Download ArcGIS FeatureServer and MapServer Data to Simple Features
Note: This package has diverged substantially from the original esri2sf package and I am unsure when or if any of the code may be merged back into the original repository. I am actively maintaining this package so please feel free to submit an issue if you have any feature requests or problems.
The ArcGIS FeatureServer or MapServer services are among the most common sources for geospatial data. The esri2sf package enables users to download data from an ArcGIS Server to a simple feature (sf) or data frame object using the ArcGIS REST API. You can learn more about working with sf objects in the documentation for the sf package.
This package takes the layer URL and query (created from a bounding box, geometry, and other parameters). Typically, the ArcGIS REST API limits the maximum number of rows that can be returned from a single query. This package uses httr2 to query the server and initially returns the ID for all features and then batches the IDs to return all requested features from the server.
The geometry is returned as a FeatureSet object (also known as an ESRI JSON object). The JSON is converted into an sf object and combined with the attribute data to return an sf data frame.
Use pak to install this fork of the esri2sf package from GitHub:
pak::pkg_install("elipousson/esri2sf")To use esri2sf, you need is the URL of a FeatureServer or MapServer layer you want to download. You can get the URL by viewing the URL widget on the service’s webpage (see image below), by asking a GIS admin, or looking at the code of a webpage where it creates a feature layer.
You can then use the url with esri2sf to download data:
library(esri2sf)
url <- "https://services.arcgis.com/V6ZHFr6zdgNZuVG0/arcgis/rest/services/Landscape_Trees/FeatureServer/0"
df <- esri2sf(url)
#> ── Downloading "Landscape_Trees" from <https://services.arcgis.com/V6ZHFr6zdgNZu
#> Layer type: "Feature Layer"
#> Geometry type: "esriGeometryPoint"
#> Service CRS: "EPSG:3857"
#> Output CRS: "EPSG:4326"
#>
plot(df)
#> Warning: plotting the first 9 out of 56 attributes; use max.plot = 56 to plot
#> all
You can select specific output fields. You can check the names of the
data source columns using the esrimeta() function with
fields = TRUE. Set progress = TRUE to show a progress bar for larger
downloads (such as this 18000 polyline data).
url <- "https://services.arcgis.com/V6ZHFr6zdgNZuVG0/arcgis/rest/services/Florida_Annual_Average_Daily_Traffic/FeatureServer/0"
esrimeta(url, fields = TRUE)
#> name type actualType alias
#> 1 FID esriFieldTypeOID int FID
#> 2 YEAR_ esriFieldTypeSmallInteger smallint YEAR_
#> 3 DISTRICT esriFieldTypeString nvarchar DISTRICT
#> 4 COSITE esriFieldTypeString nvarchar COSITE
#> 5 ROADWAY esriFieldTypeString nvarchar ROADWAY
#> 6 DESC_FRM esriFieldTypeString nvarchar DESC_FRM
#> 7 DESC_TO esriFieldTypeString nvarchar DESC_TO
#> 8 AADT esriFieldTypeInteger int AADT
#> 9 AADTFLG esriFieldTypeString nvarchar AADTFLG
#> 10 KFLG esriFieldTypeString nvarchar KFLG
#> 11 K100FLG esriFieldTypeString nvarchar K100FLG
#> 12 DFLG esriFieldTypeString nvarchar DFLG
#> 13 TFLG esriFieldTypeString nvarchar TFLG
#> 14 BEGIN_POST esriFieldTypeDouble float BEGIN_POST
#> 15 END_POST esriFieldTypeDouble float END_POST
