Difficulty resoursce

[dasom1348]

http://www.thetrailmaster.com/hike-smart/choosing-a-difficulty-level-for-your-hike-is-a-key-to-wise-hike-planning/

We are gonna refer to this resource in order to assign our difficulty

[dasom1348]

http://www.hikenewengland.com/LegendRating.php

Above link is trails resource from LA and this one is trails from New England. Overall standard for difficulty is higher than our data in Macleish. So, with these standards, our longest length and steepness trail is assigned as easy, which means all of our trails are easy course.

I am searching another resource for comparison to real world standard, but I think we need to assign ourselves within our data.. how do u guys think about this?

[eyk801]

I think that that sounds fine -- are you saying we have to make our own standards? I think that would be alright!

[dasom1348]

https://www.nps.gov/shen/planyourvisit/how-to-determine-hiking-difficulty.htm

more reliable resource

[jlin47]

https://www.nps.gov/shen/planyourvisit/how-to-determine-hiking-difficulty.htm Formula for calculating difficulty: Elevation Gain x 2 x distance (in miles). The product's square root is the numerical rating.

For example, a 10-mile hike that gains 2,200 feet in elevation: 2,200 x 2=4,400 4,400 x 10 = 44,000 Square root of 44,000=209.8

calculate difficulty for macleish: Vernal Pool Loop: 0.224016369x65.6167979x2=29.4, final: 5.4

entry trail: 0.12931039x62.335958005x2=16.1, final=4.0

Driveway: 0.107497216x0(?)x2=0.21, final= 0.46 (This trail has 0 elevation)

Easy Out: 0.0845361837x32.80839895x2=5.5, final= 2.4

[dasom1348]

Calculate difficulty for macleish: snowmobiles is 2278.4501002 -> 47.73311 Eastern Loop is 624.908528866 -> 24.99817 Western Loop is 759.941857931 -> 27.56704 Poplar Hill is 461.99785095 -> 21.49414 Pocupine is 279.553188392 -> 16.71984

[jlin47]

Code for joining trails 1 and new table with numeric rating:

trails_1<- trails %>% group_by(name) %>% summarize(num_segments = n(), total_length = sum(computed_length)) %>% arrange(desc(total_length))

name <- c('Snowmobile Trail','Eastern Loop','Easy Out', "entry trail","Poplar Hill Road","Porcupine Trail", "Vernal Pool Loop","Western Loop") numeric_rating <- c(47.73311, 24.99817, 2.4, 4.0, 21.49414,16.71984,5.4, 27.56704)

difficulty_rating <- data.frame(name, numeric_rating, stringsAsFactors=FALSE)%>% mutate (Difficulty= if_else(as.numeric(numeric_rating)<10, "Easy", ifelse(as.numeric(numeric_rating)<30, "Moderate", "Hard")))

trails_2 <-trails_1 %>% inner_join(difficulty_rating, by = "name")

[dasom1348]

All of the macleish trails are easy based on the hiking difficulty standard from the National Park Service, so among the trails in macleish, we compare their difficulty in relation to one another based on length and elevation in our data.

[jlin47]

factpal <- colorFactor(topo.colors(3), palette = c('red', 'orange', 'green'),trails_2$Difficulty)

require(leaflet)

leaflet()%>% addTiles()%>% addPolylines(data=trails_2, weight = 5, fillOpacity = 0.5, popup = ~ name, group = "Structures", color = ~factpal(Difficulty))%>% addMarkers(data = macleish_layers[["landmarks"]], popup = ~ Label, group = "Structures")%>% addPolylines(data = contours, weight = 1, fillOpacity = 0.1, color = ~pal(ELEV_M))