initial commit

.gitignore

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+.Rproj.user
+.Rhistory
+.RData
+.Ruserdata
+hamilton_landcover/

get_nlcd_rasters.R

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+library(tidyverse)
+library(sf)
+library(terra)
+
+hc <- cincy::county_7cc_2010 |> filter(county_name == "Hamilton")
+
+# nlcd
+nlcd_tif <- s3::s3_get(glue::glue("s3://geomarker/nlcd_cog/nlcd_landcover_2019.tif"))
+nlcd <- terra::rast(nlcd_tif)
+nlcd_hc_2019 <- terra::crop(nlcd, hc)
+terra::writeRaster(nlcd_hc_2019, "rasters/nlcd_hc_2019.tif")
+fs::dir_delete("s3_downloads")
+
+# impervious
+impervious_tif <- s3::s3_get(glue::glue("s3://geomarker/nlcd_cog/nlcd_impervious_2019.tif"))
+impervious <- terra::rast(impervious_tif)
+impervious_hc_2019 <- terra::crop(impervious, hc)
+terra::writeRaster(impervious_hc_2019, "rasters/impervious_hc_2019.tif")
+fs::dir_delete("s3_downloads")
+
+# tree canopy
+tree_tif <- s3::s3_get(glue::glue("s3://geomarker/nlcd_cog/nlcd_treecanopy_2016.tif"))
+treecanopy <- terra::rast(tree_tif)
+treecanopy_hc_2016 <- terra::crop(treecanopy, hc)
+terra::writeRaster(treecanopy_hc_2016, "rasters/treecanopy_hc_2016.tif")
+fs::dir_delete("s3_downloads")
+
+# evi
+evi_tif <- s3::s3_get(glue::glue("s3://geomarker/modis_evi_ndvi/evi_June_2018_5072.tif"))
+evi <- terra::rast(evi_tif)
+evi_hc_2018 <- terra::crop(evi, hc)
+terra::writeRaster(evi_hc_2018, "rasters/evi_hc_2018.tif")
+fs::dir_delete("s3_downloads")

make_tract_nlcd.R

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+library(tidyverse)
+library(sf)
+library(terra)
+library(CODECtools)
+source("nlcd_legend.R")
+
+tract <- terra::vect(cincy::tract_tigris_2010)
+
+# NLCD - greenspace
+nlcd_hc_2019 <- terra::rast("rasters/nlcd_hc_2019.tif")
+
+pct_green <- 
+  terra::extract(nlcd_hc_2019, 
+                 tract) |>
+  rename(value = Layer_1) |>
+  left_join(nlcd_legend, by = "value") |>
+  group_by(ID) |>
+  summarize(pct_green_2019 = round(sum(green) / n() * 100)) |>
+  select(-ID)
+
+tract_nlcd <- bind_cols(cincy::tract_tigris_2010, pct_green)
+
+# NLCD - impervious
+impervious_hc_2019 <- terra::rast("rasters/impervious_hc_2019.tif")
+
+pct_impervious <- 
+  terra::extract(impervious_hc_2019, 
+                 tract, 
+                 fun = "mean") |>
+  rename(value = Layer_1) |>
+  summarize(pct_impervious_2019 = round(value))
+
+tract_nlcd <- bind_cols(tract_nlcd, pct_impervious)
+
+# NLCD - treecanopy
+treecanopy_hc_2016 <- terra::rast("rasters/treecanopy_hc_2016.tif")
+
+pct_treecanopy <- 
+  terra::extract(treecanopy_hc_2016, 
+                 tract, 
+                 fun = "mean") |>
+  rename(value = Layer_1) |>
+  summarize(pct_treecanopy_2016 = round(value))
+
+tract_nlcd <- bind_cols(tract_nlcd, pct_treecanopy)
+
+# EVI
+evi_hc_2018 <- terra::rast("rasters/evi_hc_2018.tif")
+
+evi <- 
+  terra::extract(evi_hc_2018, 
+                 tract, 
+                 fun = "mean", 
+                 na.rm = TRUE) |>
+  rename(evi_2018 = evi_June_2018_5072) |>
+  mutate(evi_2018 = round(evi_2018 * 0.0001, 4)) |>
+  select(-ID)
+
+tract_nlcd <- bind_cols(tract_nlcd, evi)
+tract_nlcd <- sf::st_drop_geometry(tract_nlcd)
+
+tract_nlcd <- tract_nlcd |>
+  add_attrs(
+    name = "hamilton_landcover",
+    title = "Hamilton County Landcover and Built Environment Characteristics",
+    version = "0.1.0",
+    homepage = "https://geomarker.io/hamilton_landcover"
+  )
+
+tract_nlcd <-
+  tract_nlcd |>
+  add_col_attrs(census_tract_id, title = "Census Tract Identifier") |>
+  add_col_attrs(pct_green_2019, title = "Percent Greenspace 2019", description = "percent of pixels in each tract classified as green") |>
+  add_col_attrs(pct_impervious_2019, title = "Percent Impervious 2019", description = "average percent imperviousness for pixels in each tract") |>
+  add_col_attrs(pct_treecanopy_2016, title = "Percent Treecanopy 2016", description = "average percent tree canopy for pixels in each tract") |>
+  add_col_attrs(evi_2018, title = "Enhanced Vegetation Index 2018", description = "average enhanced vegetation index for pixels in each tract")
+
+tract_nlcd <- add_type_attrs(tract_nlcd)
+
+# write metadata.md
+cat("#### Metadata\n\n", file = "metadata.md", append = FALSE)
+CODECtools::glimpse_attr(tract_nlcd) |>
+  knitr::kable() |>
+  cat(file = "metadata.md", sep = "\n", append = TRUE)
+
+cat("\n#### Schema\n\n", file = "metadata.md", append = TRUE)
+tract_nlcd |>
+  CODECtools::glimpse_schema() |>
+  knitr::kable() |>
+  cat(file = "metadata.md", sep = "\n", append = TRUE)
+
+write_tdr_csv(tract_nlcd)

