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.
CITATION STYLE
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
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