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

Land

Ana Paula Dalla Corte¹  Márcio Coraiola²  Marcos Bergmann Carlucci³  Felipe Saad⁴  Sumalika Biswas⁵  Qiongyu Huang⁵  Peter Leimgruber⁵  Sarah Macey⁵ 

[1] Centro de Excelência em Pesquisas sobre Fixação Carbono na Biomassa—BIOFIX Lab, Universidade Federal do Paraná, Curitiba 81530-00, Brazil;Engenharia Florestal, Pontifícia Universidade Católica do Paraná—PUCPR, Curitiba 80215-901, Brazil;Laboratório de Ecologia Funcional de Comunidades (LABEF), Departamento de Botânica, Universidade Federal do Paraná, Curitiba 81531-980, Brazil;Programa de Pós-Graduação em Ecologia e Conservação, Universidade Federal do Paraná, Curitiba 81531-980, Brazil;Smithsonian Conservation Biology Institute, Front Royal, VA 22630, USA;

关键词: Atlantic Forest;    Araucaria angustifolia;    Parana pine;    Google Earth Engine;    UAV-LiDAR;    Worldview-2;   

DOI  :  10.3390/land10121316

来源: DOAJ

【 摘 要 】

The 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 Araucaria angustifolia. A. angustifolia is a critically endangered coniferous tree that is essential for supporting overall biodiversity in the Atlantic Forest. A. angustifolia’s 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 Araucaria angustifolia 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 A. angustifolia at the stand level, with an accuracy of >90% across all three study sites. The second approach relied on object identification using UAV-LiDAR and successfully mapped individual trees (producer’s/user’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 A. angustifolia trees. Each approach has its own strengths and weaknesses, and we discuss their adoptability by managers to inform conservation of A. angustifolia.

【 授权许可】

Unknown