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10.3.1 Lithosphere
10.3.1.1 Lithosphere: Topography
Topographic barriers can influence geographic patterns of biodiversity by physically
isolating populations of plants and animals (Janzen 1967). Topography also can be
used as an indirect measure of microclimate, as topographic position can influence
temperature and precipitation (e.g., Ollinger et al. 1995). Topography of the lithosphere crust is often represented by elevation (the height above sea level of a given
point on the ground) or bathymetry (the depth to the bottom of a water body). In
February 2000 the SRTM radar system flew on the US Space Shuttle Endeavour for
11 days collecting radar-derived elevation data from 60°N to 56°S. These data were
originally released at 90 m resolution; however, in 2015, 30 m data (1 arc second)
were released for the entire SRTM extent. There are many other sources of elevation
data including NASA Advanced Spaceborne Thermal Emission and Reflection
Radiometer ASTER (Fig. 10.2), active radar satellites designed for ice measurement
(see the Cryosphere section), and more. NASA is currently working to develop a
best available digital elevation model (DEM) for the planet, NASADEM. For this
the entire SRTM data set will be reprocessed, Geoscience Laser Altimeter System
(GLAS) data will be incorporated to remove artifacts, and the Advanced Spaceborne
Thermal Emission and Reflection Radiometer Global Digital Elevation Model version 2 (ASTER) and Global Digital Elevation Map (GDEM) V2 DEMs will be used
for refinement.
Elevation is only one of many products under the umbrella of topography. Slope
(the angle between two elevation points) and aspect (the direction a slope is facing)
are two of the many indices that can be derived from elevation data. Importantly,
most of these indices are kernel-dependent, meaning they rely on data not just from
an individual point but from surrounding points as well. For example, ArcGIS 10.3
(ESRI; Redlands, California) calculates the slope of a given pixel (elevation value)
as the maximum slope between that center pixel and the eight surrounding pixels.
The “terrain” function in the raster package in R statistical software (Hijmans and
van Etten 2019) permits several different methods for calculating slope based on
either a 4- or an 8-cell kernel, and these calculations differ slightly from those in the
Geospatial Data Abstraction Library (GDAL; gdal.org). Environment for Visualizing
Images (ENVI) software (Harris Geospatial Solutions, Broomfield, Colorado)
allows the user to select any kernel size then fits a quadratic surface to the entire
kernel, calculating slope and other parameters based on that surface (Wood 1996).
These different methods could lead to somewhat different results; in particular, the
selection of a small versus a large kernel could change the slope estimated. Imagine,
for example, with fine-grained data, the inside of a tip-up pit on the side of a northfacing slope. The local aspect could be south facing, while a larger kernel could
reveal that the landscape is north facing.
Beyond slope and aspect, there are many other kernel-dependent topographic
measures. For instance, Topographic Position Index (TPI) is defined as the difference between a central pixel and the mean of its surrounding pixels. Terrain
10 Remote Sensing of Geodiversity as a Link to Biodiversity
10.3.1 Lithosphere
10.3.1.1 Lithosphere: Topography
Topographic barriers can influence geographic patterns of biodiversity by physically
isolating populations of plants and animals (Janzen 1967). Topography also can be
used as an indirect measure of microclimate, as topographic position can influence
temperature and precipitation (e.g., Ollinger et al. 1995). Topography of the lithosphere crust is often represented by elevation (the height above sea level of a given
point on the ground) or bathymetry (the depth to the bottom of a water body). In
February 2000 the SRTM radar system flew on the US Space Shuttle Endeavour for
11 days collecting radar-derived elevation data from 60°N to 56°S. These data were
originally released at 90 m resolution; however, in 2015, 30 m data (1 arc second)
were released for the entire SRTM extent. There are many other sources of elevation
data including NASA Advanced Spaceborne Thermal Emission and Reflection
Radiometer ASTER (Fig. 10.2), active radar satellites designed for ice measurement
(see the Cryosphere section), and more. NASA is currently working to develop a
best available digital elevation model (DEM) for the planet, NASADEM. For this
the entire SRTM data set will be reprocessed, Geoscience Laser Altimeter System
(GLAS) data will be incorporated to remove artifacts, and the Advanced Spaceborne
Thermal Emission and Reflection Radiometer Global Digital Elevation Model version 2 (ASTER) and Global Digital Elevation Map (GDEM) V2 DEMs will be used
for refinement.
Elevation is only one of many products under the umbrella of topography. Slope
(the angle between two elevation points) and aspect (the direction a slope is facing)
are two of the many indices that can be derived from elevation data. Importantly,
most of these indices are kernel-dependent, meaning they rely on data not just from
an individual point but from surrounding points as well. For example, ArcGIS 10.3
(ESRI; Redlands, California) calculates the slope of a given pixel (elevation value)
as the maximum slope between that center pixel and the eight surrounding pixels.
The “terrain” function in the raster package in R statistical software (Hijmans and
van Etten 2019) permits several different methods for calculating slope based on
either a 4- or an 8-cell kernel, and these calculations differ slightly from those in the
Geospatial Data Abstraction Library (GDAL; gdal.org). Environment for Visualizing
Images (ENVI) software (Harris Geospatial Solutions, Broomfield, Colorado)
allows the user to select any kernel size then fits a quadratic surface to the entire
kernel, calculating slope and other parameters based on that surface (Wood 1996).
These different methods could lead to somewhat different results; in particular, the
selection of a small versus a large kernel could change the slope estimated. Imagine,
for example, with fine-grained data, the inside of a tip-up pit on the side of a northfacing slope. The local aspect could be south facing, while a larger kernel could
reveal that the landscape is north facing.
Beyond slope and aspect, there are many other kernel-dependent topographic
measures. For instance, Topographic Position Index (TPI) is defined as the difference between a central pixel and the mean of its surrounding pixels. Terrain
10 Remote Sensing of Geodiversity as a Link to Biodiversity