DAT 223 Project Three Milestone revised
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Dec 6, 2023
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Western Forest Service Client Plans for Revised Codebook
Analyst’s Name:
Amelia Madsen
Date:
02/15/2023
Research Questions:
What are the current estimated numbers of the beetle population?
What would be an appropriate/realistic level for the beetle population?
Where are the highest numbers of beetles?
What methods have been the most effective for culling beetle species in other forests?
Revised Forest Cover Type Dataset Codebook
This dataset contains tree observations from four areas of the Roosevelt National Forest
in Colorado. All observations are cartographic variables (no remote sensing) from 30-meter by
30-meter sections of forest. There are over half a million measurements total.
Content:
This dataset includes information on tree type, distance to nearby landmarks (roads), soil type,
and local topography.
The file contains cartographic variables of 581,012 measurements.
Column Description
s:
1. Horizontal_Distance_To_Hydrology: Horizontal distance to nearest surface
water features
2. Vertical_Distance_To_Hydrology: Vertical distance to nearest surface water
features
3. Horizontal_Distance_To_Roadways: Horizontal distance to nearest roadway
4. Horizontal_Distance_To_Fire_Points: Horizontal distance to nearest wildfire
ignition points
5. Wilderness_Area (see below key)
6. Soil_Type (see below key)
7. Cover_Type (see below key)
Keys:
Wilderness area designation. Integer value between 1 and 4 with the following key:
1. Rawah Wilderness Area
2. Neota Wilderness Area
3. Comanche Peak Wilderness Area
4. Cache la Poudre Wilderness
Soil Type designation. Integer value between 1 and 40 with the following key:
1. Cathedral family - Rock outcrop complex, extremely stony
2. Vanet - Ratake families complex, very stony
3. Haploborolis - Rock outcrop complex, rubbly
4. Ratake family - Rock outcrop complex, rubbly
5. Vanet family - Rock outcrop complex, rubbly
6. Vanet - Wetmore families - Rock outcrop complex, stony
7. Gothic family
8. Supervisor - Limber families complex
9. Troutville family, very stony
10. Bullwark - Catamount families - Rock outcrop complex, rubbly
11. Bullwark - Catamount families - Rock land complex, rubbly. 12 Legault
family - Rock land complex, stony
12. Unknown
13. Catamount family - Rock land - Bullwark family complex, rubbly
14. Pachic Argiborolis - Aquolis complex
15. Unspecified in the USFS Soil and ELU Survey
16. Cryaquolis - Cryoborolis complex
17. Gateview family - Cryaquolis complex
18. Rogert family, very stony
19. Typic Cryaquolis - Borohemists complex
20. Typic Cryaquepts - Typic Cryaquolls complex
21. Typic Cryaquolls - Leighcan family, till substratum complex
22. Leighcan family, till substratum, extremely bouldery
23. Leighcan family, till substratum - Typic Cryaquolls complex Page 2 of 3 24.
Leighcan family, extremely stony
25. Leighcan family, warm, extremely stony
26. Granile - Catamount families complex, very stony
27. Leighcan family, warm - Rock outcrop complex, extremely stony
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28. Leighcan family - Rock outcrop complex, extremely stony
29. Como - Legault families complex, extremely stony
30. Como family - Rock land - Legault family complex, extremely stony
31. Leighcan - Catamount families complex, extremely stony
32. Catamount family - Rock outcrop - Leighcan family complex, extremely
stony
33. Leighcan - Catamount families - Rock outcrop complex, extremely stony
34. Cryorthents - Rock land complex, extremely stony
35. Cryumbrepts - Rock outcrop - Cryaquepts complex
36. Bross family - Rock land - Cryumbrepts complex, extremely stony
37. Rock outcrop - Cryumbrepts - Cryorthents complex, extremely stony
38. Leighcan - Moran families - Cryaquolls complex, extremely stony
39. Moran family - Cryorthents - Leighcan family complex, extremely stony
40. Moran family - Cryorthents - Rock land complex, extremely stony
Forest Cover Type designation. Integer value between 1 and 7, with the following key:
1. Spruce/Fir
2. Lodgepole Pine
3. Ponderosa Pine
4. Cottonwood/Willow
5. Aspen
6. Douglas-fir
7. Krummholz
Reference Kaggle. November 3, 2016. Forest cover type dataset.
Retrieved from
https://www.kaggle.com/uciml/forest-cover-type-dataset
Changes:
Removed values that did not answer research or client questions:
o
Aspect
o
Slope
o
Hill shade
These values are unnecessary for our research and removing these columns
will allow for easier reading of the data.
Changed soil type and wilderness area designation from dummy values with
multiple columns to single columns with integer values of 1-40 and 1-4
respectively.
There are 4 main pieces that the Forest Service wants to focus on. First, they want to
know which are the areas of highest priority. To address the areas of highest priority we need to
have a way of breaking down the forest into sections so we can identify which sections to focus
our efforts on. Since the original codebook breaks the forest down into 4 different sections that
part of the codebook is important to keep.
Secondly, they want to know if these areas have similar soil types. That is why we need
to keep the section of the codebook on soil types. However, I found that the system of indicating
soil types was cumbersome the way that it was. It would have 40 different columns each with
values of 0 or 1. More columns will make the data more difficult to read. So, we change this to a
single column with values of 1-40 to indicate the soil types of the area. Multiple soil types can be
indicated and separated by a comma. I have done the same with the wilderness area designation
and together this takes the total number of columns from 54 to 7, which will make it much easy
to read.
The last two questions the client has deal with proximity to water and roadways. The
values that indicate distance are horizontal distance to hydrology, vertical distance to hydrology,
and horizontal distance to roadways. These values have been kept as is to aid in answering our
clients’ questions.
There are two categories that do not directly relate to our client’s questions or our
research questions but are nevertheless important.
In the client file the Forest Service mentions
a concern about trees downed trees being a fire hazard. That is why horizontal distance to fire
points is essential. Areas that are close to fire points are going to be areas of high priority
because a high population of beetles in that area could exacerbate the chance of a catastrophic
fire event. Lastly is cover types. The beetles specifically prefer to burrow in spruce trees. So if an
area has mainly spruce trees that area will be a higher priority while areas that do not have spruce
trees will not be a priority. Which is why the last thing I would do to edit our overall data is to
take out any rows of data that focus on areas that do not contain spruce trees, since an area
without spruce trees will not be at risk of beetle infestation. This should reduce the number of
areas that we need to deal with.