Q1 : What does the DEM layer show? What is the cell size and how do you know? Why is the cell size important?
The DEM provides elevation values over a topographic surface. The cell size in ~32.8×32.8, it states so in the layer properties. Cell size is important because it gives you a sense of how much detail and landscape differentiation is going to be recognizable in the DEM. The larger the cell size, the lesser the detail. The smaller the cell size the greater the detail, but also the larger the file size and processing time.
Q2 : Why reclassify water in this way? How will the value of the water affect the resulting cost surface?
We are assuming that water is unlikely to be traversed by the mushroom hunter and therefore we give all water a uniform, high value (100) representing high cost. The value of water bodies will dramatically increase the cost associated with traversing any water-covered area.
Q3 : What other data could be used to generate a cost surface? Do you think our slope/water cost surface is the most realistic representation of how difficult it is to travel from one grid cell to another? Why or why not?
A more detailed cost surface would also include vegetation density, which can greatly affect the speed and effort of travel, as well as visibility. I think slope definitely is a good measure of travel difficulty, but water can be a bit misleading, because it is more likely that a person will cross a shallow stream than ascend a steep slope, and yet we assign all water a high cost. I think a slope/vegetation density cost surface would more accurately represent travel difficulty, and while water also is a strong indicator, it would be better if we could filter out shallow streams and rivers that may be easily crossed.
Q4 : What does the attribute table of the Observer Points raster tell you? How would you determine which cells can be seen from which lookout?
The attribute table tells me the amount of cells that can be seen from Lookout 1, the amount of cells that can be seen from Lookout 2, the amount of cells that can be seen from both, and the amount of cells that can be seen from neither of the lookouts. The lookout shapefile attribute table numbers the lookouts 1 and 2, and the observer points attribute table has columns titled obs1 and obs2 which reflect the observation range possible from the respective lookouts.
Q5 : Based on the results of your observation points analysis and the least cost path you generated, which lookout would you recommend the Forest Service use to the mushroom hunter? Why?
I would pick lookout # 1 (the easternmost lookout) because it offers a much larger area of observation (2,699,816 cells, versus 504,912 cells for lookout 2), and because its areas of observation includes areas closer to the least cost route.
Q6 : With reference to each map, explain which areas you would prioritize in searching for the mushroom hunter. Make sure to also explain the steps you took to conduct your analysis, including any limitations or caveats of the techniques you used.
I would first prioritize along the least cost path (see Figure 2). If unsuccessful, I would follow some lesser cost routes that don’t necessarily lead to Nash Lake, but that make for easier walking. At one point the East-West canyon that comprises the beginning of the least-cost path curves Southward toward lookout 1 (see Figures 1 and 3), so the mushroom hunter may have just followed the canyon South. I would prioritize lookout 1 for viewsheds (see Figure 3), given that it allows for visibility surrounding the end of the least cost path approaching Nash Lake, and also given that its viewsheds cover a lot more ground than lookout 2.
The main limitation of the techniques used is that our analysis lacks vegetation data which limits the accuracy of our least cost path. It is also difficult to predict human behavior in such a situation, limiting our ability to make anticipate the mushroom hunter’s decisions when lost.
