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Lewis and Clark Campus Land Use and Cover Change Analysis: 1936 to 2001

Lewis and Clark Campus Land Use and Cover Change Analysis: 1936 to 2001. Miriam Coe ENVS 330 April 1, 2012. Lewis and Clark: 2001. Key Green: Forest Yellow: Grass Red: Impervious Surfaces. GPS Points: 2001 Map. Statistics: 2001. Lewis and Clark: 1936. Key Green: Forest

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Lewis and Clark Campus Land Use and Cover Change Analysis: 1936 to 2001

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  1. Lewis and Clark Campus Land Use and Cover Change Analysis: 1936 to 2001 Miriam Coe ENVS 330 April 1, 2012

  2. Lewis and Clark: 2001 Key Green: Forest Yellow: Grass Red: Impervious Surfaces

  3. GPS Points: 2001 Map

  4. Statistics: 2001

  5. Lewis and Clark: 1936 Key Green: Forest Yellow: Grass Red: Impervious Surfaces

  6. GPS Points: 1936 Map

  7. Statistics: 1936

  8. Discussion • The Lewis & Clark campus is surrounded by forested area on nearly three sides. Indeed, much of the land owned by Lewis & Clark itself is still undeveloped, forested land. To the southwest side of the campus, Tryon Creek State Natural Area resides, a forest ecosystem that contains Tryon Creek, where much of the runoff of the surrounding watershed is condensed. As the area around this creek has become increasingly covered by industrial and residential land, the percentage of impermeable surface has increased. This causes water to flow more directly into the creek, rather than soaking down through the soil, which results in flashy runoff, and a higher concentration of pollutants that get swept across roofs, roads, parking lots, and sidewalks.Lewis & Clark College is not exempt from this increase in impermeable surfaces. The biggest event that influenced this change was the sale of the land as the Frank estate to Albany College, which eventually became Lewis & Clark College. L&C has been expanding and developing the land for over a half century, increasing impermeable surfaces, while decreasing forest and lawn. In my analysis of cover change on the L&C campus, I compared cover in 1936 to 2001. I looked at three types of cover: forest, grass, and impervious surfaces. In 1936, 74% of the land cover was forested, while 22% was grass cover, and only 4% of total cover was comprised of an impervious surface. By 2001, these proportions of cover had changed drastically, with only 41% devoted to forest, 13% grass, and 44% impervious surfaces. This change shows that Lewis and Clark has been expanding its facilities and population. There is now room for a wider variety of activities (for example, there is now a football field), as well as a greater number of people (an increase in living spaces).

  9. Errors • This analysis only included visible cover as seen in air photos. It did not account for visibility difficulties, GIS operational assumptions, or overlap in cover. Visibility: The 1936 air photo is in black and white, and in many places it is hard to determine whether a surface is made up of mainly grass, pavement, or bare soil. This not only means that cover percentages may be skewed, but also that the 2001 analysis is probably much more accurate. Assumptions: The GIS program only allows for a certain amount of accuracy when creating polygons. These polygons may not follow the exact lines of cover change, or include small details in cover, such as thin pathways. In addition, time was somewhat limited, and my personal execution of the polygons may not have been as accurate as it could have been.Cover overlap: From the aerial photos, we can only see the tops of trees, and the areas where bare ground is completely exposed. There may be many spaces on the campus that are covered in impervious surfaces, but are hidden from view in an aerial photo due to tree cover. It would be interesting to do this analysis again, taking into consideration the overlap in layers of grass, impervious surfaces, and forest.

  10. Bias • This project has been completed many times before, and I already knew the general outcome before starting. While I don’t think this affected the separation of surfaces, it may have limited my creativity in making decisions. For example, I stuck to the most common forms of cover analyzed in this project (grass, forest, impervious), and created a key that colored impervious surfaces red, creating the assumption that impervious surfaces are bad while forest is good. While these kinds of operational decisions may only be changed by conscious decisions to avoid them, starting an analysis without having seen someone else’s would probably help to reduce the bias.

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