115
between field and RS work from the traditional approach of mapping and ground
truthing to one based on botanical, ecological, and biophysical knowledge in the
interpretation of remotely sensed data.
This interaction between Spectranomics and RS also provided the scientific
guidance, and initial funding, for a new class of mapping instruments, starting with
a next-generation, high-fidelity visible-to-shortwave infrared (VSWIR) imaging
spectrometer, built by the California Institute of Technology’s Jet Propulsion
Laboratory (JPL) for the Global Airborne Observatory, formerly the Carnegie
Airborne Observatory (Asner et al. 2012a). JPL then built an identical instrument
for NASA’s Airborne Visible/Infrared Imaging Spectrometer (AVIRIS; http://aviris.
jpl.nasa.gov) program, as well as several copies for the US National Ecological
Observatory Network (NEON, https://www.neonscience.org; Kampe et al. 2011).
5.3.4 Scientific and Conservation Opportunities
An important outgrowth of Spectranomics is an emerging opportunity to partner
discovery-based science with applied environmental conservation at large geographic scales. Conservation and management actions are usually limited in scope
and effectiveness by numerous interacting financial, logistical, cultural, and political factors. An increasing ability to map canopy diversity may provide an avenue to
identify the location and essential components of high-value conservation targets.
Moreover, near-real-time scientific discovery from spectral RS can lead to more
tactical conservation decision-making. Our specific experience is that, as land use
pressures expand, intensify, and change over time, a mapping capability built upon
the details of forest canopy function and composition, rather than just forest cover,
supports improved conservation discussions and planning. This type of approach is
needed to identify current and potential threats to, as well as current protections
and opportunities for new protection of, species, communities, and ecosystems.
The evolving biodiversity mapping capabilities made possible through
Spectranomics are providing a tool set to support the current portfolio of Global
Airborne Observatory activities (e.g., http://www.theborneopost.com/2016/04/06/3dmapping-to-decide-on-land-use/).
The Spectranomics approach is starting to catch on in the scientific community,
as highlighted in chapters throughout this book as well as new programs such as
NEON and Canada’s recently announced Spectranomics program for boreal forests
(the Canadian Airborne Biodiversity Observatory; http://www.caboscience.org/),
but there is much more to do to bring our approach to the global level. First, more
scientists could get involved through building plant canopy trait laboratories and
databases, paired with a specific style of leaf-level spectral measurements in the
field. Currently, many functional trait and spectral measurement protocols are
incompatible with the Spectranomics approach. For example, many foliar trait
studies have involved the collection of samples in understory or shaded settings,
5 Lessons Learned from Spectranomics: Wet Tropical Forests
between field and RS work from the traditional approach of mapping and ground
truthing to one based on botanical, ecological, and biophysical knowledge in the
interpretation of remotely sensed data.
This interaction between Spectranomics and RS also provided the scientific
guidance, and initial funding, for a new class of mapping instruments, starting with
a next-generation, high-fidelity visible-to-shortwave infrared (VSWIR) imaging
spectrometer, built by the California Institute of Technology’s Jet Propulsion
Laboratory (JPL) for the Global Airborne Observatory, formerly the Carnegie
Airborne Observatory (Asner et al. 2012a). JPL then built an identical instrument
for NASA’s Airborne Visible/Infrared Imaging Spectrometer (AVIRIS; http://aviris.
jpl.nasa.gov) program, as well as several copies for the US National Ecological
Observatory Network (NEON, https://www.neonscience.org; Kampe et al. 2011).
5.3.4 Scientific and Conservation Opportunities
An important outgrowth of Spectranomics is an emerging opportunity to partner
discovery-based science with applied environmental conservation at large geographic scales. Conservation and management actions are usually limited in scope
and effectiveness by numerous interacting financial, logistical, cultural, and political factors. An increasing ability to map canopy diversity may provide an avenue to
identify the location and essential components of high-value conservation targets.
Moreover, near-real-time scientific discovery from spectral RS can lead to more
tactical conservation decision-making. Our specific experience is that, as land use
pressures expand, intensify, and change over time, a mapping capability built upon
the details of forest canopy function and composition, rather than just forest cover,
supports improved conservation discussions and planning. This type of approach is
needed to identify current and potential threats to, as well as current protections
and opportunities for new protection of, species, communities, and ecosystems.
The evolving biodiversity mapping capabilities made possible through
Spectranomics are providing a tool set to support the current portfolio of Global
Airborne Observatory activities (e.g., http://www.theborneopost.com/2016/04/06/3dmapping-to-decide-on-land-use/).
The Spectranomics approach is starting to catch on in the scientific community,
as highlighted in chapters throughout this book as well as new programs such as
NEON and Canada’s recently announced Spectranomics program for boreal forests
(the Canadian Airborne Biodiversity Observatory; http://www.caboscience.org/),
but there is much more to do to bring our approach to the global level. First, more
scientists could get involved through building plant canopy trait laboratories and
databases, paired with a specific style of leaf-level spectral measurements in the
field. Currently, many functional trait and spectral measurement protocols are
incompatible with the Spectranomics approach. For example, many foliar trait
studies have involved the collection of samples in understory or shaded settings,
5 Lessons Learned from Spectranomics: Wet Tropical Forests