4
systems to emerging satellite systems. As a consequence, there is high potential to
detect and monitor plant diversity—and other forms of diversity—across a range of
spatial scales, and to do so iteratively and continuously, particularly if multiple
methods can be properly coordinated.
Calls for a global biodiversity observatory (Fig. 1.2) that can detect and monitor
functional plant diversity from space (Jetz et al. 2016; Proença et al. 2017; The
National Academy of Sciences 2017; Geller et al., Chap. 20) have been met with
widespread support. Forthcoming satellite missions, including the Surface Biology
and Geology (SBG) mission in planning stages at the US National Aeronautics and
Space Administration (NASA) and related missions in Europe and Japan (Schimel
et al., Chap. 19), will make unprecedented spectroscopic data available to scientists,
management communities, and decision-makers, but at relatively coarse spatial
scales. At the same time, rapid progress is being made with field spectroscopy using
unmanned aerial vehicles (UAVs) and other airborne platforms that are offering
novel ways to use RS to advance our understanding of the linkages between optical
(e.g., spectral or structural) diversity and multiple dimensions of biodiversity (e.g.,
species, functional, and phylogenetic diversity) at finer spatial scales (Fig. 1.1).
These advances present a timely and tremendously important opportunity to detect
changes in the Earth’s biodiversity over large regions of the planet. One can fairly
ask whether user communities are ready to make use of the data. Effective interpretation and application of remotely sensed data to determine the status and trends of
plant biodiversity and plant functions across the tree of life—with linkages to all
other living organisms—requires integration across vastly different knowledge arenas. Critically, it requires integration with in-situ direct and indirect measures of
species distributions, their evolutionary relationships, and their functions.
Approaches for integration are the primary focus of this book.
A central requirement to advance monitoring of biodiversity at the global scale
is to decipher the sources of variation that contribute to spectral variation, both from
a biological perspective and from a physical perspective. Distinct fields of biology
have developed a range of methodologies for understanding plant ecological and
evolutionary processes that underlie these sources of variation. Similarly, radiative
transfer models have been developed largely based on the physics of light interacting with vegetation canopy elements and the atmosphere. These models have yet to
capture the full range of plant traits, often preferring to represent “average” vegetation conditions for a region instead of the variation present, so are not yet ready for
the task. All of these methods have unique approaches to analyzing complex, multidimensional data sets, and neither the analytical approaches nor the data structures
have been brought together in a systematic or comprehensive manner. A common
language among disciplines (including biology, physiological ecology, landscape
ecology, genetics, phylogenetics, geography, spectroscopy, and radiative transfer)
related to the RS of biodiversity is currently lacking. This book provides a framework for how biodiversity, focusing particularly on plants, can be detected using
proximally and remotely sensed hyperspectral data (with many contiguous spectral
bands) and other tools, such as lidar (with its ability to detect structure). The chapters in this book present a range of perspectives and approaches on how RS can be
J. Cavender-Bares et al.
systems to emerging satellite systems. As a consequence, there is high potential to
detect and monitor plant diversity—and other forms of diversity—across a range of
spatial scales, and to do so iteratively and continuously, particularly if multiple
methods can be properly coordinated.
Calls for a global biodiversity observatory (Fig. 1.2) that can detect and monitor
functional plant diversity from space (Jetz et al. 2016; Proença et al. 2017; The
National Academy of Sciences 2017; Geller et al., Chap. 20) have been met with
widespread support. Forthcoming satellite missions, including the Surface Biology
and Geology (SBG) mission in planning stages at the US National Aeronautics and
Space Administration (NASA) and related missions in Europe and Japan (Schimel
et al., Chap. 19), will make unprecedented spectroscopic data available to scientists,
management communities, and decision-makers, but at relatively coarse spatial
scales. At the same time, rapid progress is being made with field spectroscopy using
unmanned aerial vehicles (UAVs) and other airborne platforms that are offering
novel ways to use RS to advance our understanding of the linkages between optical
(e.g., spectral or structural) diversity and multiple dimensions of biodiversity (e.g.,
species, functional, and phylogenetic diversity) at finer spatial scales (Fig. 1.1).
These advances present a timely and tremendously important opportunity to detect
changes in the Earth’s biodiversity over large regions of the planet. One can fairly
ask whether user communities are ready to make use of the data. Effective interpretation and application of remotely sensed data to determine the status and trends of
plant biodiversity and plant functions across the tree of life—with linkages to all
other living organisms—requires integration across vastly different knowledge arenas. Critically, it requires integration with in-situ direct and indirect measures of
species distributions, their evolutionary relationships, and their functions.
Approaches for integration are the primary focus of this book.
A central requirement to advance monitoring of biodiversity at the global scale
is to decipher the sources of variation that contribute to spectral variation, both from
a biological perspective and from a physical perspective. Distinct fields of biology
have developed a range of methodologies for understanding plant ecological and
evolutionary processes that underlie these sources of variation. Similarly, radiative
transfer models have been developed largely based on the physics of light interacting with vegetation canopy elements and the atmosphere. These models have yet to
capture the full range of plant traits, often preferring to represent “average” vegetation conditions for a region instead of the variation present, so are not yet ready for
the task. All of these methods have unique approaches to analyzing complex, multidimensional data sets, and neither the analytical approaches nor the data structures
have been brought together in a systematic or comprehensive manner. A common
language among disciplines (including biology, physiological ecology, landscape
ecology, genetics, phylogenetics, geography, spectroscopy, and radiative transfer)
related to the RS of biodiversity is currently lacking. This book provides a framework for how biodiversity, focusing particularly on plants, can be detected using
proximally and remotely sensed hyperspectral data (with many contiguous spectral
bands) and other tools, such as lidar (with its ability to detect structure). The chapters in this book present a range of perspectives and approaches on how RS can be
J. Cavender-Bares et al.