View in EDS

Mapping three-dimensional variation in leaf mass per area with imaging spectroscopy and lidar in a temperate broadleaf forest.

Saved in:
Bibliographic Details
Title: Mapping three-dimensional variation in leaf mass per area with imaging spectroscopy and lidar in a temperate broadleaf forest.
Authors: Chlus, Adam1 (AUTHOR) chlus@wisc.edu, Kruger, Eric L.1 (AUTHOR) elkruger@wisc.edu, Townsend, Philip A.1 (AUTHOR) ptownsend@wisc.edu
Source: Remote Sensing of Environment. Dec2020, Vol. 250, pN.PAG-N.PAG. 1p.
Subjects: Spectral imaging, Broadleaf forests, Temperate forests, Primary productivity (Biology), Partial least squares regression, LIDAR, Laser based sensors
Abstract: Imaging spectroscopy is a valuable tool for mapping canopy foliar traits in forested ecosystems at landscape and larger scales. Most efforts to date have involved two-dimensional mapping of traits, typically representing top-of-canopy conditions. However, traits and their associated biological functions vary through the canopy vertical profile, such that incorporating information about vertical patterns may improve modeling of ecosystem processes like primary productivity. In 2016 and 2017, we collected extensive field data in forests in Domain 5 (Great Lakes) of the National Ecological Observatory Network (NEON) to characterize the vertical variation in leaf mass per area (LMA), an important foliar trait related to plant growth and defense. Fieldwork was coincident with NEON Airborne Observation Platform (AOP) overflights which collected imaging spectroscopy and lidar data. Using imaging spectroscopy to map top-of-canopy LMA and lidar to model vertical gradients of transmittance, we developed a method to map three-dimensional patterns in LMA in temperate broadleaf forests. Partial least squares regression (PLSR) was used to estimate top-of-canopy LMA (R2: 0.57, RMSE 10.8 g m−2), which, along with lidar-derived metrics of light transmittance and height, was used in a multilevel regression to model within-canopy LMA (R2: 0.78, RMSE 8.3 g m−2). The coupled models accurately estimated LMA throughout the canopy without taking into account species composition (R2 = 0.82, RMSE: 8.5 g m−2). • 3D patterns in leaf mass per area are mapped with lidar and imaging spectroscopy. • Lidar transmittance was strongly correlated with within-canopy leaf mass per area. • Within-canopy gradients can be mapped without consideration of species composition. [ABSTRACT FROM AUTHOR]
Copyright of Remote Sensing of Environment is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 146612556
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Mapping three-dimensional variation in leaf mass per area with imaging spectroscopy and lidar in a temperate broadleaf forest.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Chlus%2C+Adam%22">Chlus, Adam</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> chlus@wisc.edu</i><br /><searchLink fieldCode="AR" term="%22Kruger%2C+Eric+L%2E%22">Kruger, Eric L.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> elkruger@wisc.edu</i><br /><searchLink fieldCode="AR" term="%22Townsend%2C+Philip+A%2E%22">Townsend, Philip A.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ptownsend@wisc.edu</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Remote+Sensing+of+Environment%22">Remote Sensing of Environment</searchLink>. Dec2020, Vol. 250, pN.PAG-N.PAG. 1p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Spectral+imaging%22">Spectral imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Broadleaf+forests%22">Broadleaf forests</searchLink><br /><searchLink fieldCode="DE" term="%22Temperate+forests%22">Temperate forests</searchLink><br /><searchLink fieldCode="DE" term="%22Primary+productivity+%28Biology%29%22">Primary productivity (Biology)</searchLink><br /><searchLink fieldCode="DE" term="%22Partial+least+squares+regression%22">Partial least squares regression</searchLink><br /><searchLink fieldCode="DE" term="%22LIDAR%22">LIDAR</searchLink><br /><searchLink fieldCode="DE" term="%22Laser+based+sensors%22">Laser based sensors</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Imaging spectroscopy is a valuable tool for mapping canopy foliar traits in forested ecosystems at landscape and larger scales. Most efforts to date have involved two-dimensional mapping of traits, typically representing top-of-canopy conditions. However, traits and their associated biological functions vary through the canopy vertical profile, such that incorporating information about vertical patterns may improve modeling of ecosystem processes like primary productivity. In 2016 and 2017, we collected extensive field data in forests in Domain 5 (Great Lakes) of the National Ecological Observatory Network (NEON) to characterize the vertical variation in leaf mass per area (LMA), an important foliar trait related to plant growth and defense. Fieldwork was coincident with NEON Airborne Observation Platform (AOP) overflights which collected imaging spectroscopy and lidar data. Using imaging spectroscopy to map top-of-canopy LMA and lidar to model vertical gradients of transmittance, we developed a method to map three-dimensional patterns in LMA in temperate broadleaf forests. Partial least squares regression (PLSR) was used to estimate top-of-canopy LMA (R2: 0.57, RMSE 10.8 g m−2), which, along with lidar-derived metrics of light transmittance and height, was used in a multilevel regression to model within-canopy LMA (R2: 0.78, RMSE 8.3 g m−2). The coupled models accurately estimated LMA throughout the canopy without taking into account species composition (R2 = 0.82, RMSE: 8.5 g m−2). • 3D patterns in leaf mass per area are mapped with lidar and imaging spectroscopy. • Lidar transmittance was strongly correlated with within-canopy leaf mass per area. • Within-canopy gradients can be mapped without consideration of species composition. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Remote Sensing of Environment is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=146612556
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.rse.2020.112043
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 1
        StartPage: N.PAG
    Subjects:
      – SubjectFull: Spectral imaging
        Type: general
      – SubjectFull: Broadleaf forests
        Type: general
      – SubjectFull: Temperate forests
        Type: general
      – SubjectFull: Primary productivity (Biology)
        Type: general
      – SubjectFull: Partial least squares regression
        Type: general
      – SubjectFull: LIDAR
        Type: general
      – SubjectFull: Laser based sensors
        Type: general
    Titles:
      – TitleFull: Mapping three-dimensional variation in leaf mass per area with imaging spectroscopy and lidar in a temperate broadleaf forest.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Chlus, Adam
      – PersonEntity:
          Name:
            NameFull: Kruger, Eric L.
      – PersonEntity:
          Name:
            NameFull: Townsend, Philip A.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 12
              Text: Dec2020
              Type: published
              Y: 2020
          Identifiers:
            – Type: issn-print
              Value: 00344257
          Numbering:
            – Type: volume
              Value: 250
          Titles:
            – TitleFull: Remote Sensing of Environment
              Type: main
ResultId 1