#> 16 KFCTR esriFieldTypeDouble float KFCTR
#> 17 K100FCTR esriFieldTypeDouble float K100FCTR
#> 18 DFCTR esriFieldTypeDouble float DFCTR
#> 19 TFCTR esriFieldTypeDouble float TFCTR
#> 20 Shape_Leng esriFieldTypeDouble float Shape_Leng
#> 21 TFCTR_copy esriFieldTypeDouble <NA> % truck volume per day
#> 22 TRUCK_PER esriFieldTypeDouble <NA> % of truck traffic per day
#> sqlType nullable editable domain defaultValue length
#> 1 sqlTypeInteger FALSE FALSE NA NA NA
#> 2 sqlTypeSmallInt TRUE TRUE NA NA NA
#> 3 sqlTypeNVarchar TRUE TRUE NA NA 1
#> 4 sqlTypeNVarchar TRUE TRUE NA NA 6
#> 5 sqlTypeNVarchar TRUE TRUE NA NA 8
#> 6 sqlTypeNVarchar TRUE TRUE NA NA 30
#> 7 sqlTypeNVarchar TRUE TRUE NA NA 30
#> 8 sqlTypeInteger TRUE TRUE NA NA NA
#> 9 sqlTypeNVarchar TRUE TRUE NA NA 1
#> 10 sqlTypeNVarchar TRUE TRUE NA NA 1
#> 11 sqlTypeNVarchar TRUE TRUE NA NA 1
#> 12 sqlTypeNVarchar TRUE TRUE NA NA 1
#> 13 sqlTypeNVarchar TRUE TRUE NA NA 1
#> 14 sqlTypeFloat TRUE TRUE NA NA NA
#> 15 sqlTypeFloat TRUE TRUE NA NA NA
#> 16 sqlTypeFloat TRUE TRUE NA NA NA
#> 17 sqlTypeFloat TRUE TRUE NA NA NA
#> 18 sqlTypeFloat TRUE TRUE NA NA NA
#> 19 sqlTypeFloat TRUE TRUE NA NA NA
#> 20 sqlTypeFloat TRUE TRUE NA NA NA
#> 21 sqlTypeOther TRUE TRUE NA NA NA
#> 22 sqlTypeOther TRUE TRUE NA NA NA
df <- esri2sf(url, outFields = c("AADT", "DFLG"))
#> ── Downloading "Florida_Annual_Average_Daily_Traffic" from <https://services.arc
#> Layer type: "Feature Layer"
#> Geometry type: "esriGeometryPolyline"
#> Service CRS: "EPSG:3857"
#> Output CRS: "EPSG:4326"
#>
plot(df)
You can filter rows as well by providing a where condition in
standardized SQL (SQL-92) that is applied to non-spatial attributes.
Seethe ArcGIS
documentation
for more information on supported operators and functions.
url <- "https://sampleserver6.arcgisonline.com/arcgis/rest/services/Census/MapServer/2"
mi <- esri2sf(
url,
where = "STATE_NAME = 'Michigan'",
outFields = c("POP2000", "pop2007", "POP00_SQMI", "POP07_SQMI")
)
#> ── Downloading "Detailed Counties" from <https://sampleserver6.arcgisonline.com/
#> Layer type: "Feature Layer"
#> Geometry type: "esriGeometryPolygon"
#> Service CRS: "EPSG:4269"
#> Output CRS: "EPSG:4326"
#>
plot(mi)
You can download non-spatial tables of the ‘Table’ layer type using
esri2df().
df <- esri2df("https://sampleserver6.arcgisonline.com/arcgis/rest/services/SF311/MapServer/1", where = "category = 'VEHICLE THEFT'")
#> ── Downloading "SF_Crime_Incidents" from <https://sampleserver6.arcgisonline.com
#> Layer type: "Table"
#>
df
#> # A tibble: 1,254 × 10
#> objectid incidntnum category descript dayofweek date_ time pddistrict
#> <int> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 26961944 090786072 VEHICLE THEFT STOLEN AU… Sunday 08/0… 23:00 CENTRAL
#> 2 26961973 090846466 VEHICLE THEFT STOLEN TR… Wednesday 08/1… 01:08 BAYVIEW
#> 3 26962047 090746270 VEHICLE THEFT ATTEMPTED… Wednesday 07/2… 00:01 INGLESIDE
#> 4 26962054 090751978 VEHICLE THEFT STOLEN AU… Thursday 07/2… 23:00 INGLESIDE
#> 5 26962055 090753413 VEHICLE THEFT STOLEN AU… Thursday 07/2… 18:30 NORTHERN
#> 6 26962060 090761046 VEHICLE THEFT STOLEN TR… Sunday 07/2… 18:00 INGLESIDE
#> 7 26962061 090764802 VEHICLE THEFT STOLEN AU… Monday 07/2… 21:00 MISSION
#> 8 26962063 090766820 VEHICLE THEFT STOLEN AU… Monday 07/2… 18:30 RICHMOND
