Create a Tibble for a location's AOD readings at a given hour

Creates a time series Tibble for AOD at the given coordinates. The readings are approximated by tracking the AOD values for raster cells close to the coordinates.

raster_createLocationTimeseries(
  rasterStack = NULL,
  longitude = NULL,
  latitude = NULL,
  bbox = NULL,
  method = "simple",
  buffer = NULL,
  fun = mean
)

Arguments

rasterStack	a RasterStack with a RasterLayer for every data snapshot.
longitude	Longitude of the location of interest in decimal degrees E.
latitude	Latitude of the location of interest in decimal degrees N.
bbox	bounding box for the rasters.
method	determines how a value is extracted from the location if a buffer is not used. Can be set to either "simple", which returns the exact value of the cell the coordinates fall in, or "bilinear", which interpolates the four nearest raster cell values.
buffer	radius for a circluar region around the location. If multiple cells fall within this region then all of their values are aggregated by the 'fun' method. Radius is measured in map units (typically meters).
fun	function for aggregating all the values in the buffer (if buffer is used)

Value

Tibble

Examples

if (FALSE) {

library(MazamaSatelliteUtils)
library(MazamaSpatialUtils)
setSatelliteDataDir("~/Data/Satellite")
setSpatialDataDir("~/Data/Spatial")
loadSpatialData("USCensusStates")

# Oregon on August 1, 2019 at 12pm (Milepost 97 Fire)
datetime <- "2019-08-01 19"
timezone <- "UTC"
oregon <- subset(USCensusStates, stateCode == "OR")
bbox_oregon <- sp::bbox(oregon)
lon <- -123.245
lat <- 42.861

# Gather all the raster layers for the given hour into a stack
rasterStack <- goesaodc_createRasterStack(
  satID = "G16",
  datetime = datetime,
  timezone = timezone,
  bbox = bbox_oregon,
  res = 0.05,
  dqfLevel = 2,
  verbose = TRUE
)

rasterAvg <- raster::mean(rasterStack, na.rm = TRUE)
tb <- raster_createLocationTimeseries(rasterStack = rasterStack,
                                      longitude = lon, latitude = lat,
                                      bbox = bbox_oregon,
                                      buffer = 1000)

# Plot AOD time series
pal_aod <- colorRampPalette(c("lightgoldenrod1", "red3"))
par(mfrow = c(1, 2))
raster::plot(rasterAvg, main = "Average AOD", col = pal_aod(50),
             xlim = c(-125, -122), ylim = c(42, 44))
plot(oregon, add = TRUE)
points(x = c(lon), y = c(lat), cex = 2.0, pch = 3, lwd = 1.5)
plot(x = tb$datetime, y = tb$aod, pch = 15, cex = 1,
     main = datetime, xlab = "Time", ylab = "AOD")
}