DAT 223 Project Three Status Report
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School
Southern New Hampshire University *
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Course
223
Subject
Geography
Date
Dec 6, 2023
Type
docx
Pages
8
Uploaded by DrTree1894
Project Status Report
Name:
Amelia Madsen
Date: 02/26/2023
Status Report
1
Status
Progress
Supporting
Documentation
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 8, which will make it much
easier 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
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Status
Progress
Preliminary Data
First, I identified the data values that were needed to answer our
research questions.
Then I removed the values that did not answer our 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.
Then I 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.
Then to make it easier to import to mySQL and still maintain order,
I created a primary key that I called “Data Point#”. This had to be
done because all the other values have duplicate values and would
not work as a primary key.
Then I deleted the first row which denoted the column headers.
Then I created a matching table in SQL where all columns were set
as integer values.
Then I imported the CSV to SQL and saved it. The result is shown
below.
Data Analysis
Requirements
The available data does not fully meet our data requirements. This
data does answer some questions that the client has namely similarity of soil
types, and proximity to water and roadways. That will be helpful supporting
documentation for the overall research project, but it is still missing
important information needed to answer our research questions.
Next Steps and
Rationale
We still need more data on the actual beetles themselves because
ultimately that is the problem we are trying to solve. While the data we have
is helpful it lacks any information about the beetles that we are trying to deal
with. This won’t answer our research questions about where the highest
beetle populations are, what the numbers should look like or what is the most
effective method for reducing their numbers. Further research will need to be
done to collect this missing information. Without data on the beetles, we
can’t decide which areas of the forest to focus or how to go about eliminating
the beetles.
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Preliminary Data
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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. Data_Point#
2. Horizontal_Distance_To_Hydrology: Horizontal distance to nearest surface
water features
3. Vertical_Distance_To_Hydrology: Vertical distance to nearest surface water
features
4. Horizontal_Distance_To_Roadways: Horizontal distance to nearest roadway
5. Horizontal_Distance_To_Fire_Points: Horizontal distance to nearest wildfire
ignition points
6. Wilderness_Area (see below key)
7. Soil_Type (see below key)
8. 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
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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
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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
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
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Reference Kaggle. November 3, 2016. Forest cover type dataset. Retrieved from
https://www.kaggle.com/uciml/forest-cover-type-dataset
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