#> 9 26962083 090770718 VEHICLE THEFT STOLEN AU… Tuesday 07/2… 16:00 TARAVAL
#> 10 26962085 090771261 VEHICLE THEFT STOLEN AU… Monday 07/2… 19:00 NORTHERN
#> # ℹ 1,244 more rows
#> # ℹ 2 more variables: resolution <chr>, datetime <dbl>In some cases, tables may include coordinates as numeric attribute
columns but no geometry. If this is the case, you can create a bounding
box filter condition using the glue_sql_bbox() helper function:
# Using the Michigan sf data to create a bbox
bbox <- sf::st_bbox(mi)
coords <- c("longitude", "latitude")
glue_sql_bbox(bbox, coords)
#> <SQL> (longitude >= -90.4181359945804) AND (longitude <= -82.4183959883841) AND (latitude >= 41.6960880241431) AND (latitude <= 48.1895339877034)When specifying the CRS parameter, any transformation that happens will
be done within the ArcGIS REST API. Caution should be taken when
specifying an output crs that requires a datum transformation as ESRI
will automatically apply a default transformation (with no feedback as
to which one) which could end up adding small unexpected errors into
your data.
By default, esri2sf() will transform any data to WGS 1984 (EPSG:4326),
but it may be safer to set crs = NULL which will return the data in
the same CRS as the host service. You can also set an alternate default
crs using options, e.g. options("esri2sf.crs", 3857).
url <- "https://sampleserver6.arcgisonline.com/arcgis/rest/services/Census/MapServer/2"
where <- "STATE_NAME = 'Michigan'"
outFields <- c("POP2000", "pop2007", "POP00_SQMI", "POP07_SQMI")
# default crs = 4326
esri2sf(url, where = where, outFields = outFields)
#> ── Downloading "Detailed Counties" from <https://sampleserver6.arcgisonline.com/
#> Layer type: "Feature Layer"
#> Geometry type: "esriGeometryPolygon"
#> Service CRS: "EPSG:4269"
#> Output CRS: "EPSG:4326"
#>
#> Simple feature collection with 83 features and 4 fields
#> Geometry type: MULTIPOLYGON
#> Dimension: XY
#> Bounding box: xmin: -90.41814 ymin: 41.69609 xmax: -82.4184 ymax: 48.18953
#> Geodetic CRS: WGS 84
#> First 10 features:
#> POP2000 POP2007 POP00_SQMI POP07_SQMI geoms
#> 1 11719 11941 16.9 17.2 MULTIPOLYGON (((-83.88856 4...
#> 2 9862 10188 10.5 10.9 MULTIPOLYGON (((-86.64985 4...
#> 3 105665 116417 125.4 138.2 MULTIPOLYGON (((-86.2447 42...
#> 4 31314 30120 52.8 50.8 MULTIPOLYGON (((-83.88972 4...
#> 5 23110 25435 44.0 48.5 MULTIPOLYGON (((-85.38891 4...
#> 6 17269 17912 47.0 48.7 MULTIPOLYGON (((-84.16662 4...
#> 7 8746 8760 9.5 9.5 MULTIPOLYGON (((-88.64074 4...
#> 8 56755 60956 98.3 105.6 MULTIPOLYGON (((-85.54387 4...
#> 9 110157 109920 245.9 245.3 MULTIPOLYGON (((-84.16703 4...
#> 10 15998 18565 46.0 53.4 MULTIPOLYGON (((-86.25825 4...
# No transformation (recommended)
esri2sf(url, where = where, outFields = outFields, crs = NULL)
#> ── Downloading "Detailed Counties" from <https://sampleserver6.arcgisonline.com/
#> Layer type: "Feature Layer"
#> Geometry type: "esriGeometryPolygon"
#> Service CRS: "EPSG:4269"
#> Output CRS: "EPSG:4269"
#>
#> Simple feature collection with 83 features and 4 fields
#> Geometry type: MULTIPOLYGON
#> Dimension: XY
#> Bounding box: xmin: -90.41813 ymin: 41.69608 xmax: -82.41839 ymax: 48.18953
#> Geodetic CRS: NAD83
#> First 10 features:
#> POP2000 POP2007 POP00_SQMI POP07_SQMI geoms
#> 1 11719 11941 16.9 17.2 MULTIPOLYGON (((-83.88856 4...