metadata.md

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+#### Metadata
+
+|name     |value                                                           |
+|:--------|:---------------------------------------------------------------|
+|name     |hamilton_landcover                                              |
+|version  |0.1.0                                                           |
+|title    |Hamilton County Landcover and Built Environment Characteristics |
+|homepage |https://geomarker.io/hamilton_landcover                         |
+
+#### Schema
+
+|name                |title                          |type   |description                                                |
+|:-------------------|:------------------------------|:------|:----------------------------------------------------------|
+|census_tract_id     |Census Tract Identifier        |string |NA                                                         |
+|pct_green_2019      |Percent Greenspace 2019        |number |percent of pixels in each tract classified as green        |
+|pct_impervious_2019 |Percent Impervious 2019        |number |average percent imperviousness for pixels in each tract    |
+|pct_treecanopy_2016 |Percent Treecanopy 2016        |number |average percent tree canopy for pixels in each tract       |
+|evi_2018            |Enhanced Vegetation Index 2018 |number |average enhanced vegetation index for pixels in each tract |

nlcd_legend.R

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+nlcd_legend <-
+  tibble::tribble(
+    ~value, ~landcover_class, ~landcover, ~green,
+    11, "water", "water", FALSE,
+    12, "water", "ice/snow", FALSE,
+    21, "developed", "developed open", TRUE,
+    22, "developed", "developed low intensity", TRUE,
+    23, "developed", "developed medium intensity", FALSE,
+    24, "developed", "developed high intensity", FALSE,
+    31, "barren", "rock/sand/clay", FALSE,
+    41, "forest", "deciduous forest", TRUE,
+    42, "forest", "evergreen forest", TRUE,
+    43, "forest", "mixed forest", TRUE,
+    51, "shrubland", "dwarf scrub", TRUE,
+    52, "shrubland", "shrub/scrub", TRUE,
+    71, "herbaceous", "grassland", TRUE,
+    72, "herbaceous", "sedge", TRUE,
+    73, "herbaceous", "lichens", TRUE,
+    74, "herbaceous", "moss", TRUE,
+    81, "cultivated", "pasture/hay", TRUE,
+    82, "cultivated", "cultivated crops", TRUE,
+    90, "wetlands", "woody wetlands", TRUE,
+    95, "wetlands", "emergent herbaceous wetlands", TRUE
+  )