Create interactive visualisations of spatial EE objects (Geometry, Image, Feature, FeatureCollection or ImageCollection) base on mapview.
ee_map(eeobject, ...) # S3 method for default ee_map(eeobject, ...) # S3 method for ee.geometry.Geometry ee_map(eeobject, vizparams, center, zoom_start = 8, objname = "map", quiet = FALSE, ...) # S3 method for ee.feature.Feature ee_map(eeobject, vizparams, center, zoom_start = 8, objname = "map", quiet = FALSE, ...) # S3 method for ee.featurecollection.FeatureCollection ee_map(eeobject, vizparams, center, zoom_start = 8, objname = "map", quiet = FALSE, ...) # S3 method for ee.image.Image ee_map(eeobject, vizparams, center, zoom_start = 8, objname = "map", quiet = FALSE, ...) # S3 method for ee.imagecollection.ImageCollection ee_map(eeobject, vizparams, center, zoom_start = 8, objname = "map", max_nimage = 10, quiet = FALSE, ...)
| eeobject | An EE spatial object. |
|---|---|
| ... | Ignored. |
| vizparams | A list that contains the visualization parameters. See details. |
| center | The longitude and latitude of the map center. If it is not defined, the centroid of the spatial EE object is taked. |
| zoom_start | zoom level. |
| objname | character vector. Name of the map, or maps in case that the EE object be an ImageCollection. |
| quiet | logical; suppress info messages. |
| max_nimage | Max number of Image to display. |
ee_map takes advantage of the ee$Image()$getMapId python function for fetch and return
a mapid and token that is suitable for use in a mapview. To achieve desirable
visualization effects, it is depend on the type of spatial EE object . For neither Image or
ImageCollection, you can provide visualization parameters to ee_map by the parameter vizparams.
The parameters available are:
| Parameter | Description | Type |
| bands | Comma-delimited list of three band names to be mapped to 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 DN | 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 images only) | comma-separated list of hex strings |
| opacity | The opacity of the layer (0.0 is fully transparent and 1.0 is fully opaque) | number |
If you add an Image or ImageCollection to the map without any additional parameters,
by default ee_map assigns the first three bands to red, green and blue, respectively.
The default stretch is based on the min-max range. For Geometry, Feature or
FeatureCollection. The available vizparams are:
color: A hex string in the format RRGGBB specifying the color to use for drawing the features. By default 000000.
pointRadius: The radius of the point markers. By default 3.
strokeWidth: The width of lines and polygon borders. By default 3.
if (FALSE) { library(rgee) ee_Initialize() # Case: Geometry* geom <- ee$Geometry$Point(list(-73.53522, -15.75453)) m1 <- ee_map( eeobject = geom, vizparams = list(pointRadius = 10, color = "FF0000"), objname = "Geometry-Arequipa" ) m1 # Case: Feature eeobject_fc <- ee$FeatureCollection("users/csaybar/DLdemos/train_set")$first() m2 <- ee_map(eeobject = ee$Feature(eeobject_fc), objname = "Feature-Arequipa") m2 + m1 # Case: FeatureCollection eeobject_fc <- ee$FeatureCollection("users/csaybar/DLdemos/train_set") m3 <- ee_map(eeobject = eeobject_fc, objname = "FeatureCollection") m3 + m2 + m1 # Case: Image image <- ee$Image("LANDSAT/LC08/C01/T1/LC08_044034_20140318") m4 <- ee_map( eeobject = image, vizparams = list( bands = c("B4", "B3", "B2"), max = 10000 ), objname = "SF", zoom_start = "8" ) m4 # Case: ImageCollection collection <- ee$ImageCollection("LANDSAT/LC08/C01/T1_TOA")$ filter(ee$Filter()$eq("WRS_PATH", 44))$ filter(ee$Filter()$eq("WRS_ROW", 34))$ filterDate("2014-01-01", "2015-01-01")$ sort("CLOUD_COVER") m5 <- ee_map( eeobject = collection, vizparams = list(bands = c("B4", "B3", "B2"), max = 1), objname = c("Scene_2019", "Scene_2016", "Scene_2011"), max_nimage = 3, zoom_start = 10 ) m5 }