#> 2 9862 10188 10.5 10.9 MULTIPOLYGON (((-86.64984 4...
#> 3 105665 116417 125.4 138.2 MULTIPOLYGON (((-86.24469 4...
#> 4 31314 30120 52.8 50.8 MULTIPOLYGON (((-83.88971 4...
#> 5 23110 25435 44.0 48.5 MULTIPOLYGON (((-85.3889 45...
#> 6 17269 17912 47.0 48.7 MULTIPOLYGON (((-84.16662 4...
#> 7 8746 8760 9.5 9.5 MULTIPOLYGON (((-88.64073 4...
#> 8 56755 60956 98.3 105.6 MULTIPOLYGON (((-85.54387 4...
#> 9 110157 109920 245.9 245.3 MULTIPOLYGON (((-84.16702 4...
#> 10 15998 18565 46.0 53.4 MULTIPOLYGON (((-86.25824 4...The glue_ansi_sql() helper is useful when building queries with
vectors of possible values:
states <- c("Alabama", "Michigan")
where <- glue_ansi_sql("STATE_NAME", " IN ({states*})")
esri2sf(url, where = where, outFields = c("STATE_NAME", outFields))
#> ── Downloading "Detailed Counties" from <https://sampleserver6.arcgisonline.com/
#> Layer type: "Feature Layer"
#> Geometry type: "esriGeometryPolygon"
#> Service CRS: "EPSG:4269"
#> Output CRS: "EPSG:4326"
#>
#> Simple feature collection with 150 features and 5 fields
#> Geometry type: MULTIPOLYGON
#> Dimension: XY
#> Bounding box: xmin: -90.41814 ymin: 30.22331 xmax: -82.4184 ymax: 48.18953
#> Geodetic CRS: WGS 84
#> First 10 features:
#> STATE_NAME POP2000 POP2007 POP00_SQMI POP07_SQMI
#> 1 Alabama 43671 49541 72.3 82.0
#> 2 Alabama 140415 175513 84.9 106.1
#> 3 Alabama 29038 28992 32.1 32.1
#> 4 Alabama 20826 21911 33.3 35.0
#> 5 Alabama 51024 55496 78.4 85.3
#> 6 Alabama 11714 11519 18.7 18.4
#> 7 Alabama 21399 20888 27.5 26.9
#> 8 Alabama 112249 112267 183.3 183.3
#> 9 Alabama 36583 35245 60.7 58.4
#> 10 Alabama 23988 25160 40.0 41.9
#> geoms
#> 1 MULTIPOLYGON (((-86.90477 3...
#> 2 MULTIPOLYGON (((-88.0222 30...
#> 3 MULTIPOLYGON (((-85.74825 3...
#> 4 MULTIPOLYGON (((-87.4212 32...
#> 5 MULTIPOLYGON (((-86.96314 3...
#> 6 MULTIPOLYGON (((-85.9992 32...
#> 7 MULTIPOLYGON (((-86.90894 3...
#> 8 MULTIPOLYGON (((-86.14556 3...
#> 9 MULTIPOLYGON (((-85.59365 3...
#> 10 MULTIPOLYGON (((-85.84166 3...Since the addition of the WKT1_ESRI output from sf::st_crs() in sf
version 1.0-1, you can enter common CRS format (any that sf::st_crs()
can handle) into the crs parameters and it will be able to convert to
the ESRI formatted WKT needed for the outSR field in the REST query.
Below are two examples of the variety of input types that you can use
with the crs parameters.
