1. Fragstats and Landscape Metrics
Bill Dijak
Wildlife Biologist/GIS Specialist USDA Forest Service
Room 309

2. Map Projection UTM, Universal Transverse Mercator.
Datum, NAD1927, NAD1983, WGS1984.
Missouri use NAD1983, Zone 15, Unit meters.

3. Two forms of GIS data
Vector data, points lines and polygons usually stored as a shapefile (.shp).
Raster data stored as square raster cells or pixels.
Each raster cell has a numerical value representing a landscape characteristic and resolution which is the length of the side of the raster cell.
ESRI rasters are often referred to as grids.

4. Examples of Raster Data
Gap landcover (MORAP)
Landsat satellite imagery
Digital elevation models (DEM)
Digital raster graphics (DRG)
Landform

10. Fragstats 3.3
FragSetup33.zip

12. Fragstats 3.3
Click Fragstats and select Set Run Parameters.

15. 1 4 2 3

16. 1 4 2 3

17. 1,forest,t,f 2,grassland,t,f 3,cropland,t,f 4,glade,t,f 5,water,t,f
Class Properties File
Class ID, Class Name, Status, Is Background
1,forest,t,f
2,grassland,t,f
3,cropland,t,f
4,glade,t,f
5,water,t,f
6,urban,f,t
7,wetland,f,t

18. Patch Metrics
Provide metric information for each and every patch found in the landscape
Generate an Enormous amount of information.
Are useful for generating information for specific locations on the landscape such as nest locations or point count locations.
Example: An area-sensitive species selects patches of forest of some minimum size.

20. Fragstats: Select Patch Metrics

25. Weighting tables can be created in Excel
FTABLE 1 2 3 4
0.8
0.4
0.6
0.1
0.2
0.5
0.3
But must be saved as CSV files
FTABLE,1,2,3,4
1,1,0.8,0,0.4
2,0,1,0.6,0.4
3,0.1,0.2,1,0.5
4,0.3,0.4,0.5,1
Rows represent the focal class, columns
the “with” class

26. Fragstats: Select Class metrics

29. Fragstats: Select Landscape Metrics

32. File: Save as
Saves all your parameter settings to one file _______.frg
Can be opened and reused using
File: Open

33. Fragstats: Execute
Executes program using the
parameter files and generates
comma delimited files
.patch
.class
.land
These files can be imported into excel.

35. LID
PID
TYPE
AREA
AREA_CSD
AREA_CPS
AREA_LSD
AREA_LPS
PERIM
PERIM_CSD
C:\aaaa\elt7 74
forest
0.09
120
161
1.44
1.6949
10.559
540
156
1.89
3.3898
720 56
2.25
-0.738
5.0847
1440
160
2.97
6.7797
900
-0.796
151
3.06
8.4746
1020 95
3.33
960 29
3.6
-0.682
1320
157
1080
152
4.05
1140
162
4.14
1380 33
4.41
1620
148
4.5
20.339
1560 67
4.59
-0.641
-0.449
1740
158
1200 23
5.49 14
5.94
-0.585 21
6.12 99
6.21 87
6.3
2760 75
6.39
1680
109
1500 31
7.02
2160 86 35
7.56
40.678

36. LID
TYPE
PLAND PD TE ED
AREA_MN
SHAPE_MN
FRAC_MN
PARA_MN
CIRCLE_MN
C:\aaaa\elt7
water
4.159
0.368
34860
2.5208
1.1549
0.8468
forest
1.8398
179580
1.895
1.1031
0.7161
grassland
1.4105
176940
24.887
1.9335
1.0993
0.6778
cropland
1.2572
122760
1.9249
1.1007
0.6569
glade
0.367
0.092
5700
1.7478
3.99
2.3137
1.1529
0.703

37. HELP!

39. So, what metrics do I need?
It depends on what landscape charateristics you believe are impacting your species of intererst.
Most landscape scale wildlife studies are concerned with the amount and spatial characteristics of habitat.
Amount is is determined using pland in the class parameter settings

40. Nest predation example
Patch area (Area)
Patch shape (Shape)
Patch core area index% (CAI)
Class edge density (ED)
Class habitat percentage (Pland)
Class aggregation Index (AI)

41. Area Sensitive Interior Species
Patch area (Area)
Patch area standard deviation (Area_CSD)
Class habitat percentage (Pland)
Class mean patch area (Area_MN)
Class patch area variation (Area_SD)
Class total core area (TCA)
Class core area percent of landscape (CPLAND)

42. Population Viability (Extinction and Recolinization)
Class habitat percentage (PLAND)
Class number of patches (NP)
Class largest patch index (LPI)
Class mean euclidean nearest neighbor distance (ENN_MN)
Class variation in euclidean nearest neighbor distance (ENN_SD)
Class Connectance Index (CONNECT)

43. Questions
Do not send to my missouri.edu unless you want to wait a few days for a response.