Coefficient of variation of patches.
Example: Coefficient of Variation of Conifer patches (Class Level) PSCoV = PSSD/MPS = (11.05 hectares / 17.42 hectares) *100 = 63 Example: Coefficient of Variation of all patches (Landscape Level) PSCoV = (9.51 hectares / 13.15 hectares)*100 =72
Total Edge (TE) Perimeter of patches.
Example: Total Edge Conifer (Class Level) TE = Sum of perimeter of all conifer patches. TE = 10858.88 metres
Units are expressed in native maps units. Example: Total Edge all patches (Landscape Level) TE = Sum of perimeter of all patches TE = 28607.27 metres Important
In the case of vector layers (themes), edge calculations include all the edge on the landscape including boundary edge. The contrasted weighted edge feature allows edge weight at the
boundaries to be set to zero. In the case of raster (grid) layers (themes), edge calculations do not include the edges that surround the landscape boundary edge or any interior edges that include pixels classified as No Data.
Edge Density (ED)
Amount of edge relative to the landscape area. Example: Edge Density Conifer (Class Level) ED = TE / TLA
ED = 10858.88 metres/184.11 hectares = 58.98 metres/hectare Example: Edge Density of all Patches (Landscape Level) ED = 28607.27 metres/184.11 hectares = 155.38 metres/hectare
Mean Patch Edge (MPE)
Average amount of edge per patch.
Example: Mean Patch Edge Conifer (Class Level) MPE = TE / NumP
MPE = 10858.88 metres/4 patches = 2714.72 metres/patch Example: Mean Patch Edge all Patches (Landscape Level) MPE = TE / NumP
MPE = 28607.27 metres/14 patches = 2043.38 metres/patch
Contrasted Weighted Edge Density (CWED)
CWED is a measure of density of edge in a landscape (metres per hectare) with a user-specified contrast weight.
CWED is equal to 0 when there is no edge in the landscape, in other words the whole landscape and it's border are made up of a single patch. It's value increases as the amount of edge in the landscape increases and/or as the user increases the contrast weight.
Landscape Shape Index (LSI)
LSI is the total landscape boundary and all edge within the boundary divided by the square root of the total landscape area (square metres) and adjusted by a constant (circular standard for vector layers, square standard for rasters). The LSI will increase with increasing landscape shape irregularity or increasing amounts of edge within the landscape.
Double Log Fractal Dimension (DLFD)
DLFD is a measure of patch perimeter complexity. It nears 1 when patch shapes are 'simple', such as circles or squares and it approaches 2 as patch shape perimeter complexity increases. Mean Perimeter-Area Ratio (MPAR) Shape Complexity.
Example: Mean perimeter-area ratio Conifer (Class Level) MPAR = Sum of each patches perimeter/area ratio divided by number of patches.
MPAR = (132 m/ha + 112 m/ha + 201 m/ha + 84 m/ha)/4 patches MPAR = 182 metres/hectare
Example: Mean perimeter-area ratio all patches (Landscape Level) MPAR = (200 m/ha + 132 m/ha + ... + 175 m/ha)/14 patches MPAR = 185 metres/hectare
Mean Shape Index (MSI) Shape Complexity.
MSI is equal to 1 when all patches are circular (for polygons) or square (for rasters (grids)) and it increases with increasing patch shape irregularity.
MSI = sum of each patch's perimeter divided by the square root of patch area (in hectares) for each class (when analyzing by class) or all patches (when analyzing by landscape), and adjusted for circular standard ( for polygons), or square standard (for rasters (grids)), divided by the number of patches.
Area Weighted Mean Shape Index (AWMSI)
AWMSI is equal to 1 when all patches are circular (for polygons) or square (for rasters (grids)) and it increases with increasing patch shape irregularity.
AWMSI equals the sum of each patch's perimeter, divided by the square root of patch area (in hectares) for each class (when analyzing by class) or for all patches (when analyzing by
landscape), and adjusted for circular standard ( for polygons), or square standard (for rasters (grids)), divided by the number of patches. It differs from the MSI in that it's weighted by patch area so larger patches will weigh more than smaller ones.
Mean Patch Fractal Dimension (MPFD) Shape Complexity.
Mean patch fractal dimension (MPFD) is another measure of shape complexity. Mean fractal dimension approaches one for shapes with simple perimeters and approaches two when shapes are more complex.
Area Weighted Mean Patch Fractal Dimension (AWMPFD) Shape Complexity adjusted for shape size.
Area weighted mean patch fractal dimension is the same as mean patch fractal dimension with the addition of individual patch area weighting applied to each patch. Because larger patches tend to be more complex than smaller patches, this has the effect of
determining patch complexity independent of its size. The unit of measure is the same as mean patch fractal dimension.
Mean Nearest Neighbor (MNN) Measure of patch isolation.
The nearest neighbor distance of an individual patch is the shortest distance to a similar patch (edge to edge). The mean nearest neighbor distance is the average of these distances (metres) for individual classes at the class level and the mean of the class nearest neighbor distances at the landscape level.
Interspersion Juxtaposition Index (IJI) Measure of patch adacency.
Approaches zero when the distribution of unique patch adjacencies becomes uneven and 100 when all patch types are equally adjacent. Interspersion requires that the landscape be made up of a minimum of three classes. At the class level interspersion is a measure of relative interspersion of each class. At the landscape level it is a measure of the interspersion of the each patch in the landscape.
Mean Proximity Index (MPI)
Measure of the degree of isolation and fragmentation.
Mean proximity index is a measure of the degree of isolation and fragmentation of a patch. MPI uses the nearest neighbor statistic. The distance threshold default is 1,000,000. If MPI is required at specific distances, select Set MPI Threshold from the main Patch pull-down menu and enter a threshold distance.
Both MNN and MPI use the nearest neighbor statistic of similar polygons in their algorithm. Occasionally a blank or zero will be reported in MNN and MPI fields. This happens when one polygon vertex touches another polygons border but the two similar polygons do not share a common border. When this happens a manual edit (move) of the touching vertex will correct the problem in the layer (theme). This problem will not happen when analyzing raster (grid) layers (themes).