I am trying to figure our the proportion of an area that has a slope of 0, +/- 5 degrees. Another way of saying it is anything above 5 degrees and below 5 degrees are bad. I am trying to find the actual number, and a graphic.
To achieve this I turned to R and using the Raster package. Let's use a generic country, in this case, the Philippines
{list.of.packages <- c("sp","raster","rasterVis","maptools","rgeos")
new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,"Package"])]
if(length(new.packages)) install.packages(new.packages)}
library(sp) # classes for spatial data
library(raster) # grids, rasters
library(rasterVis) # raster visualisation
library(maptools)
library(rgeos)
Now let's get the altitude information and plot the slopes.
elevation <- getData("alt", country = "PHL")
x <- terrain(elevation, opt = c("slope", "aspect"), unit = "degrees")
plot(x$slope)
Not very helpful due to the scale, so let's simply look at the Island of Palawan
e <- drawExtent(show=TRUE) #to crop out Palawan (it's the long skinny island that is roughly midway on the left and is oriented between 2 and 8 O'clock)
gewataSub <- crop(x,e)
plot(gewataSub, 1)## Now visualize the new cropped object
A little bit better to visualize. I get a sense of the magnitude of the slopes and that with a 5 degree restriction, I am mostly confined to the coast. But I need a little bit more for analysis.
I would like Results to be something to be in two parts: 1. " 35 % (made up) of the selected area has a slope exceeding +/- 5 degrees" or " 65 % of the selected area is within +/- 5 degrees". (with the code to get it) 2. A picture where everything within +/- 5 degrees is one color, call it good or green, and everything else is in another color, call it bad or red.
Thanks
You can use reclassify
from the raster
package to achieve that. The function assigns each cell value that lies within a defined interval a certain value. For example, you can assign cell values within interval (0,5]
to value 0
and cell values within the interval (5, maxSlope]
to value 1
.
library(raster)
library(rasterVis)
elevation <- getData("alt", country = "PHL")
x <- terrain(elevation, opt = c("slope", "aspect"), unit = "degrees")
plot(x$slope)
e <- drawExtent(show = TRUE)
gewataSub <- crop(x, e)
plot(gewataSub$slope, 1)
m <- c(0, 5, 0, 5, maxValue(gewataSub$slope), 1)
rclmat <- matrix(m, ncol = 3, byrow = TRUE)
rc <- reclassify(gewataSub$slope, rclmat)
levelplot(
rc,
margin = F,
col.regions = c("wheat", "gray"),
colorkey = list(at = c(0, 1, 2), labels = list(at = c(0.5, 1.5), labels = c("<= 5", "> 5")))
)
After the reclassification you can calculate the percentages:
length(rc[rc == 0]) / (length(rc[rc == 0]) + length(rc[rc == 1])) # <= 5 degrees
[1] 0.6628788
length(rc[rc == 1]) / (length(rc[rc == 0]) + length(rc[rc == 1])) # > 5 degrees
[1] 0.3371212