Automating site suitability

Part 1: Exporting a tool as a Python script

1. Open your model from the in-class exercise from the previous class period

2. From the Model Builder menu, click on “Export -> Send to Python Window”

3. From the Model Builder menu, click on “Export -> Export to Python file”

4. Inspect the file in a text editor

Part 2: Adding parameters to a model

1. Open your model from the in-class exercise from the previous class period

2. From the Model Builder menu, click on the “Variable” icon

3. For the variable type, select “Coordinate System”

4. Then, right-click on the variable and select “Parameter”

5. Save your model. Then open the model by double clicking on it. You should see the Coordinate System parameter available.

Part 3: Further automation

• Run the following line of code from the console in RStudio to install necessary packages:

install.packages(c("tigris", "raster", "dplyr", "sf", "leaflet"))

• Follow along with the instructor by copying, pasting, and editing the code below:

library(tigris)
library(raster)
library(dplyr)
library(sf)
library(leaflet)

wi_dem <- raster("Q:/StudentCoursework/Haffnerm/DATA/DEM_30m/demgw930/")

plot(wi_dem)

site_suitability <- function(input_raster, county, slope_min, slope_max, asp_min, asp_max) {
  ## download counties data from US Census
  counties <- counties(state = "Wisconsin", class = "sf", cb = TRUE, progress_bar = FALSE)

  ## filter county, transform crs
  county <- counties %>%
    filter(NAME == !!county) %>%
    st_transform(., crs(input_raster))

  ## crop raster to area of interest
  county_dem <- crop(wi_dem, county)

  ## create suitability raster
  suit_rast <-
    terrain(county_dem, opt = "slope", unit = "degrees") > slope_min &
    terrain(county_dem, opt = "slope", unit = "degrees") < slope_max &
    terrain(county_dem, opt = "aspect", unit = "degrees") > asp_min &
    terrain(county_dem, opt = "aspect", unit = "degrees") < asp_max

  ## set plot parameters
  par(mfrow = c(2,2))

  ## plot each step
  plot(county_dem, main = "DEM")
  plot(terrain(county_dem, opt = "slope", unit = "degrees") > slope_min &
       terrain(county_dem, opt = "slope", unit = "degrees") < slope_max,
       main = "Slope criteria",
       col = c("white", "blue"))
  plot(terrain(county_dem, opt = "aspect", unit = "degrees") > asp_min &
       terrain(county_dem, opt = "aspect", unit = "degrees") < asp_max,
       main = "Aspect criteria",
       col = c("white", "orange"))
  plot(suit_rast,
       main = "Suitable areas",
       col = c("white", "black"))

  ## reset plot parameters
  par(mar = c(1,1,1,1))

  return(suit_rast)
}


suitable_locations <- site_suitability(input_raster = _____,
                                       county = _____,
                                       slope_min = _____,
                                       slope_max = _____,
                                       asp_min = _____,
                                       asp_max = _____)

leaflet(width = "100%") %>%
  addTiles() %>%
  addRasterImage(suitable_locations, opacity = 0.5, col = c("#ffffff", "#ff0000"))

Imagine you are seeking to build a solar farm in Buffalo County. Set the slope and aspect parameters properly to find suitable locations.