270
become prevalent (Masters and Norgrove 2010). Therefore, minimizing IAS spread
is necessary to meet the targets in UN Sustainable Development Goal 15, Life on
Land, which has a target focusing specifically on preventing introduction, controlling, and eradicating IAS. The European Environmental Agency (EEA 2012) has
also developed an “invasive alien species in Europe” indicator summarizing the
trends of invasions since 1900 and the greatest biodiversity threats. Meanwhile the
US National Invasive Species Council coordinates and facilitates data interoperability across data providers and users, including defining data standards, formats, and
protocols and facilitating cooperation across sectors and governments (National
Invasive Species Council 2016).
In order to reduce the pressure of IAS on biodiversity and ecosystems, globally
integrated approaches to IAS prioritization, management, and control are needed.
Fundamental to international cooperation is cross-border policy and cooperation
and transboundary assessments that are implemented within a global monitoring
framework (Latombe et al. 2017). Following the Essential Biodiversity Variable
(EBV) concept (see Fernández et al., Chap. 18), essential variables for invasion
monitoring have recently been proposed by Latombe et al. (2017) to underpin a
global monitoring system for IAS. Essential variables for IAS include occurrence,
alien status, and alien species impact. Remote sensing (RS) is a valuable observation tool in this new EBV framework because it can be used to identify locations,
cover, abundance, biomass, and other traits of IAS. Because it provides synoptic
spatial, routine monitoring with fine scale, high-resolution RS can be used to identify sources of IAS and pathways for spread. RS-enabled IAS location data can
inform control decisions and, with routine monitoring, can be used to quantify
trends and predict invasion processes into the future to support policy decisions and
management actions aimed at preventing undesired spread.
12.1.3 Remote Sensing for Detection of Plant Invasions
RS has long been favored as a tool for IAS mapping, specifically for plants, due to
its ability to provide synoptic views over large geographical extents. This provides
an advantage over field surveys, which are often limited to a small areas and may be
in difficult to access locations. Historically, RS has been crucial in IAS detection.
As far back as the 1970s, color infrared (IR) photos captured from airplanes were
used to target herbicide applications to control water hyacinth (Eichhornia crassipes)
infestations (Rouse et al. 1975). Over time, the state of the science has progressed
substantially. Current technologies such as hyperspectral imaging spectroscopy and
light detection and ranging (lidar) make it possible to detect and differentiate plant
species within the same functional groups. Coupled with advances in image processing algorithms, these technologies have enabled accurate, repeatable RS measurements over time, providing consistent monitoring records to support control
efforts.
E. A. Bolch et al.
become prevalent (Masters and Norgrove 2010). Therefore, minimizing IAS spread
is necessary to meet the targets in UN Sustainable Development Goal 15, Life on
Land, which has a target focusing specifically on preventing introduction, controlling, and eradicating IAS. The European Environmental Agency (EEA 2012) has
also developed an “invasive alien species in Europe” indicator summarizing the
trends of invasions since 1900 and the greatest biodiversity threats. Meanwhile the
US National Invasive Species Council coordinates and facilitates data interoperability across data providers and users, including defining data standards, formats, and
protocols and facilitating cooperation across sectors and governments (National
Invasive Species Council 2016).
In order to reduce the pressure of IAS on biodiversity and ecosystems, globally
integrated approaches to IAS prioritization, management, and control are needed.
Fundamental to international cooperation is cross-border policy and cooperation
and transboundary assessments that are implemented within a global monitoring
framework (Latombe et al. 2017). Following the Essential Biodiversity Variable
(EBV) concept (see Fernández et al., Chap. 18), essential variables for invasion
monitoring have recently been proposed by Latombe et al. (2017) to underpin a
global monitoring system for IAS. Essential variables for IAS include occurrence,
alien status, and alien species impact. Remote sensing (RS) is a valuable observation tool in this new EBV framework because it can be used to identify locations,
cover, abundance, biomass, and other traits of IAS. Because it provides synoptic
spatial, routine monitoring with fine scale, high-resolution RS can be used to identify sources of IAS and pathways for spread. RS-enabled IAS location data can
inform control decisions and, with routine monitoring, can be used to quantify
trends and predict invasion processes into the future to support policy decisions and
management actions aimed at preventing undesired spread.
12.1.3 Remote Sensing for Detection of Plant Invasions
RS has long been favored as a tool for IAS mapping, specifically for plants, due to
its ability to provide synoptic views over large geographical extents. This provides
an advantage over field surveys, which are often limited to a small areas and may be
in difficult to access locations. Historically, RS has been crucial in IAS detection.
As far back as the 1970s, color infrared (IR) photos captured from airplanes were
used to target herbicide applications to control water hyacinth (Eichhornia crassipes)
infestations (Rouse et al. 1975). Over time, the state of the science has progressed
substantially. Current technologies such as hyperspectral imaging spectroscopy and
light detection and ranging (lidar) make it possible to detect and differentiate plant
species within the same functional groups. Coupled with advances in image processing algorithms, these technologies have enabled accurate, repeatable RS measurements over time, providing consistent monitoring records to support control
efforts.
E. A. Bolch et al.