Detectability of the Critically Endangered Araucaria angustifolia Tree Using Worldview-2 Images, Google Earth Engine and UAV-LiDAR

dc.contributor.authorSaad, Felipeen
dc.contributor.authorBiswas, Sumalikaen
dc.contributor.authorHuang, Qiongyuen
dc.contributor.authorCorte, Ana Paula Dallaen
dc.contributor.authorCoraiola, Márcioen
dc.contributor.authorMacey, Sarahen
dc.contributor.authorCarlucci, Marcos Bergmannen
dc.contributor.authorLeimgruber, Peteren
dc.coverage.countryBrazilen
dc.date.accessioned2021-12-09T19:58:32Zen
dc.date.available2021-12-09T19:58:32Zen
dc.date.issued2021-11-30en
dc.date.updated2021-12-09T14:32:15Zen
dc.description.abstractThe Brazilian Atlantic Forest is a global biodiversity hotspot and has been extensively mapped using satellite remote sensing. However, past mapping focused on overall forest cover without consideration of keystone plant resources such as <i>Araucaria angustifolia.</i>&nbsp;<i>A. angustifolia</i> is a critically endangered coniferous tree that is essential for supporting overall biodiversity in the Atlantic Forest. <i>A. angustifolia&rsquo;s</i> distribution has declined dramatically because of overexploitation and land-use changes. Accurate detection and rapid assessments of the distribution and abundance of this species are urgently needed. We compared two approaches for mapping <i>Araucaria angustifolia</i> across two scales (stand vs. individual tree) at three study sites in Brazil. The first approach used Worldview-2 images and Random Forest in Google Earth Engine to detect <i>A. angustifolia</i> at the stand level, with an accuracy of &gt;90% across all three study sites. The second approach relied on object identification using UAV-LiDAR and successfully mapped individual trees (producer&rsquo;s/user&rsquo;s accuracy = 94%/64%) at one study site. Both approaches can be employed in tandem to map remaining stands and to determine the exact location of <i>A. angustifolia</i> trees. Each approach has its own strengths and weaknesses, and we discuss their adoptability by managers to inform conservation of <i>A. angustifolia</i>.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationSaad, F.; Biswas, S.; Huang, Q.; Corte, A.P.D.; Coraiola, M.; Macey, S.; Carlucci, M.B.; Leimgruber, P. Detectability of the Critically Endangered Araucaria angustifolia Tree Using Worldview-2 Images, Google Earth Engine and UAV-LiDAR. Land 2021, 10, 1316.en
dc.identifier.doihttps://doi.org/10.3390/land10121316en
dc.identifier.urihttp://hdl.handle.net/10919/106905en
dc.language.isoenen
dc.publisherMDPIen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleDetectability of the Critically Endangered Araucaria angustifolia Tree Using Worldview-2 Images, Google Earth Engine and UAV-LiDARen
dc.title.serialLanden
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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