# ESRI Authority Code
df1 <- esri2sf(url, where = where, outFields = outFields, crs = "ESRI:102690")
#> ── Downloading "Detailed Counties" from <https://sampleserver6.arcgisonline.com/
#> Layer type: "Feature Layer"
#> Geometry type: "esriGeometryPolygon"
#> Service CRS: "EPSG:4269"
#> Output CRS: "ESRI:102690"
#>
# OGC WKT
df2 <- esri2sf(url, where = where, outFields = outFields, crs = 'PROJCS["NAD_1983_StatePlane_Michigan_South_FIPS_2113_Feet",GEOGCS["GCS_North_American_1983",DATUM["North_American_Datum_1983",SPHEROID["GRS_1980",6378137,298.257222101]],PRIMEM["Greenwich",0],UNIT["Degree",0.017453292519943295]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["False_Easting",13123333.33333333],PARAMETER["False_Northing",0],PARAMETER["Central_Meridian",-84.36666666666666],PARAMETER["Standard_Parallel_1",42.1],PARAMETER["Standard_Parallel_2",43.66666666666666],PARAMETER["Latitude_Of_Origin",41.5],UNIT["Foot_US",0.30480060960121924],AUTHORITY["EPSG","102690"]]')
#> ── Downloading "Detailed Counties" from <https://sampleserver6.arcgisonline.com/
#> Layer type: "Feature Layer"
#> Geometry type: "esriGeometryPolygon"
#> Service CRS: "EPSG:4269"
#> Output CRS: "EPSG:102690"
#> Their similarity on the output CRS can be proven by the following function that calculates the mean difference in X-Y coordinates at each point. All are very close to 0.
coord_diff <- function(df1, df2) {
suppressWarnings({
c(
"x" = mean(sf::st_coordinates(sf::st_cast(df1, "POINT"))[, 1] - sf::st_coordinates(sf::st_cast(df2, "POINT"))[, 1]),
"y" = mean(sf::st_coordinates(sf::st_cast(df1, "POINT"))[, 2] - sf::st_coordinates(sf::st_cast(df2, "POINT"))[, 2])
)
})
}
coord_diff(df1, df2)
#> x y
#> 0 0The esriRequest() function has also made it easier to build new
functions for ArcGIS REST API services. esriCatalog() uses the
Catalog
endpoint
to return a list of folders and layers.
url <- "https://sampleserver6.arcgisonline.com/ArcGIS/rest/services"
esriCatalog(url)[1:5]
#> $currentVersion
#> [1] 10.91
#>
#> $folders
#> $folders[[1]]
#> [1] "AGP"
#>
#> $folders[[2]]
#> [1] "Elevation"
#>
#> $folders[[3]]
#> [1] "Energy"
#>
#> $folders[[4]]
#> [1] "LocalGovernment"
#>
#> $folders[[5]]
#> [1] "Locators"
#>
#> $folders[[6]]
#> [1] "NetworkAnalysis"
#>
#> $folders[[7]]
#> [1] "Oblique"
#>
#> $folders[[8]]
#> [1] "OsoLandslide"
#>
#> $folders[[9]]
#> [1] "ScientificData"
#>
#> $folders[[10]]
#> [1] "SpatioTemporalAggregation"
#>
#> $folders[[11]]
#> [1] "StoryMaps"
#>
#> $folders[[12]]
#> [1] "Sync"
#>
#> $folders[[13]]
#> [1] "Utilities"
#>
#>
#> $services
#> $services[[1]]
#> $services[[1]]$name
#> [1] "911CallsHotspot"
#>
#> $services[[1]]$type
#> [1] "GPServer"
#>
#>
#> $services[[2]]
#> $services[[2]]$name
#> [1] "911CallsHotspot"
#>
#> $services[[2]]$type
#> [1] "MapServer"
#>
#>
#> $services[[3]]
#> $services[[3]]$name
#> [1] "911CallsHotspotPro"
#>
#> $services[[3]]$type
#> [1] "GPServer"
#>
#>
#> $services[[4]]
#> $services[[4]]$name
#> [1] "Census"
#>
#> $services[[4]]$type
#> [1] "MapServer"
#>
#>
#> $services[[5]]
#> $services[[5]]$name
#> [1] "CharlotteLAS"
#>
