237
through clouds. A recent book, Remote Sensing of the Cryosphere (Tedesco 2014),
describes these tools and methods in great detail; here we review some of the major
techniques. In all of the discussion below, the importance of change over time is
paramount; inter- and intra-annual variation in snow and ice cover are important
drivers of physical and biological processes.
The 3-D extent of snow and ice can easily be mapped using optical techniques;
snow reflects strongly in the visible and near-infrared (NIR) range but absorbs in the
shortwave infrared (SWIR), making it spectrally distinct from other white objects
such as rooftops and clouds. These distinctions may still be challenging with multispectral sensors, but hyperspectral sensors permit mapping of snow versus clouds
and even some estimation of snow particle size (e.g., Burakowski et al. 2015).
Passive microwave sensors can be used to estimate snow depth and snow water
equivalent, while active microwave sensors can map liquid water content. Tools and
techniques for mapping snow are reviewed by Dietz et al. (2011).
Ice and permafrost features can be mapped with many of the tools and methods
described in preceding sections. Snow cover can be mapped using optical sensors
and methods; subsidence of the cryosphere can be mapped with SRTM (near global
extent, 30–90 m spatial resolution, single snapshot in time) and SAR (airborne, 2 m
spatial resolution); and passive microwave radiometers such as SMOS (global
extent, 50 km spatial resolution, 3-day temporal resolution) and SMAP (near global
extent for low-vegetation areas, 9–36 km spatial resolution, 8-day temporal resolution) can be used to map frozen versus thawed ground surfaces (Entekhabi et al.
2014). Because glaciers and ice sheets are fundamentally a combination of snow,
ice, and liquid water, many of the techniques described above, such as optical sensors and passive microwave radiometers, can be used to map their extent and status.
In addition, the GLAS sensor onboard the Ice, Cloud, and land Elevation Satellite
(ICESat; near global spatial extent, 70 m spatial resolution, 91-day temporal resolution from 2003 to 2009) permitted the mapping of ice sheet mass balance (Zwally
et al. 2011). ICESat-2 is scheduled for launch in 2018 (global spatial extent, 14 km
spatial resolution, 91-day temporal resolution). SAR has also been used to map ice
flow on Antarctica (Rignot et al. 2011).
Sea, lake, and river ice cover can be mapped using optical techniques (Jeffries
et al. 2005), while thickness has been measured using ICESat and passive microwave sensors (e.g., Kwok and Rothrock 2009). The difference between first-year
sea ice and older sea ice can be identified by changes in salinity using multichannel
passive microwave sensors like the Advanced Microwave Scanning Radiometer for
Earth Observing System (AMSR-E) onboard NASA’s Aqua satellite (global spatial
extent, 474 km spatial resolution, 12-hour temporal resolution, operational
2002–2015). River ice mapping is critical for monitoring and predicting river habitat quality and duration for a variety of organisms (e.g., Charney and Record 2016;
Pavelsky and Zarnetske 2017). The extent and duration of river icing types have
been mapped with different polarizations of passive microwave data from Canada’s
RADARSAT-1 (1995–2013) and RADARSAT-2 (launched 2007) (Weber et al.
2003; Jeffries et al. 2005; Yoshikawa et al. 2007 for aufeis features) and with
MODIS Terra (Pavelsky and Zarnetske 2017).
10 Remote Sensing of Geodiversity as a Link to Biodiversity
through clouds. A recent book, Remote Sensing of the Cryosphere (Tedesco 2014),
describes these tools and methods in great detail; here we review some of the major
techniques. In all of the discussion below, the importance of change over time is
paramount; inter- and intra-annual variation in snow and ice cover are important
drivers of physical and biological processes.
The 3-D extent of snow and ice can easily be mapped using optical techniques;
snow reflects strongly in the visible and near-infrared (NIR) range but absorbs in the
shortwave infrared (SWIR), making it spectrally distinct from other white objects
such as rooftops and clouds. These distinctions may still be challenging with multispectral sensors, but hyperspectral sensors permit mapping of snow versus clouds
and even some estimation of snow particle size (e.g., Burakowski et al. 2015).
Passive microwave sensors can be used to estimate snow depth and snow water
equivalent, while active microwave sensors can map liquid water content. Tools and
techniques for mapping snow are reviewed by Dietz et al. (2011).
Ice and permafrost features can be mapped with many of the tools and methods
described in preceding sections. Snow cover can be mapped using optical sensors
and methods; subsidence of the cryosphere can be mapped with SRTM (near global
extent, 30–90 m spatial resolution, single snapshot in time) and SAR (airborne, 2 m
spatial resolution); and passive microwave radiometers such as SMOS (global
extent, 50 km spatial resolution, 3-day temporal resolution) and SMAP (near global
extent for low-vegetation areas, 9–36 km spatial resolution, 8-day temporal resolution) can be used to map frozen versus thawed ground surfaces (Entekhabi et al.
2014). Because glaciers and ice sheets are fundamentally a combination of snow,
ice, and liquid water, many of the techniques described above, such as optical sensors and passive microwave radiometers, can be used to map their extent and status.
In addition, the GLAS sensor onboard the Ice, Cloud, and land Elevation Satellite
(ICESat; near global spatial extent, 70 m spatial resolution, 91-day temporal resolution from 2003 to 2009) permitted the mapping of ice sheet mass balance (Zwally
et al. 2011). ICESat-2 is scheduled for launch in 2018 (global spatial extent, 14 km
spatial resolution, 91-day temporal resolution). SAR has also been used to map ice
flow on Antarctica (Rignot et al. 2011).
Sea, lake, and river ice cover can be mapped using optical techniques (Jeffries
et al. 2005), while thickness has been measured using ICESat and passive microwave sensors (e.g., Kwok and Rothrock 2009). The difference between first-year
sea ice and older sea ice can be identified by changes in salinity using multichannel
passive microwave sensors like the Advanced Microwave Scanning Radiometer for
Earth Observing System (AMSR-E) onboard NASA’s Aqua satellite (global spatial
extent, 474 km spatial resolution, 12-hour temporal resolution, operational
2002–2015). River ice mapping is critical for monitoring and predicting river habitat quality and duration for a variety of organisms (e.g., Charney and Record 2016;
Pavelsky and Zarnetske 2017). The extent and duration of river icing types have
been mapped with different polarizations of passive microwave data from Canada’s
RADARSAT-1 (1995–2013) and RADARSAT-2 (launched 2007) (Weber et al.
2003; Jeffries et al. 2005; Yoshikawa et al. 2007 for aufeis features) and with
MODIS Terra (Pavelsky and Zarnetske 2017).
10 Remote Sensing of Geodiversity as a Link to Biodiversity