In Part III, we will use two Spatial Analyst tools to bring together the raster layers we created in Part I (habitat quality) and Part II (forest patches). Zonal Geometry calculates several geometry measures, such as area and thickness, for zones in a raster. We will use it to generate a table of statistics about the size and shape of each forest patch. We will also use the Zonal Histogram Tool to tabulate the number of cells of each habitat type within each forest patch and management unit.
Make sure you have the correct answer before moving on to the next step.
The "PatchGeometry" table should have the following information. If your data does not match this, go back and redo the previous step.
OID | Value | Area | Perimeter | Thickness | Xcentroid | ycentroid | Majoraxis | minoraxis | orientation |
---|---|---|---|---|---|---|---|---|---|
0 | 1 | 642010000 | 350600 | 6343.9 | 1688100 | 359206 | 24878.6 | 8214.21 | 81.9311 |
1 | 2 | 580000 | 3800 | 212.1 | 1696040 | 379519 | 631.205 | 292.488 | 84.2196 |
2 | 3 | 1228670000 | 907000 | 6250.3 | 1756350 | 335775 | 36173.2 | 10811.8 | 134.675 |
3 | 4 | 190000 | 2400 | 150 | 1698610 | 378516 | 270.871 | 223.275 | 140.531 |
4 | 5 | 300000 | 2800 | 170.7 | 1699130 | 378353 | 401.382 | 237.911 | 110.363 |
5 | 6 | 10000 | 400 | 50 | 1699560 | 378016 | 56.419 | 56.419 | 90 |
6 | 7 | 130000 | 1600 | 150 | 1700800 | 377131 | 219.193 | 188.785 | 166.224 |
7 | 8 | 10000 | 400 | 50 | 1698360 | 377216 | 56.419 | 56.419 | 90 |
Which field in the "PatchGeometry" table is the equivalent to the "ForestID" field? What are the units of the fields "AREA," "PERIMETER," and "THICKNESS"? What do the values in the fields "XCENTROID," "YCENTROID," "MAJORAXIS," "MINORAXIS", and "ORIENTATION" mean?
The Zonal Histogram tool will create a summary table that contains one row for each unique value in the "Value raster" and one column for each unique value in the "Zone dataset." The tool will calculate the total number of cells for each combination of a unique row and column. The tool can also create a graph based on the output table, which we are going to skip.
Make sure you have the correct answer before moving on to the next step.
The "Habitat_by_Patch" table should have the following information. If your data does not match this, go back and redo the previous step.
oid | Label | Value_2 | Value_3 | FORESTID | EDge_sqm | int_sqM | PCTtotedge | pcttotint |
---|---|---|---|---|---|---|---|---|
0 | 1 | 22207 | 41994 | 1 | 222070000 | 419940000 | 35 | 65 |
1 | 2 | 58 | 0 | 2 | 580000 | 0 | 100 | 0 |
2 | 3 | 74095 | 48772 | 3 | 740950000 | 487720000 | 60 | 40 |
3 | 4 | 19 | 0 | 4 | 190000 | 0 | 100 | 0 |
4 | 5 | 30 | 0 | 5 | 300000 | 0 | 100 | 0 |
What do numbers in the "LABEL" field of the "Habitat_by_MU" mean? Which management unit "use" has the most roads?
Make sure you have the correct answer before moving on to the next step.
The "Habitat_by_MU" table should have the following values. If your data does not match this, go back and redo the previous step.
OID | Label | logging | coservation | habitat | logSqm | conssqm | pcttotlog | pcttotcons |
---|---|---|---|---|---|---|---|---|
0 | 1 | 35322 | 1428 | Low Quality Habitat | 353220000 | 14280000 | 96 | 4 |
1 | 2 | 635978 | 44954 | Medium Quality Habitat | 6359780000 | 449540000 | 93 | 7 |
2 | 3 | 302425 | 167611 | High Quality Habitat | 3024250000 | 1676110000 | 64 | 36 |
Make sure you have the correct answer before moving on to the next step.
The "forestpatchpoly" shapefile should have the following information. If your data does not match this, go back and redo the previous step. Note that this table has been sorted based on "gridcode".
Fid | Shape* | Id | gridcode | ForestID |
---|---|---|---|---|
36 | Polygon | 37 | 1 | 1 |
0 | Polygon | 1 | 2 | 2 |
61 | Polygon | 62 | 3 | 3 |
1 | Polygon | 2 | 4 | 4 |
2 | Polygon | 3 | 5 | 5 |
Why is there such a large range of values for the edge to area ratio results?
How would the results of the analysis change if we used a larger or smaller cell size?
Make sure you have the correct answer before moving on to the next step.
The "Final_Forest_Patches" attribute table should have the following information. If your data does not match this, go back and redo the previous step.
FID | Shape* | Forest ID | Totareasqm | perimeterm | thichnessm | edge_sqm | int_sqm | pcttotedge | pcttotint | edgetoarea |
---|---|---|---|---|---|---|---|---|---|---|
36 | Polygon | 1 | 642010000 | 350600 | 6343.9 | 222070000 | 419940000 | 35 | 65 | 0.05461 |
0 | Polygon | 2 | 580000 | 3800 | 212.1 | 580000 | 0 | 100 | 0 | 0.655172 |
61 | Polygon | 3 | 1228670000 | 90700 | 6250.3 | 740950000 | 487720000 | 60 | 40 | 0.07382 |
1 | Polygon | 4 | 190000 | 2400 | 150 | 190000 | 0 | 100 | 0 | 1.26316 |
2 | Polygon | 5 | 300000 | 2800 | 170.7 | 300000 | 0 | 100 | 0 | 0.933333 |
3 | Polygon | 6 | 10000 | 400 | 50 | 10000 | 0 | 100 | 0 | 4 |
5 | Polygon | 7 | 130000 | 1600 | 150 | 130000 | 0 | 100 | 0 | 1.23077 |
Notice how the default outputs from many of the Spatial Analyst tools are not very easy to understand. It’s worth the time to create more intuitive fields, units, and names while you are doing the analysis. That way you can easily interpret your results later on and share them with others in a meaningful format.