520
Turner et al. 2003; Jetz et al. 2016; Luque et al. 2018). The chapters in this book
examine the use of RS to characterize and monitor biodiversity, focused largely on
plant diversity. The authors have collectively explained the technologies involved
and the analytical and conceptual approaches available for applying RS to monitor
changes in the multiple dimensions of biodiversity and for evaluating ecosystem
condition and function. The techniques discussed reflect recent advances in RS
technologies, which have enabled massive increases in the amount of data available,
and data science, which has developed new methods for applying these data to the
detection and prediction of biodiversity. These advances are occurring in parallel
with those in computing technology and statistical and analytical methods.
Integrating all of these advances creates new opportunities to monitor biodiversity
change and ecosystem condition and function at a global scale. Coincidentally,
these opportunities arise at a time when the climate is changing rapidly and human
population continues to grow, both of which further increase pressures on the
world’s natural systems and its biodiversity, accelerating declines that began decades
ago. The emergence of international efforts to develop a global biodiversity monitoring system that can integrate RS with traditional field methods offers some hope
that the ability to assess change and enhance management efforts can be improved.
Spaceborne RS has special value for monitoring these biodiversity changes
because it is global, consistent, periodic, and, for Landsat, has a retrospective record
going back more than 40 years. A system that combines the techniques, approaches,
and lessons learned described in this book’s 19 chapters would support monitoring
Earth’s biodiversity globally and at unprecedented levels of spatial and temporal
resolution. Such a system would facilitate breakthroughs in scientific knowledge as
well as provide previously unavailable information to manage biodiversity and natural resources. But spaceborne RS, by itself, is not enough. Utilizing it requires a
suite of additional data, including airborne RS and a wide variety of in-situ measurements, so these must also be part of any global monitoring system.
How can these many pieces be brought together? It seems a fitting way to end
this book by briefly exploring ideas for a system that can do that.
20.1 Current Situation
Most RS technology and instrumentation are developed and operated by government space agencies such as the National Aeronautics and Space Administration
(NASA, USA) and the European Space Agency (ESA, Europe); while there are
others, these organizations currently provide the bulk of the world’s freely accessible data. Agencies such as these acquire, store, manage, and process data; they distribute data that support development of the algorithms used to generate these
products. While some recent projects take a different approach, traditionally, development was assigned to specific funded teams to develop algorithms, which were
then used to generate a mostly static list of standard products over the life of a
particular satellite program. These products are available for download by individual users who can then process them further and apply them to problems of interest.
G. N. Geller et al.
Turner et al. 2003; Jetz et al. 2016; Luque et al. 2018). The chapters in this book
examine the use of RS to characterize and monitor biodiversity, focused largely on
plant diversity. The authors have collectively explained the technologies involved
and the analytical and conceptual approaches available for applying RS to monitor
changes in the multiple dimensions of biodiversity and for evaluating ecosystem
condition and function. The techniques discussed reflect recent advances in RS
technologies, which have enabled massive increases in the amount of data available,
and data science, which has developed new methods for applying these data to the
detection and prediction of biodiversity. These advances are occurring in parallel
with those in computing technology and statistical and analytical methods.
Integrating all of these advances creates new opportunities to monitor biodiversity
change and ecosystem condition and function at a global scale. Coincidentally,
these opportunities arise at a time when the climate is changing rapidly and human
population continues to grow, both of which further increase pressures on the
world’s natural systems and its biodiversity, accelerating declines that began decades
ago. The emergence of international efforts to develop a global biodiversity monitoring system that can integrate RS with traditional field methods offers some hope
that the ability to assess change and enhance management efforts can be improved.
Spaceborne RS has special value for monitoring these biodiversity changes
because it is global, consistent, periodic, and, for Landsat, has a retrospective record
going back more than 40 years. A system that combines the techniques, approaches,
and lessons learned described in this book’s 19 chapters would support monitoring
Earth’s biodiversity globally and at unprecedented levels of spatial and temporal
resolution. Such a system would facilitate breakthroughs in scientific knowledge as
well as provide previously unavailable information to manage biodiversity and natural resources. But spaceborne RS, by itself, is not enough. Utilizing it requires a
suite of additional data, including airborne RS and a wide variety of in-situ measurements, so these must also be part of any global monitoring system.
How can these many pieces be brought together? It seems a fitting way to end
this book by briefly exploring ideas for a system that can do that.
20.1 Current Situation
Most RS technology and instrumentation are developed and operated by government space agencies such as the National Aeronautics and Space Administration
(NASA, USA) and the European Space Agency (ESA, Europe); while there are
others, these organizations currently provide the bulk of the world’s freely accessible data. Agencies such as these acquire, store, manage, and process data; they distribute data that support development of the algorithms used to generate these
products. While some recent projects take a different approach, traditionally, development was assigned to specific funded teams to develop algorithms, which were
then used to generate a mostly static list of standard products over the life of a
particular satellite program. These products are available for download by individual users who can then process them further and apply them to problems of interest.
G. N. Geller et al.