105
© The Author(s) 2020
J. Cavender-Bares et al. (eds.), Remote Sensing of Plant Biodiversity,
https://doi.org/10.1007/978-3-030-33157-3_5
Chapter 5
Lessons Learned from Spectranomics:
Wet Tropical Forests
Roberta E. Martin
5.1 Introduction
One of the major challenges for biodiversity science is how to measure biodiversity
at spatial scales relevant for conservation and management (Turner 2014). Supported
by technological, computational, and modeling advances, along with increased data
availability, remote sensing (RS) has become an essential tool for ecologists and
land managers because it provides data on the optical properties of the Earth’s surface at landscape to global scales (Jetz et al. 2016). At the same time, increasing
awareness of how little we know about the species inhabiting our planet has led to a
surge in ground-based activities to catalog what’s out there and establish baselines
such as Conservation International’s Rapid Assessment Program and/or community
aggregated information needed for biodiversity assessment (Myers et al. 2000). In
addition, advances in genetic analysis, physiological experiments, and trait-based
studies have advanced our understanding of functional biodiversity (CavenderBares et al. 2006; Kress et al. 2009; Baraloto et al. 2012). Despite these knowledge
gains, linking the information from these disparate sources in a useful manner presented a new hurdle. In 2007 the Spectranomics approach was launched to address
this challenge using canopy functional traits and their resultant spectral properties.
R. E. Martin (*)
School of Geographical Sciences and Urban Planning, Arizona State University,
Tempe, AZ, USA
Center for Global Discovery and Conservation Science, Arizona State University,
Tempe, AZ, USA
e-mail: Roberta.Martin@asu.edu
© The Author(s) 2020
J. Cavender-Bares et al. (eds.), Remote Sensing of Plant Biodiversity,
https://doi.org/10.1007/978-3-030-33157-3_5
Chapter 5
Lessons Learned from Spectranomics:
Wet Tropical Forests
Roberta E. Martin
5.1 Introduction
One of the major challenges for biodiversity science is how to measure biodiversity
at spatial scales relevant for conservation and management (Turner 2014). Supported
by technological, computational, and modeling advances, along with increased data
availability, remote sensing (RS) has become an essential tool for ecologists and
land managers because it provides data on the optical properties of the Earth’s surface at landscape to global scales (Jetz et al. 2016). At the same time, increasing
awareness of how little we know about the species inhabiting our planet has led to a
surge in ground-based activities to catalog what’s out there and establish baselines
such as Conservation International’s Rapid Assessment Program and/or community
aggregated information needed for biodiversity assessment (Myers et al. 2000). In
addition, advances in genetic analysis, physiological experiments, and trait-based
studies have advanced our understanding of functional biodiversity (CavenderBares et al. 2006; Kress et al. 2009; Baraloto et al. 2012). Despite these knowledge
gains, linking the information from these disparate sources in a useful manner presented a new hurdle. In 2007 the Spectranomics approach was launched to address
this challenge using canopy functional traits and their resultant spectral properties.
R. E. Martin (*)
School of Geographical Sciences and Urban Planning, Arizona State University,
Tempe, AZ, USA
Center for Global Discovery and Conservation Science, Arizona State University,
Tempe, AZ, USA
e-mail: Roberta.Martin@asu.edu