Lessons learned from spectranomics: Wet tropical forests

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

One of the major struggles for biodiversity science is how to measure biodiversity at scales relevant for conservation and management, particularly in wet tropical forests where vast, largely inaccessible landscapes and enormous taxonomic variation make field-based approaches alone infeasible, and current Earth-observing satellites are unable to detect compositional differences or forest functional changes over time. The Spectranomics approach was developed to link plant canopy functional traits to their spectral properties with the objective of providing time-varying, scalable methods for remote sensing (RS) of forest biodiversity. In this chapter we explain key components of Spectranomics and highlight some of the major lessons learned over the past decade as we developed the program in tropical forests sites around the world.

Original languageEnglish (US)
Title of host publicationRemote Sensing of Plant Biodiversity
PublisherSpringer International Publishing
Pages105-120
Number of pages16
ISBN (Electronic)9783030331573
ISBN (Print)9783030331566
DOIs
StatePublished - Jan 1 2020

Keywords

  • Biodiversity
  • Biogeography
  • Canopy chemistry
  • Conservation mapping
  • Functional traits
  • Global Airborne Observatory (GAO)
  • Imaging spectroscopy
  • Phylogeny
  • Plant traits
  • Remote sensing

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Environmental Science(all)
  • Engineering(all)
  • Earth and Planetary Sciences(all)

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  • Cite this

    Martin, R. E. (2020). Lessons learned from spectranomics: Wet tropical forests. In Remote Sensing of Plant Biodiversity (pp. 105-120). Springer International Publishing. https://doi.org/10.1007/978-3-030-33157-3_5