Supplement 1 Explanation, biological interpretation, and PMM analog of the ten surface metrics
calculated for 2211 landscapes. This table is based largely on the supplementary material from
McGarigal et al (2009).
Metric
Characteristics
Amplitude Metrics
Average
surface
roughness
Ten- point
height
Measures aspects of
landscape composition
but not configuration.
Sensitive to overall
height distribution.
Ssk
Skewness
Sku
Kurtosis
Measures symmetry of
the surface height
distribution.
A measure of the shape
of the surface height
distribution.
Sa
S10z
Sensitive to deep valleys
or high peaks.
Meaning
Interpretation
PMM
Average deviation of height from
mean height.
Non-spatial measures of landscape
diversity.
The larger the values of Sa and S10z
the larger the landscape richness.
Patch-based
diversity metrics
High (positive or negative) skewness
indicates a landscape dominated by
high or low values.
High kurtosis: landscape with greater
abundance of high and low values
Low kurtosis: landscape with greater
abundance of mean values.
In combination with surface skewness
it explains the degree and nature of
landscape dominance.
Patch-based
evenness
metrics.
Contrast
between habitat
and matrix.
Increasing variability and steepness of
local slopes: increasing density of edges
and the magnitude contrast between
abutting high quality habitat areas along
those edges.
Contrastweighted edge
density metric.
Ranges between 0-180
Only meaningful if there is a dominate
direction and is =0 otherwise.
Direction that crosses repeated higher
contrasts.
Ranges from 0 - 1.
Surfaces with very dominant
directions: Stdi ~ 0.
If all directions are similar: Stdi ~ 1.
Ranges from 0 – 1.
Surfaces with very dominant radial
wavelengths: Srwi ~ 0.
If there is no dominating wavelength:
Srwi ~ 1.
Ranges from 2 – 4.
Larger values indicate a fractal surface
with an increasing dominant radial
wavelength.
NA
Measure of landscape dominance and
nature of the surface composition.
Matrix and
patch
distribution in
the landscape.
Average difference between
surface mean and most extreme
heights and depths.
Skewness of height distribution
towards high or low values.
Peakedness of the height
distribution.
More constant height =
Platykurtic (Sku < 3).
Large-tailed height distribution
=Leptokurtic (Sku > 3).
Configuration Metrics
Sdr
Std
Stdi
Surface
area ratio
Dominant
texture
direction
Texture
direction
index
Srwi
Radial
wavelength
index
Sfd
Fractal
dimension
Configuration metrics
common shared
characteristics:
 Measure compositional
and configurational
aspects of the
landscape.
 Measure horizontal and
vertical aspects of
surface deviation.
 Sensitive to variability
in distribution and
spatial arrangement of
heights.
Ratio between the surface area
to the area of a flat plane with
the same x-y dimensions.
Totally flat surface: Sdr = 0 %.
Sdr increases with the local
slope variability.
Direction of the dominant
amplitude calculated from the
Fourier spectrum.
Relative dominance of
amplitude in direction Std over
other directions.
Relative dominance wavelengths
over all other radial distances.
Calculated for the different
angles of the angular spectrum
by analyzing the Fourier
amplitude spectrum.
NA
NA
NA
Bearing Metric
Sbi
Surface
bearing
index
Cumulative measure of
vertical aspects of
surface deviation based
on Abbott curve.
Landscape composition
only metrics.
Measure of the surface
height shape profile.
Sensitive to occasional
high peaks and not deep
valleys.
Ratio of the root mean square
roughness to the height from
the top of the surface to the
height at 5% bearing area.
Normal height distribution:
Sbi = 0.608.
Relatively few high peaks:
Sbi < 0.608.
Relatively many high peaks or
no high peaks:
Sbi > 0.608.