Logo do repositório

Characterizing Canopy Structure Variability in Amazonian Secondary Successions with Full-Waveform Airborne LiDAR

dc.contributor.authorJacon, Aline D.
dc.contributor.authorGalvão, Lênio Soares
dc.contributor.authorMartins-Neto, Rorai Pereira
dc.contributor.authorCrespo-Peremarch, Pablo
dc.contributor.authorAragão, Luiz E. O. C.
dc.contributor.authorOmetto, Jean P.
dc.contributor.authorAnderson, Liana O.
dc.contributor.authorVedovato, Laura Barbosa
dc.contributor.authorSilva-Junior, Celso H. L.
dc.contributor.authorLopes, Aline Pontes
dc.contributor.authorPeripato, Vinícius
dc.contributor.authorAssis, Mauro
dc.contributor.authorPereira, Francisca R. S.
dc.contributor.authorHaddad, Isadora
dc.contributor.authorde Almeida, Catherine Torres [UNESP]
dc.contributor.authorCassol, Henrique L. G.
dc.contributor.authorDalagnol, Ricardo
dc.contributor.institutionNational Institute for Space Research (INPE)
dc.contributor.institutionCzech University of Life Sciences Prague (CULS)
dc.contributor.institutionUniversitat Politècnica de València
dc.contributor.institutionValencian International University—VIU
dc.contributor.institutionNational Center for Monitoring and Early Warning of Natural Disasters (CEMADEN)
dc.contributor.institutionInstitute for Technological Research (IPT)
dc.contributor.institutionInstituto de Pesquisa Ambiental da Amazônia (IPAM)
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionR. do Rocio
dc.contributor.institutionUniversity of California
dc.contributor.institutionCalifornia Institute of Technology
dc.date.accessioned2025-04-29T18:07:28Z
dc.date.issued2024-06-01
dc.description.abstractFull-waveform LiDAR (FWF) offers a promising advantage over other technologies to represent the vertical canopy structure of secondary successions in the Amazon region, as the waveform encapsulates the properties of all elements intercepting the emitted beam. In this study, we investigated modifications in the vertical structure of the Amazonian secondary successions across the vegetation gradient from early to advanced stages of vegetation regrowth. The analysis was performed over two distinct climatic regions (Drier and Wetter), designated using the Maximum Cumulative Water Deficit (MCWD). The study area was covered by 309 sample plots distributed along 25 LiDAR transects. The plots were grouped into three successional stages (early—SS1; intermediate—SS2; advanced—SS3). Mature Forest (MF) was used as a reference of comparison. A total of 14 FWF LiDAR metrics from four categories of analysis (Height, Peaks, Understory and Gaussian Decomposition) were extracted using the Waveform LiDAR for Forestry eXtraction (WoLFeX) software (v1.1.1). In addition to examining the variation in these metrics across different successional stages, we calculated their Relative Recovery (RR) with vegetation regrowth, and evaluated their ability to discriminate successional stages using Random Forest (RF). The results showed significant differences in FWF metrics across the successional stages, and within and between sample plots and regions. The Drier region generally exhibited more pronounced differences between successional stages and lower FWF metric values compared to the Wetter region, mainly in the category of height, peaks, and Gaussian decomposition. Furthermore, the Drier region displayed a lower relative recovery of metrics in the early years of succession, compared to the areas of MF, eventually reaching rates akin to those of the Wetter region as succession progressed. Canopy height metrics such as Waveform distance (WD), and Gaussian Decomposition metrics such as Bottom of canopy (BC), Bottom of canopy distance (BCD) and Canopy distance (CD), related to the height of the lower forest stratum, were the most important attributes in discriminating successional stages in both analyzed regions. However, the Drier region exhibited superior discrimination between successional stages, achieving a weighted F1-score of 0.80 compared to 0.73 in the Wetter region. When comparing the metrics from SS in different stages to MF, our findings underscore that secondary forests achieve substantial relative recovery of FWF metrics within the initial 10 years after land abandonment. Regions with potentially slower relative recovery (e.g., Drier regions) may require longer-term planning to ensure success in providing full potential ecosystem services in the Amazon.en
dc.description.affiliationEarth Observation and Geoinformatics Division National Institute for Space Research (INPE), SP
dc.description.affiliationFaculty of Forestry and Wood Sciences Czech University of Life Sciences Prague (CULS), Kamýcká 129
dc.description.affiliationGeo-Environmental Cartography and Remote Sensing Group (CGAT) Department of Cartographic Engineering Geodesy and Photogrammetry Universitat Politècnica de València, Camí de Vera s/n
dc.description.affiliationEscuela Superior de Ingeniería Ciencia y Tecnología Valencian International University—VIU, Calle Pintor Sorolla 21
dc.description.affiliationGeneral Coordination of Earth Science National Institute for Space Research (INPE), SP
dc.description.affiliationNational Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), SP
dc.description.affiliationInstitute for Technological Research (IPT), Av. Prof. Almeida Prado, Butantã, SP
dc.description.affiliationInstituto de Pesquisa Ambiental da Amazônia (IPAM), SCN 211, Bloco B, Sala 201, GO
dc.description.affiliationFaculty of Agricultural Sciences of Vale do Ribeira-Câmpus de Registro São Paulo State University (UNESP) Júlio de Mesquita Filho, SP
dc.description.affiliationBluebell Index R. do Rocio, 291-Vila Olímpia, SP
dc.description.affiliationCenter for Tropical Research Institute of the Environment and Sustainability University of California
dc.description.affiliationNASA-Jet Propulsion Laboratory California Institute of Technology
dc.description.affiliationUnespFaculty of Agricultural Sciences of Vale do Ribeira-Câmpus de Registro São Paulo State University (UNESP) Júlio de Mesquita Filho, SP
dc.identifierhttp://dx.doi.org/10.3390/rs16122085
dc.identifier.citationRemote Sensing, v. 16, n. 12, 2024.
dc.identifier.doi10.3390/rs16122085
dc.identifier.issn2072-4292
dc.identifier.scopus2-s2.0-85197295277
dc.identifier.urihttps://hdl.handle.net/11449/297704
dc.language.isoeng
dc.relation.ispartofRemote Sensing
dc.sourceScopus
dc.subjectAmazon
dc.subjectfull-waveform LiDAR
dc.subjectrelative recovery
dc.subjectsecondary succession
dc.subjectsuccessional stages
dc.subjecttropical rainforest
dc.titleCharacterizing Canopy Structure Variability in Amazonian Secondary Successions with Full-Waveform Airborne LiDARen
dc.typeArtigopt
dspace.entity.typePublication
unesp.author.orcid0000-0002-8313-0497[2]
unesp.author.orcid0000-0001-5318-2627[3]
unesp.author.orcid0000-0003-2241-4493[4]
unesp.author.orcid0000-0002-4134-6708[5]
unesp.author.orcid0000-0002-4221-1039[6]
unesp.author.orcid0000-0001-9545-5136[7]
unesp.author.orcid0000-0002-1052-5551[9]
unesp.author.orcid0000-0001-7668-1226[10]
unesp.author.orcid0000-0002-3137-211X[11]
unesp.author.orcid0000-0002-1319-7717[13]
unesp.author.orcid0000-0001-6728-4712[16]
unesp.author.orcid0000-0002-7151-8697[17]
unesp.campusUniversidade Estadual Paulista (UNESP), Faculdade de Ciências Agrárias do Vale do Ribeira, Registropt

Arquivos