Mapping for coral reef conservation: comparing the value of participatory and remote sensing approaches
Detailed habitat maps are critical for conservation planning, yet for many coastal habitats only coarse-resolution maps are available. As the logistic and technological constraints of habitat mapping become increasingly tractable, habitat map comparisons are warranted. Here we compare two mapping approaches: local environmental knowledge (LEK) obtained from interviews; and remote sensing analysis (RS) of high spatial resolution satellite imagery (2.0 m pixel) using object-based image analysis. For a coral reef ecosystem, we compare the accuracy of these two approaches for mapping shallow seafloor habitats and contrast their characterization of habitat area and seascape connectivity. We also explore several implications for conservation planning.
When evaluated using independent ground verification data, LEK-derived maps achieved a lower overall accuracy than RS-derived maps (LEK: 66%; RS: 76%). A comparison of mapped habitats found low overall agreement between LEK and RS maps. The RS map identified 5.4 times more habitat edges (the border between adjacent habitat classes) and 3.7–6.4 times greater seascape connectivity. Since the spatial arrangement of habitats affects many species (e.g., movement, predation risk), such discrepancies in landscape metrics are important to consider in conservation planning. Our results help identify strengths and weakness of both mapping approaches for conservation planning. Because RS provided a more accurate estimate of habitat distributions, it would be better for conservation planning for species sensitive to fine-spatial scale seascape patterns (e.g., habitat edges), whereas LEK is more cost effective and appropriate for mapping coarse habitat patterns. Goals for maps used in conservation should be identified early in their development.
Selgrath, J. C., C. Roelfsema, S.E. Gergel and A.C.J. Vincent 2016. Mapping for coral reef conservation: Comparing the value of participatory and remote sensing approaches. Ecosphere 7(5). https://doi.org/10.1002/ecs2.1325