments to sustainable development, technology transfer and reduced inequality. Between 2000 and 2019, mangrove research using aerial tools was largely conducted in and led by institutions in higher income countries, despite High-income countries accounting for only 9% of global mangrove coverage. Of studies where the country of the lead institution differed from that of the study site, only 38% of the studies included local co-authors. These results echo historical patterns of research conducted by researchers from higher income countries on biodiversity concentrated in lower income countries, frequently with limited involvement of local scientists—known as “helicopter research.” The disconnect between where mangroves are located and where aerial research is conducted may result from barriers such as government restrictions, limited financial and technical resources, language barriers hindering UAV deployment, or hampered findability of local research. Our findings suggest that expertise for aerial surveys currently lies in “High-income, Annex II” and “Upper-middle-income, Non-Annex” countries, and both groups could invest time and resources in building local, long-term technological capacity in Upper-middle, Lower-middle and Low-income countries. We identify strategic partnerships to expand aerial tools for mangrove research that also address commitments under the United Nations Framework Convention on Climate Change and potential international collaborations under the framework proposed by the UN Decade of Ocean Science for Sustainable Development.