Program in GIS

Final Candidate Sites for Priority Conservation Areas in Centre County

Figure 1: Suitable Sites for Vineyards.

Source:  Brenton White ArcMap Project 8, 9, & 10 screen capture.

Figure 1 shows the priority conservation areas (approximately 26 square miles) that takes into account the need to be located with specific road, species, habitat, ownership, land use, and slope characteristics.  The 26 square miles was computed as follows:

Each cell is 27 meters by 27 meters and equals 729 square meters per cell
92,871 cells multiplied by 729 square meters per cell equals 67,702,959 square meters
67,702,959 square meters by 10.7639 equal 728,747,880 square feet
27,878,400 square feet equals 1 square mile
So, 728,747,880 square feet divided by 27,878,400 square feet equals 26.140 square miles

Close Up of Some Candidate Sites

Figure 2: Suitable site showing whether site is on public or private land.

Source:  Brenton White ArcMap Project 8, 9, & 10 screen capture.

Figure 2 shows a close up of some of the candidate sites with a locator map that show the close up area in relation to the entire county.

Creating this map required:

• Organizing the project data and working environment

• Specifying Spatial Analyst options

• Buffering roads

• Determining study sites with <10% area in buffered roads

• Determining study sites with >75 bird and mammal species combined

• Using spatial analyst to identify locations with <15% slope

• Using spatial analyst to generate a hillshade from an elevation grid

• Converting all necessary layers to raster and reclassify to get binary cell values

• Performing criteria-based analysis by combining multiple grid themes

  • Sites with less than 10% area in buffered roads

  • Study sites with >75 bird and mammal species combined

  • High habitat potential

  • Publicly owned land

  • Forested areas

  • Slope less than 15%

• Turn everything into a pretty report

Methods Used in the Analysis

The key methods used in this analysis were dissolving, buffering, intersecting, adding fields and populating them (both manually and with code), joining, converting to raster, reclassifying, and raster math.  The most complex combination of these methods was using them to determine which study sites had <10% area in buffered roads.

Note:  It occurred to me after doing the analysis, that I should (could?) have started by selecting the study sites with greater than 75 bird and mammal species combined.  This would have simplified the step of analyzing those sites that had less than 10% roads, since we have many fewer sites to consider.  Ah...live and learn!

I began by organizing the project data and working environment.  I then set the Spatial Analyst options.  Of particular importance was the cell size for raster operations.  The choice fell as either 50 meters or 27 meters based on the sizes of the land use and elevation layers.  I chose 27 as I did not want to miss an slope areas.  Any less than 27 and effort would be wasted.  Any more than 50 and we'd lose some data.

My general workflow was to create raster layers for each of the criteria (as above) so that I could do raster math on the necessary layers to determine the priority conservation areas.  The generation of the layer with Study Sites meeting the <10% roads criteria proved the most challenging.  Generating the other layers was quite simple and will be addressed below briefly.  So, let's talk about what it took to get the Study Sites road criteria analyzed.

I began with the clip_rds and studysites vector layers.  First, I dissolved the clip_rds layer into the three road types.  I then added a BuffSize field to the clip_rds layer.  I manually entered the BuffSize parameters of 20, 50, and 100 meters to roads, highways, and interstates, respectively.  Since I have a fairly powerful computer, I went ahead and dissolved the buffer.

With the buffered roads layer in place, I performed an Intersection of it and the study sites layer.  This, I expected would give me the buffered roads identified by block_ID.  I had 155 records in the study sites layer, and ended up with 258.  I had expected to get an  intersected polygon (e.g., roads polygon) for each block ID in the study sites layer.  So, I tried to dissolve the polygons based on block ID.  This, however, created some strange groupings, so I abandoned this process.  Instead, I went in manually and removed incorrectly identified records.  After cleaning up the incorrect records, I was able to dissolve the layer on block_ID and come up with the correct number of records and could then add an AreaRds field and populate it by calculating the fields with the code from Lesson 2.  I then joined this layer to studysites, added a percent roads field and populated it.  I then selected records with <10% roads and created my study sites layer that met this criteria.

Note:  I don't know why the INTERSECT did not return the same number of records as in the StudySite layer (except where features did not overlap in a studysite), but I did hope that a dissolve would group them appropriately.  I also tried UNION and then to select only those features which were "Road," "Highway," and "Interstate."  I save this selection as a layer and then dissolved on block_ID.  This process, however, also generated selections that extended beyond a given block_ID.  Finally, I tried to CLIP studysites with buffered roads and got the same result.  Some areas where clipped properly, while others extended over multiple study sites.   I am using ArcMap 9.0 and don't know if there is a problem, but I could manually fix the data, in each case, to generate the right selections.  I guess you'll have to tell me what method/step I missed here.

To get the species criteria, I just joined the species richness table to the studysites with <10% roads (since they both had block_ID).  I added a field for TotSpecies, populated it, and then selected those records with TotSpecies >75.  This became my StudySites with >75 species layer.

I performed a slope and hillshade operation on the elevation layer to generate the slope and hillshade layers, respectively.

The remaining layers were converted to raster and reclassified to give me a 1 for cells that met the criteria.  I also converted the studysites <10% roads and >75 species to raster and reclassified them.

Finally, I performed the raster mathematics, multiplying the layers to get the final Priority Conservation Areas.

Steps Along the Way

Buffer Roads

Figure 3a: Close up of the buffered roads.

Source:  Brenton White ArcMap Project 8, 9, & 10 screen capture.

Figure 3a shows the buffered area around the roads buffered as follows:  Interstates—100 meters, Highways—50 meters, and Roads—20 meters.

Select Study Sites With <10% Area in Buffered Roads

Figure 3b: Candidate study sites based on road criteria.

Source:  Brenton White ArcMap Project 8, 9, & 10 screen capture.

Figure 3b shows the resulting Study Sites (in tan) selected that had <10% area covered in buffered roads.

Select Study Sites With >75 Bird and Mammal Species

Figure 4: Candidate sites based on number of species.

Source:  Brenton White ArcMap Project 8, 9, & 10 screen capture.

Figure 4 shows the Study Sites (in light blue) that had greater than 75 bird and mammal species combined AND met the criteria of the study site having <10% area covered with buffered roads.

Find Land With High Habitat Potential

Figure 5: Land with high habitat potential.

Source:  Brenton White ArcMap Project 8, 9, & 10 screen capture.

Figure 5 shows the land with high habitat potential (in light green).

Find Publicly Owned Land

Figure 6: Land that is publicly owned.

Source:  Brenton White ArcMap Project 8, 9, & 10 screen capture.

Figure 6 shows publicly owned land (in brown).

Find Forested Areas

Figure 7: Forested land.

Source:  Brenton White ArcMap Project 8, 9, & 10 screen capture.

Figure 7 shows land covered with forest (in green).

Find Land With <15% Slope

Figure 7: Criteria layers are "raster calculated" to determine suitable sites.

Source:  Brenton White ArcMap Project 8, 9, & 10 screen capture.

Figure 7 shows land with slope <15%

GEOG 5222: Project 8, 9, & 10: Identifying Priority Conservation Areas in Centre County.