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I ended up running this analysis on a university supercomputer, and it took 2 months to run for a subsample of my study area ( 500 km^2 subsample) with a rural road density. The road densities were higher in some areas because they followed legal section lines every 1-mile. We deemed the analysis unfeasible for our study. The best citation for the methods is Montgomery et al. 2012 (http://www.bioone.org/doi/abs/10.2981/11-123) Importance of visibility when evaluating animal response to roads, but they're a bit light on the analytical methods to try to replicate the GIS steps. Good luck! Jesse
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06-25-2018
02:36 PM
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I got access granted to a much more powerful computer that can be left to run for a few days. I am going to try this using the visibility tool with 30m DEM raster data and a roads shapefile broken into 100m line segments (i.e. the tool will examine vertices at 100m). If I do not update my progress within a few weeks, feel free to contact me.
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02-08-2017
12:27 PM
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Thank you both for your feedback. We will be considering habitat type, road surface type (as a proxy for traffic levels), development densities, ruggedness, slope, aspect, and a whole suite of predictor variables that have been shown to influence deer distributions in the literature. The idea to incorporate viewshed is from anecdotal observations of deer using miniature "wilderness" areas among heavily developed portions of the study area. These areas may be very close to roads, but on the opposite side of a ridge, so on the ground, they feel much more remote than areas at the same distance to roads without any topography to break the viewshed. There is a publication by Robert Montgomery et al. 2012. Importance of visibility when evaluating animal responses to roads. Wildlife Biology 18:393-405. I'm trying to replicate their methods, but without adding the height of forest cover, since I'm working in fairly open habitats.
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02-08-2017
09:09 AM
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And thank you very much for trying to help. If it clarifies my question at all, I'm looking at the influence of roads on deer movements. I hypothesize that deer will not be as affected by roads if the roads are out of sight. I have 600,000 (and counting) deer locations, so I was hoping to calculate the entire raster instead of calculating visibility for each deer location. This will also help to create predictive maps to highlight areas that are currently not visible from roads. Thanks again!
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02-07-2017
09:21 PM
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I am looking at a large area approximately 80x80 miles with an extensive road network (see attached, roads are clipped by a study area buffer). So I cannot use the observer option because of the 32 point limit on observers. I am currently running the Visibility tool with the DEM as the input raster, and roads as the input polyline. Analysis type: FREQUENCY, observer parameters-- Surface offset: 2, Outer radius: 1600. I thought the Surface offset would account for the 2m vehicle height. However, the tool has been running for 4+ hours, and I do not think it is working. With an outer radius of 1600, it seems like the calculation would just look at the center of each 30m pixel and calculate visibility from roads up to 1600m. However, I believe it is counting a density, which is taking too much resources. Is there any way to calculate I's/0/s so that after confirming a pixel is visible from a road, the calculation could move on?
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02-07-2017
09:17 PM
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I have a 30m DEM raster and a polyline shapefile for a road network. I would like to produce a 30m raster of I/0 values showing whether or not each cell is visible from a road up to 2000m. I'd like to use a height of 2m above the road to represent the height of a commercial vehicle. Is this possible with the viewshed tool? The examples I have found work best for smaller point shapefiles, like whether a tower is visible, and do not help for a large, polyline feature. Thank you for any ideas!
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02-07-2017
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