9
degree, often measured as habitat heterogeneity, a key driver of species diversity. They
illustrate the approach by examining the relationship between biodiversity and geodiversity with tree biodiversity data from the US Forest Inventory and Analysis Program
and geodiversity data from remotely sensed elevation from the Shuttle Radar
Topography Mission (SRTM). In doing so, they outline the challenges and opportunities for using RS to link biodiversity to geodiversity.
Paz et al. (Chap. 11) present an approach for using RS data to predict patterns of
plant diversity and endemism in the tropics within the Brazilian Atlantic rainforest.
They examine how RS environmental data from tropical regions can be used to support biodiversity prediction at multiple spatial, temporal, and taxonomic scales.
Bolch et al. (Chap. 12) summarize the range of approaches that can be used to
optimize detection of invasive alien species (IAS), which pose severe threats to
biodiversity. These approaches emphasize the ability to detect individual plant species that have distinct functional properties. The chapter presents current RS capabilities to detect and track invasive plant species across terrestrial, riparian, aquatic,
and human-modified ecosystems. Each of these systems has a unique set of issues
and species assemblages with its own detection requirements. The authors examine
how RS data collection in the spectral, spatial, and temporal domains can be optimized for a particular invasive species based on the ecosystem type and image analysis approach. RS approaches are enhancing studies of the invasion processes and
enabling managers to monitor invasions and predict the spread of IAS.
The next three chapters of the book explore how components of diversity can be
detected spectrally and remotely with a focus on optical detection methods and
technical challenges. Lausch et al. (Chap. 13) delve into the complexity of monitoring vegetation diversity and explain how no single monitoring approach is sufficient
on its own. The chapter introduces the range of Earth observation (EO) techniques
available for assessing vegetation diversity, covering close-range EO platforms,
spectral approaches, plant phenomics facilities, ecotrons, wireless sensor networks
(WSNs), towers, air- and spaceborne EO platforms, UAVs, and approaches that
integrate air- and spaceborne EO data. The chapter presents the challenges with
these approaches and concludes with recommendations and future directions for
monitoring vegetation diversity using RS.
Ustin and Jacquemoud (Chap. 14) provide the physical basis for detecting the
optical properties of leaves based on how they modify the absorption and scattering
of energy to reveal variation in function. The chapter provides considerable detail
on how the combination of absorption and scattering properties of leaves together
creates the shape of their reflectance spectrum. It also reviews and summarizes the
most common interactions between leaf properties and light and the physical processes that regulate the outcomes of these interactions.
Schweiger (Chap. 15) describes a set of best practices for planning field campaigns
and collecting and processing data, focusing on spectral data of terrestrial plants
collected across various levels of measurements, from leaf to canopy to airborne.
These approaches also generally apply to RS of aquatic systems, soil, and the atmosphere and to active RS systems, such as lidar, thermal, and satellite data collection.
Schweiger discusses how goals for data collection can be broadly classified into
model calibration, model validation, and model interpretation.
1 The Use of Remote Sensing to Enhance Biodiversity Monitoring and Detection…
degree, often measured as habitat heterogeneity, a key driver of species diversity. They
illustrate the approach by examining the relationship between biodiversity and geodiversity with tree biodiversity data from the US Forest Inventory and Analysis Program
and geodiversity data from remotely sensed elevation from the Shuttle Radar
Topography Mission (SRTM). In doing so, they outline the challenges and opportunities for using RS to link biodiversity to geodiversity.
Paz et al. (Chap. 11) present an approach for using RS data to predict patterns of
plant diversity and endemism in the tropics within the Brazilian Atlantic rainforest.
They examine how RS environmental data from tropical regions can be used to support biodiversity prediction at multiple spatial, temporal, and taxonomic scales.
Bolch et al. (Chap. 12) summarize the range of approaches that can be used to
optimize detection of invasive alien species (IAS), which pose severe threats to
biodiversity. These approaches emphasize the ability to detect individual plant species that have distinct functional properties. The chapter presents current RS capabilities to detect and track invasive plant species across terrestrial, riparian, aquatic,
and human-modified ecosystems. Each of these systems has a unique set of issues
and species assemblages with its own detection requirements. The authors examine
how RS data collection in the spectral, spatial, and temporal domains can be optimized for a particular invasive species based on the ecosystem type and image analysis approach. RS approaches are enhancing studies of the invasion processes and
enabling managers to monitor invasions and predict the spread of IAS.
The next three chapters of the book explore how components of diversity can be
detected spectrally and remotely with a focus on optical detection methods and
technical challenges. Lausch et al. (Chap. 13) delve into the complexity of monitoring vegetation diversity and explain how no single monitoring approach is sufficient
on its own. The chapter introduces the range of Earth observation (EO) techniques
available for assessing vegetation diversity, covering close-range EO platforms,
spectral approaches, plant phenomics facilities, ecotrons, wireless sensor networks
(WSNs), towers, air- and spaceborne EO platforms, UAVs, and approaches that
integrate air- and spaceborne EO data. The chapter presents the challenges with
these approaches and concludes with recommendations and future directions for
monitoring vegetation diversity using RS.
Ustin and Jacquemoud (Chap. 14) provide the physical basis for detecting the
optical properties of leaves based on how they modify the absorption and scattering
of energy to reveal variation in function. The chapter provides considerable detail
on how the combination of absorption and scattering properties of leaves together
creates the shape of their reflectance spectrum. It also reviews and summarizes the
most common interactions between leaf properties and light and the physical processes that regulate the outcomes of these interactions.
Schweiger (Chap. 15) describes a set of best practices for planning field campaigns
and collecting and processing data, focusing on spectral data of terrestrial plants
collected across various levels of measurements, from leaf to canopy to airborne.
These approaches also generally apply to RS of aquatic systems, soil, and the atmosphere and to active RS systems, such as lidar, thermal, and satellite data collection.
Schweiger discusses how goals for data collection can be broadly classified into
model calibration, model validation, and model interpretation.
1 The Use of Remote Sensing to Enhance Biodiversity Monitoring and Detection…