mikemahoney218

# values specific to your stac source
# in this case, from 
# https://planetarycomputer.microsoft.com/dataset/usgs-lcmap-conus-v13
COLLECTION="usgs-lcmap-conus-v13"
ASSET="lcpri"

# query parameters: bbox (wgs84) and datetime (utc)
# I grabbed these values from R
WGS84_BBOX="-79.762,40.496,-71.856,45.013"
DATETIME="2021-01-01/2021-12-31"

mikemahoney218

stack_rasters <- function(rasters,
                          raster_path,
                          ...,
                          reference_layer = 1,
                          resampling_method = "bilinear") {

  check_type_and_length(
    reference_layer = integer(1)
  )

mikemahoney218

FROM tuxmake/clang-15

RUN apt-get update -y ; apt-get install -y curl

RUN curl -Ls https://github.com/r-lib/rig/releases/download/latest/rig-linux-latest.tar.gz | tar xz -C /usr/local

RUN rig add devel

RUN mkdir ~/.R

mikemahoney218

library(spatialsample)

# Might need to get the CRS if you haven't before:
sf::sf_proj_network(TRUE)
sf::sf_add_proj_units()

spatial_clustering_cv(boston_canopy, v = 5) |> 
  autoplot()

spatial_block_cv(boston_canopy, v = 5, method = "snake") |> 

mikemahoney218

# remotes::install_github('tidymodels/spatialsample')
library(spatialsample)
library(cluster)

make_clusters <- function(func) { 
  set.seed(123)
  boston_canopy |> 
    spatial_clustering_cv(cluster_function = func) |> 
    autoplot() 
}

mikemahoney218

# 12.5 Spatial CV (with spatialsample)

library(tidymodels)
library(spatialsample)
library(sf)

data("lsl", "study_mask", package = "spDataLarge")
lsl <- lsl |> 
  st_as_sf(coords = c("x", "y"), crs = "EPSG:32717")
ta <- terra::rast(system.file("raster/ta.tif", package = "spDataLarge"))

mikemahoney218

.cursor <- R6::R6Class(
  "cursor",
  list(
    x = 0,
    y = 0,
    direction = 0,
    left = function() {
      self$direction <- self$direction + 270
      invisible(self)
    },

mikemahoney218

library(sf)
library(tidycensus)
library(dplyr)
library(ggplot2)
options(tigris_use_cache = TRUE)

acs_pop <- do.call(
  rbind,
  lapply(
    setdiff(state.abb, c("AK", "HI")),

mikemahoney218

library(terrainr)
library(raster)
library(rayshader)
library(sf)

baker <- tmaptools::geocode_OSM("Mount Baker")
baker <- st_as_sf(as.data.frame(t(as.data.frame(baker$coords))), coords = c("x", "y"), crs = 4326)
zscale <- 5
baker <- set_bbox_side_length(
  baker,

mikemahoney218

library(sf)
library(tidycensus)
library(ggplot2)
library(dplyr)

acs_pop <- lapply(
  setdiff(state.abb, c("AK", "HI")),
  \(x) {
    get_acs(
      geography = "block group",