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R6 object (Map) to display Earth Engine (EE) spatial objects — Map • rgee

Create interactive visualizations of spatial EE objects (ee$FeatureCollection, ee$ImageCollection, ee$Geometry, ee$Feature, and ee$Image.) using leaflet in the backend.

Format

An object of class environment with the following functions:

Value

Object of class leaflet, with the following extra parameters: tokens, name, opacity, shown, min, max, palette, and legend. Use the $ method to retrieve the data (e.g. m$rgee$min).

Details

Map use the Earth Engine method getMapId to fetch and return an ID dictionary being used to create layers in a leaflet object. Users can specify visualization parameters to Map$addLayer by using the visParams argument. Each Earth Engine spatial object has a specific format. For ee$Image, the parameters available are:

Parameter Description Type bands Comma-delimited list of three band (RGB) list min Value(s) to map to 0 number or list of three numbers, one for each band max Value(s) to map to 1 number or list of three numbers, one for each band gain Value(s) by which to multiply each pixel value number or list of three numbers, one for each band bias Value(s) to add to each Digital Number value number or list of three numbers, one for each band gamma Gamma correction factor(s) number or list of three numbers, one for each band palette List of CSS-style color strings (single-band only) comma-separated list of hex strings opacity The opacity of the layer (from 0 to 1) number

If you add an ee$Image to Map$addLayer without any additional parameters, by default it assigns the first three bands to red, green, and blue bands, respectively. The default stretch is based on the min-max range. On the other hand, the available parameters for ee$Geometry, ee$Feature, and ee$FeatureCollection are:

Examples
if (FALSE) { # \dontrun{
library(rgee)
library(sf)

ee_Initialize()

# Case 1: Geometry*
geom1 <- ee$Geometry$Point(list(-73.53, -15.75))
Map$centerObject(geom1, zoom = 8)
m1 <- Map$addLayer(
  eeObject = geom1,
  visParams = list(
    pointRadius = 10,
    color = "FF0000"
  ),
  name = "Geometry-Arequipa"
)

# Case 2: Feature
feature_arq <- ee$Feature(ee$Geometry$Point(list(-72.53, -15.75)))
m2 <- Map$addLayer(
  eeObject = feature_arq,
  name = "Feature-Arequipa"
)
m2 + m1

# Case 4: Image
image <- ee$Image("LANDSAT/LC08/C01/T1/LC08_044034_20140318")
Map$centerObject(image)
m4 <- Map$addLayer(
  eeObject = image,
  visParams = list(
    bands = c("B4", "B3", "B2"),
    max = 10000
  ),
  name = "SF"
)

# Case 5: ImageCollection
nc <- st_read(system.file("shape/nc.shp", package = "sf")) %>%
  st_transform(4326) %>%
  sf_as_ee()

ee_s2 <- ee$ImageCollection("COPERNICUS/S2")$
  filterDate("2016-01-01", "2016-01-31")$
  filterBounds(nc)
ee_s2 <- ee$ImageCollection(ee_s2$toList(2))

Map$centerObject(nc$geometry())
m5 <- Map$addLayers(ee_s2)
m5

# Case 6: Map comparison
image <- ee$Image("LANDSAT/LC08/C01/T1/LC08_044034_20140318")
Map$centerObject(image)
m_ndvi <- Map$addLayer(
  eeObject = image$normalizedDifference(list("B5", "B4")),
  visParams = list(min = 0, max = 0.7),
  name = "SF_NDVI"
) + Map$addLegend(list(min = 0, max = 0.7), name = "NDVI", position = "bottomright", bins = 4)
m6 <- m4 | m_ndvi
m6

# Case 7: digging up the metadata
m6$rgee$tokens
m5$rgee$tokens

# Case 8: COG support
# See parameters here: https://api.cogeo.xyz/docs

server <- "https://storage.googleapis.com/pdd-stac/disasters/"
file <- "hurricane-harvey/0831/20170831_172754_101c_3B_AnalyticMS.tif"
resource <- paste0(server, file)
visParams <- list(bands = c("B3", "B2", "B1"), min = 3000, max = 13500, nodata = 0)
Map$centerObject(resource)
Map$addLayer(resource, visParams = visParams, shown = TRUE)
} # }

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