234
Copernicus program has long been used for mapping lithography in exposed surface environments (Rowan and Mars 2003; Hewson et al. 2005; Massironi et al.
2008; van der Werff and van der Meer 2016). Hyperspectral imagery has been used
successfully to map minerals in many low-vegetation landscapes. For example, the
Hyperion sensor, aboard the now decommissioned EO-1 satellite, was used to map
mineralogy in Australia (Cudahy et al. 2001). The Airborne Visible/Infrared
Imaging Spectrometer (AVIRIS) and new AVIRIS-Next Generation missions continue to push the boundary of imaging spectroscopy used in mineral mapping
(Krause et al. 1993; Crowley 1993; Green et al. 1998). These instruments can also
provide information on soil nutrient availability in areas dominated by vegetation
cover via the influence of soils on foliar chemistry (e.g., Ollinger et al. 2002).
Ground-based RS has also provided insights for subsurface geologic mapping.
For instance, ground-penetrating radar (GPR) uses radar pulses to map the relative
densities of materials belowground and effectively maps soil and bedrock in layers
(Davis and Annan 1989). Airborne GPR can greatly enhance the temporal and spatial resolution of geologic maps (Catapano et al. 2014; Campbell et al. 2018).
10.3.2 Atmosphere: Climate and Weather
Climate is an important control on mineral weathering, soil formation, and landforms (Jenny 1941). Surface temperature and cloud cover are readily observed with
RS. The Advanced Very High Resolution Radiometers [AVHRR; National
Oceanographic and Atmospheric Administration (NOAA)] have been collecting
surface radiation data in the visible, infrared, and thermal spectra with twice-daily
global coverage since 1981 that currently gathers data at ~1 km spatial resolution.
AVHRR data can be used to map cloud cover and land and water surface temperatures; however, changes in satellite technology and the lack of onboard calibration
in the AVHRR sensors have made the use of these data challenging due to a need for
standardization of data across satellite technologies (Cao et al. 2008). The launch of
the MODIS sensors on NASA’s Terra (launched in 1999) and Aqua (launched in
2002) satellites and ESA’s Sentinel-3 satellite as part of the Copernicus program
(3-A launched in 2016 and 3-B launched in 2018) significantly improved global
mapping capabilities. The two MODIS sensors map most of the planet twice a day
with 36 bands ranging from the visible to the thermal infrared. The MODIS bands
were selected to capture properties of the land surface but also ocean properties,
atmospheric water vapor, surface temperature, and clouds (Fig. 10.2). Products
from MODIS, such as surface temperature and cloud presence, have been used
either to directly map climate variables for use in ecological research (e.g., Cord and
Rödder 2011; Wilson and Jetz 2016) or to inform modeled climate products like
Worldclim-2 (Fick and Hijmans 2017). Furthermore, surface temperature can better
characterize plant ecological differences (Still et al. 2014) because it more accurately captures canopy temperature, which is not the same as air temperature, and
because many air temperature products (such as Worldclim-2) are interpolated (see
Pinto-Ledézma and Cavender-Bares, Chap. 9).
S. Record et al.
Copernicus program has long been used for mapping lithography in exposed surface environments (Rowan and Mars 2003; Hewson et al. 2005; Massironi et al.
2008; van der Werff and van der Meer 2016). Hyperspectral imagery has been used
successfully to map minerals in many low-vegetation landscapes. For example, the
Hyperion sensor, aboard the now decommissioned EO-1 satellite, was used to map
mineralogy in Australia (Cudahy et al. 2001). The Airborne Visible/Infrared
Imaging Spectrometer (AVIRIS) and new AVIRIS-Next Generation missions continue to push the boundary of imaging spectroscopy used in mineral mapping
(Krause et al. 1993; Crowley 1993; Green et al. 1998). These instruments can also
provide information on soil nutrient availability in areas dominated by vegetation
cover via the influence of soils on foliar chemistry (e.g., Ollinger et al. 2002).
Ground-based RS has also provided insights for subsurface geologic mapping.
For instance, ground-penetrating radar (GPR) uses radar pulses to map the relative
densities of materials belowground and effectively maps soil and bedrock in layers
(Davis and Annan 1989). Airborne GPR can greatly enhance the temporal and spatial resolution of geologic maps (Catapano et al. 2014; Campbell et al. 2018).
10.3.2 Atmosphere: Climate and Weather
Climate is an important control on mineral weathering, soil formation, and landforms (Jenny 1941). Surface temperature and cloud cover are readily observed with
RS. The Advanced Very High Resolution Radiometers [AVHRR; National
Oceanographic and Atmospheric Administration (NOAA)] have been collecting
surface radiation data in the visible, infrared, and thermal spectra with twice-daily
global coverage since 1981 that currently gathers data at ~1 km spatial resolution.
AVHRR data can be used to map cloud cover and land and water surface temperatures; however, changes in satellite technology and the lack of onboard calibration
in the AVHRR sensors have made the use of these data challenging due to a need for
standardization of data across satellite technologies (Cao et al. 2008). The launch of
the MODIS sensors on NASA’s Terra (launched in 1999) and Aqua (launched in
2002) satellites and ESA’s Sentinel-3 satellite as part of the Copernicus program
(3-A launched in 2016 and 3-B launched in 2018) significantly improved global
mapping capabilities. The two MODIS sensors map most of the planet twice a day
with 36 bands ranging from the visible to the thermal infrared. The MODIS bands
were selected to capture properties of the land surface but also ocean properties,
atmospheric water vapor, surface temperature, and clouds (Fig. 10.2). Products
from MODIS, such as surface temperature and cloud presence, have been used
either to directly map climate variables for use in ecological research (e.g., Cord and
Rödder 2011; Wilson and Jetz 2016) or to inform modeled climate products like
Worldclim-2 (Fick and Hijmans 2017). Furthermore, surface temperature can better
characterize plant ecological differences (Still et al. 2014) because it more accurately captures canopy temperature, which is not the same as air temperature, and
because many air temperature products (such as Worldclim-2) are interpolated (see
Pinto-Ledézma and Cavender-Bares, Chap. 9).
S. Record et al.