Geoscience Reference
In-Depth Information
using color infrared (CIR) aerial photographs (1:24,000 scale) collected in 1995 (SEMCOG, 1995).
The classes were based on a modified Anderson et al. (1976) system, which we reclassified to high-
density residential, low-density residential, other urban, and other. The second was a LC classifi-
cation created through unsupervised clustering and subsequent cluster labeling of scanned color-
infrared photography (1:58,000-scale) collected in 1998. The LC classes were forest, herbaceous,
impervious, bare soil, wetland, and open water. The two maps were overlaid to identify the
correspondence between the LC classes and the urban LU classes. The percentages of forest and
impervious cover were calculated within each of the urban LU types.
16.3.3
Landscape Simulations
16.3.3.1
Ecotone Abruptness
An experiment was designed in which 25 different landscape types were defined, each repre-
senting a combination of among five different levels of abruptness and five levels of patchiness
(Bowersox and Brown, 2001). Ecotone abruptness (i.e., how quickly an ecotone transitioned from
forest to nonforest) was controlled by altering the parameters of a mathematical function to model
the change from high to low values along the gradient representing forested cover. Patchiness was
introduced by combining the mathematical surface with a randomized surface that was smoothed
to introduce varying degrees of spatial autocorrelation. Once the combined gradient was created,
all cells with a value above a set threshold were classified as forest, and those below were classified
as nonforest. The threshold was set so that each simulated landscape was 50% forested and 50%
nonforested.
For each type of landscape, 50 different simulations were conducted. The ability of each
landscape metric to detect abruptness was then tested by comparing the values of the 50 simulations
among the different cover types. The landscape metric values were compared among the abruptness
and patchiness levels using analysis of variance (ANOVA). The ANOVA results were analyzed to
identify the most suitable metrics for measuring abruptness (i.e., those exhibiting a high degree of
variation between landscape types with variable abruptness levels but a low degree of variation
between landscape types with variable patchiness).
In addition to several patch-based metrics (including area-weight patch fractal dimension, area-
weighted mean shape index, contagion, and total edge), boundary-based metrics were used, includ-
ing (1) number of boundary elements, (2) number of subgraphs, and (1) maximum subgraph length.
The analysis compared the ability of two new boundary-based metrics designed specifically to
measure ecotone abruptness and distinguish different levels of abruptness. These new metrics
characterize the dispersion of boundary elements around an “average ecotone position,” calculated
as the centroid of all boundary elements, and the area under the curve of the number of boundary
elements vs. the slope threshold level.
16.3.3.2
Fragmentation
The sensitivity of several potential measures of forest fragmentation to the amount of forest
was also investigated through simulation. The simulation included: (1) generating a random map
for 100-
100-grid cells with pixel values randomly drawn from a normal distribution (mean = 0,
standard deviation = 1), (2) smoothing with a five-by-five averaging filter to introduce spatial
autocorrelation, and (3) creating maps (
¥
= 10) by classifying cells as forest or nonforest based on
different threshold levels. The threshold levels were defined so that the different maps had a
uniformly increasing amount of forest from about 9% to about 91% (Figure 16.2). By extracting
the maps with different proportions of forest from the same simulated surface, patterns were
controlled and the dominant difference among maps was the amount forested. The simulation
process was repeated 10 times to produce a range of output values at each landscape proportion level.
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