Monitoring restored tropical forest diversity and structure through UAV-borne hyperspectral and lidar fusion

REMOTE SENSING OF ENVIRONMENT

卷:264

Article

de Almeida, Danilo Roberti Alves^1,2  Broadbent, Eben North²  Ferreira, Matheus Pinheiro³  Meli, Paula⁴  Zambrano, Angelica Maria Almeyda⁵  Gorgens, Eric Bastos⁶  Resende, Angelica Faria¹  de Almeida, Catherine Torres¹  do Amaral, Cibele Hummel⁷  Corte, Ana Paula Dalla⁸  Silva, Carlos Alberto^9,10  Romanelli, Joao P.¹  Prata, Gabriel Atticciati²  Papa, Daniel de Almeida¹¹  Stark, Scott C.¹²  Valbuena, Ruben¹³  Nelsonn, Bruce Walker¹⁴  Guillemot, Joannes^1,15,16  Feret, Jean-Baptiste¹⁷  Chazdon, Robin¹⁸  Brancalion, Pedro H. S.¹ 

[1] Univ Sao Paulo USP ESALQ, Luiz de Queiroz Coll Agr, Dept Forest Sci, Piracicaba, SP, Brazil

[2] Univ Florida, Sch Forest Resources & Conservat, Spatial Ecol & Conservat Lab, Gainesville, FL 32611 USA

[3] Mil Inst Engn IME, Cartog Engn Dept, Rio De Janeiro, RJ, Brazil

[4] Univ La Frontera, Landscape Ecol & Conservat Lab LEPCON, Temuco, Chile

[5] Univ Florida, Ctr Latin Amer Studies, Spatial Ecol & Conservat SPEC Lab, Gainesville, FL USA

[6] Fed Univ Jequitinhonha & Mucuri Valleys UFVJM, Dept Forestry, Diamantina, MG, Brazil

[7] Univ Fed Vicosa, Dept Forest Engn, Vicosa, MG, Brazil

[8] Univ Fed Parana, Dept Forest Engn, Curitiba, Parana, Brazil

[9] Univ Florida, Sch Forest Fisheries & Geomat Sci, Gainesville, FL USA

[10] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA

[11] Embrapa Acre, Rio Branco, Acre, Brazil

[12] Michigan State Univ, Dept Forestry, E Lansing, MI 48824 USA

[13] Bangor Univ, Sch Nat Sci, Bangor, Gwynedd, Wales

[14] Natl Inst Amazon Res INPA, Manaus, Amazonas, Brazil

[15] CIRAD, UMR Eco & Sols, F-34398 Montpellier, France

[16] Univ Montpellier, Inst Agro, CIRAD, INRAE,Eco & Sols,IRD, Montpellier, France

[17] Univ Montpellier, CNRS, AgroParisTech, CIRAD,INRAE,TETIS, Montpellier, France

[18] Univ Sunshine Coast, Trop Forests & People Res Ctr, Sippy Downs, Qld 4556, Australia

关键词: Forest landscape restoration;    Tropical forests;    Drones;    Lidar remote sensing;    Hyperspectral remote sensing;    Leaf area density;    Vegetation indices;   

DOI  :  10.1016/j.rse.2021.112582

来源: Elsevier

【 摘 要 】

Remote sensors, onboard orbital platforms, aircraft, or unmanned aerial vehicles (UAVs) have emerged as a promising technology to enhance our understanding of changes in ecosystem composition, structure, and function of forests, offering multi-scale monitoring of forest restoration. UAV systems can generate highresolution images that provide accurate information on forest ecosystems to aid decision-making in restoration projects. However, UAV technological advances have outpaced practical application; thus, we explored combining UAV-borne lidar and hyperspectral data to evaluate the diversity and structure of restoration plantings. We developed novel analytical approaches to assess twelve 13-year-old restoration plots experimentally established with 20, 60 or 120 native tree species in the Brazilian Atlantic Forest. We assessed (1) the congruence and complementarity of lidar and hyperspectral-derived variables, (2) their ability to distinguish tree richness levels and (3) their ability to predict aboveground biomass (AGB). We analyzed three structural attributes derived from lidar data-canopy height, leaf area index (LAI), and understory LAI-and eighteen variables derived from hyperspectral data-15 vegetation indices (VIs), two components of the minimum noise fraction (related to spectral composition) and the spectral angle (related to spectral variability). We found that VIs were positively correlated with LAI for low LAI values, but stabilized for LAI greater than 2 m2/m2. LAI and structural VIs increased with increasing species richness, and hyperspectral variability was significantly related to species richness. While lidar-derived canopy height better predicted AGB than hyperspectral-derived VIs, it was the fusion of UAV-borne hyperspectral and lidar data that allowed effective co-monitoring of both forest structural attributes and tree diversity in restoration plantings. Furthermore, considering lidar and hyperspectral data together more broadly supported the expectations of biodiversity theory, showing that diversity enhanced biomass capture and canopy functional attributes in restoration. The use of UAV-borne remote sensors can play an essential role during the UN Decade of Ecosystem Restoration, which requires detailed forest monitoring on an unprecedented scale.

【 授权许可】

Free