#> $services[[5]]$type
#> [1] "ImageServer"
#>
#>
#> $services[[6]]
#> $services[[6]]$name
#> [1] "CommercialDamageAssessment"
#>
#> $services[[6]]$type
#> [1] "FeatureServer"
#>
#>
#> $services[[7]]
#> $services[[7]]$name
#> [1] "CommercialDamageAssessment"
#>
#> $services[[7]]$type
#> [1] "MapServer"
#>
#>
#> $services[[8]]
#> $services[[8]]$name
#> [1] "CommunityAddressing"
#>
#> $services[[8]]$type
#> [1] "FeatureServer"
#>
#>
#> $services[[9]]
#> $services[[9]]$name
#> [1] "CommunityAddressing"
#>
#> $services[[9]]$type
#> [1] "MapServer"
#>
#>
#> $services[[10]]
#> $services[[10]]$name
#> [1] "DamageAssessment"
#>
#> $services[[10]]$type
#> [1] "FeatureServer"
#>
#>
#> $services[[11]]
#> $services[[11]]$name
#> [1] "DamageAssessment"
#>
#> $services[[11]]$type
#> [1] "MapServer"
#>
#>
#> $services[[12]]
#> $services[[12]]$name
#> [1] "DamageAssessmentStatePlane"
#>
#> $services[[12]]$type
#> [1] "FeatureServer"
#>
#>
#> $services[[13]]
#> $services[[13]]$name
#> [1] "DamageAssessmentStatePlane"
#>
#> $services[[13]]$type
#> [1] "MapServer"
#>
#>
#> $services[[14]]
#> $services[[14]]$name
#> [1] "Earthquakes_Since1970"
#>
#> $services[[14]]$type
#> [1] "FeatureServer"
#>
#>
#> $services[[15]]
#> $services[[15]]$name
#> [1] "Earthquakes_Since1970"
#>
#> $services[[15]]$type
#> [1] "MapServer"
#>
#>
#> $services[[16]]
#> $services[[16]]$name
#> [1] "EmergencyFacilities"
#>
#> $services[[16]]$type
#> [1] "FeatureServer"
#>
#>
#> $services[[17]]
#> $services[[17]]$name
#> [1] "EmergencyFacilities"
#>
#> $services[[17]]$type
#> [1] "MapServer"
#>
#>
#> $services[[18]]
#> $services[[18]]$name
#> [1] "GDBVersions"
#>
#> $services[[18]]$type
#> [1] "GPServer"
#>
#>
#> $services[[19]]
#> $services[[19]]$name
#> [1] "Hurricanes"
#>
#> $services[[19]]$type
#> [1] "MapServer"
#>
#>
#> $services[[20]]
#> $services[[20]]$name
#> [1] "Military"
#>
#> $services[[20]]$type
#> [1] "FeatureServer"
#>
#>
#> $services[[21]]
#> $services[[21]]$name
#> [1] "Military"
#>
#> $services[[21]]$type
#> [1] "MapServer"
#>
#>
#> $services[[22]]
#> $services[[22]]$name
#> [1] "MontgomeryQuarters"
#>
#> $services[[22]]$type
#> [1] "MapServer"
#>
#>
#> $services[[23]]
#> $services[[23]]$name
#> [1] "MtBaldy_BaseMap"
#>
#> $services[[23]]$type
#> [1] "MapServer"
#>
#>
#> $services[[24]]
#> $services[[24]]$name
#> [1] "MultiDimensional_Sample"
#>
#> $services[[24]]$type
#> [1] "MapServer"
#>
#>
#> $services[[25]]
#> $services[[25]]$name
#> [1] "NapervilleShelters"
#>
#> $services[[25]]$type
#> [1] "FeatureServer"
#>
#>
#> $services[[26]]
#> $services[[26]]$name
#> [1] "NapervilleShelters"
#>
#> $services[[26]]$type
#> [1] "MapServer"
#>
#>
#> $services[[27]]
#> $services[[27]]$name
#> [1] "NLCDLandCover2001"
#>
#> $services[[27]]$type
#> [1] "ImageServer"
#>
#>
#> $services[[28]]
#> $services[[28]]$name
#> [1] "Notes"
#>
#> $services[[28]]$type
#> [1] "FeatureServer"
#>
#>
#> $services[[29]]
#> $services[[29]]$name
#> [1] "Notes"
#>
#> $services[[29]]$type
#> [1] "MapServer"
#>
#>
#> $services[[30]]
#> $services[[30]]$name
#> [1] "NYTimes_Covid19Cases_USCounties"
