Assessment of Sentinel-2 Spectral Features to Estimate Forest Height with the New GEDI Data

João E. Pereira-Pires, André Mora, Valentine Aubard, João M. N. Silva, José M. Fonseca

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

The unprecedent availability of vertical structure forest data provided by NASA Global Ecosystem Dynamics Investigation (GEDI), allows the validation of new methodologies based on other Remote Sensing (RS) sensors for monitoring forest parameters, such as Forest Height (FH). Previously, studies on FH estimation implied in-situ measurements or acquiring LiDAR data, which was limited and expensive. Opposing to the sampling nature of GEDI mission, Sentinel-2 optical products has a high revisiting frequency and a high spatial resolution favoring the implementation of forest monitoring methodologies. This work presents a study on the correlation and usability of linear and exponential regressions for estimating FH through Sentinel-2 imagery. It was also exploited the advantages of making estimations by study area, or by specific land cover types. Overall, a R2 of 0.66 and a RMSE of 2.91 m were achieved, and in case of specifying the vegetation type were 0.83 and 2.40 m, respectively.

Original languageEnglish
Title of host publicationTechnological Innovation for Applied AI Systems: 12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021, Costa de Caparica, Portugal, July 7–9, 2021, Proceedings
EditorsLuis M. Camarinha-Matos, Pedro Ferreira, Guilherme Brito
Place of PublicationCham
PublisherSpringer
Pages123-131
Number of pages9
ISBN (Electronic)978-3-030-78288-7
ISBN (Print)978-3-030-78287-0, 978-3-030-78290-0
DOIs
Publication statusPublished - 2021
Event12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021 - Costa de Caparica and Online, Portugal
Duration: 7 Jul 20219 Jul 2021

Publication series

NameIFIP Advances in Information and Communication Technology
PublisherSpringer
Volume626
ISSN (Print)1868-4238
ISSN (Electronic)1868-422X

Conference

Conference12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021
Country/TerritoryPortugal
CityCosta de Caparica and Online
Period7/07/219/07/21

Keywords

  • Forest height
  • GEDI
  • LiDAR
  • Parametric regressions
  • Remote sensing
  • Sentinel-2

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