#>
#> $services[[30]]$type
#> [1] "MapServer"
#>
#>
#> $services[[31]]
#> $services[[31]]$name
#> [1] "OilSandsProjectBoundaries"
#>
#> $services[[31]]$type
#> [1] "FeatureServer"
#>
#>
#> $services[[32]]
#> $services[[32]]$name
#> [1] "OilSandsProjectBoundaries"
#>
#> $services[[32]]$type
#> [1] "MapServer"
#>
#>
#> $services[[33]]
#> $services[[33]]$name
#> [1] "OtherGeoprocessingServices"
#>
#> $services[[33]]$type
#> [1] "GPServer"
#>
#>
#> $services[[34]]
#> $services[[34]]$name
#> [1] "PhoneIncidents"
#>
#> $services[[34]]$type
#> [1] "FeatureServer"
#>
#>
#> $services[[35]]
#> $services[[35]]$name
#> [1] "PhoneIncidents"
#>
#> $services[[35]]$type
#> [1] "MapServer"
#>
#>
#> $services[[36]]
#> $services[[36]]$name
#> [1] "PoolPermits"
#>
#> $services[[36]]$type
#> [1] "FeatureServer"
#>
#>
#> $services[[37]]
#> $services[[37]]$name
#> [1] "PoolPermits"
#>
#> $services[[37]]$type
#> [1] "MapServer"
#>
#>
#> $services[[38]]
#> $services[[38]]$name
#> [1] "Precipitation"
#>
#> $services[[38]]$type
#> [1] "MapServer"
#>
#>
#> $services[[39]]
#> $services[[39]]$name
#> [1] "Recreation"
#>
#> $services[[39]]$type
#> [1] "FeatureServer"
#>
#>
#> $services[[40]]
#> $services[[40]]$name
#> [1] "Recreation"
#>
#> $services[[40]]$type
#> [1] "MapServer"
#>
#>
#> $services[[41]]
#> $services[[41]]$name
#> [1] "RedlandsEmergencyVehicles"
#>
#> $services[[41]]$type
#> [1] "FeatureServer"
#>
#>
#> $services[[42]]
#> $services[[42]]$name
#> [1] "RedlandsEmergencyVehicles"
#>
#> $services[[42]]$type
#> [1] "MapServer"
#>
#>
#> $services[[43]]
#> $services[[43]]$name
#> [1] "RiversAnnotation"
#>
#> $services[[43]]$type
#> [1] "FeatureServer"
#>
#>
#> $services[[44]]
#> $services[[44]]$name
#> [1] "RiversAnnotation"
#>
#> $services[[44]]$type
#> [1] "MapServer"
#>
#>
#> $services[[45]]
#> $services[[45]]$name
#> [1] "SampleWorldCities"
#>
#> $services[[45]]$type
#> [1] "MapServer"
#>
#>
#> $services[[46]]
#> $services[[46]]$name
#> [1] "ServiceRequest"
#>
#> $services[[46]]$type
#> [1] "FeatureServer"
#>
#>
#> $services[[47]]
#> $services[[47]]$name
#> [1] "ServiceRequest"
#>
#> $services[[47]]$type
#> [1] "MapServer"
#>
#>
#> $services[[48]]
#> $services[[48]]$name
#> [1] "SF311"
#>
#> $services[[48]]$type
#> [1] "FeatureServer"
#>
#>
#> $services[[49]]
#> $services[[49]]$name
#> [1] "SF311"
#>
#> $services[[49]]$type
#> [1] "MapServer"
#>
#>
#> $services[[50]]
#> $services[[50]]$name
#> [1] "Toronto"
#>
#> $services[[50]]$type
#> [1] "ImageServer"
#>
#>
#> $services[[51]]
#> $services[[51]]$name
#> [1] "USA"
#>
#> $services[[51]]$type
#> [1] "MapServer"
#>
#>
#> $services[[52]]
#> $services[[52]]$name
#> [1] "VerticalLines"
#>
#> $services[[52]]$type
#> [1] "FeatureServer"
#>
#>
#> $services[[53]]
#> $services[[53]]$name
#> [1] "VerticalLines"
#>
#> $services[[53]]$type
#> [1] "MapServer"
#>
#>
#> $services[[54]]
#> $services[[54]]$name
#> [1] "Viewshed"
#>
#> $services[[54]]$type
#> [1] "GPServer"
#>
#>
#> $services[[55]]
#> $services[[55]]$name
#> [1] "Water_Network_Base_Map"
#>
#> $services[[55]]$type
#> [1] "MapServer"
#>
#>
#> $services[[56]]
#> $services[[56]]$name
#> [1] "Water_Network"
#>
#> $services[[56]]$type
#> [1] "FeatureServer"
#>
#>
#> $services[[57]]
#> $services[[57]]$name
#> [1] "Water_Network"
#>
#> $services[[57]]$type
#> [1] "MapServer"
#>
#>
#> $services[[58]]
#> $services[[58]]$name
#> [1] "Wildfire"
#>
#> $services[[58]]$type
#> [1] "FeatureServer"
#>
#>
#> $services[[59]]
#> $services[[59]]$name
#> [1] "Wildfire"
#>
#> $services[[59]]$type
#> [1] "MapServer"
#>
#>
#> $services[[60]]
#> $services[[60]]$name
#> [1] "WindTurbines"
#>
#> $services[[60]]$type
#> [1] "MapServer"
#>
#>
#> $services[[61]]
#> $services[[61]]$name
#> [1] "World_Street_Map"
#>
#> $services[[61]]$type
#> [1] "MapServer"
#>
#>
#> $services[[62]]
#> $services[[62]]$name
#> [1] "WorldTimeZones"
#>
#> $services[[62]]$type
#> [1] "MapServer"
#>
#>
#>
#> $<NA>
#> NULL
#>
#> $<NA>
#> NULLesriIndex() wraps esriCatalog() but returns a data frame with added
columns to differentiate between folder, service, and layer URLs.
esriIndex(url)
#> # A tibble: 75 × 5
#> name type url urlType serviceType
#> <chr> <chr> <chr> <chr> <chr>
#> 1 AGP <NA> https://sampleserver6.ar… folder <NA>
#> 2 Elevation <NA> https://sampleserver6.ar… folder <NA>
#> 3 Energy <NA> https://sampleserver6.ar… folder <NA>
#> 4 LocalGovernment <NA> https://sampleserver6.ar… folder <NA>
#> 5 Locators <NA> https://sampleserver6.ar… folder <NA>
#> 6 NetworkAnalysis <NA> https://sampleserver6.ar… folder <NA>
#> 7 Oblique <NA> https://sampleserver6.ar… folder <NA>
#> 8 OsoLandslide <NA> https://sampleserver6.ar… folder <NA>
#> 9 ScientificData <NA> https://sampleserver6.ar… folder <NA>
#> 10 SpatioTemporalAggregation <NA> https://sampleserver6.ar… folder <NA>
#> # ℹ 65 more rowsSet recurse = TRUE to loop through folders and ensure the data frame
includes all available services.
esriIndex(url, recurse = TRUE)Similarly, the new esrigeocode() provides support for the Find
Address
Candidates
and Reverse
Geocode
REST APIs.
url <- "https://geodata.baltimorecity.gov/egis/rest/services/Locator/EGISCompositeLocator/GeocodeServer"
esrigeocode(url, address = "100 HOLLIDAY STREET")
#> Simple feature collection with 1 feature and 2 fields
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: -76.61032 ymin: 39.29052 xmax: -76.61032 ymax: 39.29052
#> Geodetic CRS: WGS 84
#> address score geometry
#> 1 100 HOLLIDAY ST 100 POINT (-76.61032 39.29052)- {arcgisbinding} and the R-ArcGIS Bridge
- {arcpullr}: Functions for pulling spatial data from an ArcGIS REST API and formatting those layers into either sf or Raster* objects.
- {geosapi}: GeoServer REST API R Interface
- {aarapir}: Access ArcGIS online API endpoints with R
- {RPyGeo}
- esri-dump: A Node module to assist with pulling data out of an ESRI ArcGIS REST server into GeoJSON.
- pyesridump: Scrapes an ESRI MapServer REST endpoint to spit out more generally-usable geodata.
- Geocoding Addresses with the ArcGIS REST API (Stanford Affiliates Only)
- All things R Spatial: An introduction to spatial R for ArcGIS users (repo)
- ArcRasterRescue: Extract raster data from ArcGIS/ESRI formats.