Simplifying polygons in rgeos and maintaining data in SpatialPolygonsDataFrameHow to attach a simple data.frame to a SpatialPolygonDataFrame in R?gSimplify not simplifying shapefile in RHow to join (merge) data frames (inner, outer, left, right)Drop data frame columns by nameHow to create new polygons by simplifying from two SpatialPolygonsDataFrame objects in R?Simple way to subset SpatialPolygonsDataFrame (i.e. delete polygons) by attribute in RRGeo Projected Buffer Polygon too smallLoop polygon clipping with gIntersectionVariant of rgeos::gUnion that won't dissolve adjacent polygons?Value of coordinates() for a SpatialPolygonsDataFrame object?Remove certain polygons from SpatialPolygonsDataFrameMerge data frame with SpatialPolygonsDataFrame
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Simplifying polygons in rgeos and maintaining data in SpatialPolygonsDataFrame
How to attach a simple data.frame to a SpatialPolygonDataFrame in R?gSimplify not simplifying shapefile in RHow to join (merge) data frames (inner, outer, left, right)Drop data frame columns by nameHow to create new polygons by simplifying from two SpatialPolygonsDataFrame objects in R?Simple way to subset SpatialPolygonsDataFrame (i.e. delete polygons) by attribute in RRGeo Projected Buffer Polygon too smallLoop polygon clipping with gIntersectionVariant of rgeos::gUnion that won't dissolve adjacent polygons?Value of coordinates() for a SpatialPolygonsDataFrame object?Remove certain polygons from SpatialPolygonsDataFrameMerge data frame with SpatialPolygonsDataFrame
.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty margin-bottom:0;
Background
I'm interested in simplifying polygons with use of the gSimplify function available through the rgeos package.
Reproducible example
A reproducible example can be generated with use of the code below:
# Data sourcing -----------------------------------------------------------
# Download an read US state shapefiles
tmp_shps <- tempfile()
tmp_dir <- tempdir()
download.file(
"http://www2.census.gov/geo/tiger/GENZ2014/shp/cb_2014_us_state_20m.zip",
tmp_shps
)
unzip(tmp_shps, exdir = tmp_dir)
# Libs
require(rgdal)
require(rgeos)
# Read
us_shps <- readOGR(dsn = tmp_dir, layer = "cb_2014_us_state_20m")
# Simplified --------------------------------------------------------------
# Simplifiy
us_shps_smpl <- gSimplify(spgeom = us_shps,
tol = 200,
topologyPreserve = TRUE)
Preview
par(mfrow = c(2,1))
plot(us_shps_smpl, main = "Simplified")
plot(us_shps, main = "Original")
Problem
In addittion to simplifying polygons the gSimplify function changed classes of the resulting object:
>> class(us_shps)
[1] "SpatialPolygonsDataFrame"
attr(,"package")
[1] "sp"
>> class(us_shps_smpl)
[1] "SpatialPolygons"
attr(,"package")
[1] "sp"
>> names(us_shps)
[1] "STATEFP" "STATENS" "AFFGEOID" "GEOID" "STUSPS" "NAME" "LSAD" "ALAND" "AWATER"
>> names(us_shps_smpl)
[1] "0" "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12" "13" "14" "15" "16" "17" "18" "19"
[21] "20" "21" "22" "23" "24" "25" "26" "27" "28" "29" "30" "31" "32" "33" "34" "35" "36" "37" "38" "39"
[41] "40" "41" "42" "43" "44" "45" "46" "47" "48" "49" "50" "51"
Questions
How can I safely reattached the data that was initially available in the original object and transform the resulting
SpatialPolygonsobject to aSpatialPolygonsDataFrameI reckon that one approach would simply involve attaching data frame;but this depends on the order of elements not changing. Are there any other better approaches (ideally preserving initial object class)?
r gis spatial sp rgeo
asked Sep 5 '17 at 14:17
KonradKonrad
8,24310 gold badges58 silver badges109 bronze badges
|
show 4 more comments
Background
I'm interested in simplifying polygons with use of the gSimplify function available through the rgeos package.
Reproducible example
A reproducible example can be generated with use of the code below:
# Data sourcing -----------------------------------------------------------
# Download an read US state shapefiles
tmp_shps <- tempfile()
tmp_dir <- tempdir()
download.file(
"http://www2.census.gov/geo/tiger/GENZ2014/shp/cb_2014_us_state_20m.zip",
tmp_shps
)
unzip(tmp_shps, exdir = tmp_dir)
# Libs
require(rgdal)
require(rgeos)
# Read
us_shps <- readOGR(dsn = tmp_dir, layer = "cb_2014_us_state_20m")
# Simplified --------------------------------------------------------------
# Simplifiy
us_shps_smpl <- gSimplify(spgeom = us_shps,
tol = 200,
topologyPreserve = TRUE)
Preview
par(mfrow = c(2,1))
plot(us_shps_smpl, main = "Simplified")
plot(us_shps, main = "Original")
Problem
In addittion to simplifying polygons the gSimplify function changed classes of the resulting object:
>> class(us_shps)
[1] "SpatialPolygonsDataFrame"
attr(,"package")
[1] "sp"
>> class(us_shps_smpl)
[1] "SpatialPolygons"
attr(,"package")
[1] "sp"
>> names(us_shps)
[1] "STATEFP" "STATENS" "AFFGEOID" "GEOID" "STUSPS" "NAME" "LSAD" "ALAND" "AWATER"
>> names(us_shps_smpl)
[1] "0" "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12" "13" "14" "15" "16" "17" "18" "19"
[21] "20" "21" "22" "23" "24" "25" "26" "27" "28" "29" "30" "31" "32" "33" "34" "35" "36" "37" "38" "39"
[41] "40" "41" "42" "43" "44" "45" "46" "47" "48" "49" "50" "51"
Questions
How can I safely reattached the data that was initially available in the original object and transform the resulting
SpatialPolygonsobject to aSpatialPolygonsDataFrameI reckon that one approach would simply involve attaching data frame;but this depends on the order of elements not changing. Are there any other better approaches (ideally preserving initial object class)?
r gis spatial sp rgeo
asked Sep 5 '17 at 14:17
KonradKonrad
8,24310 gold badges58 silver badges109 bronze badges
gis.stackexchange.com they can help you for surely
– Andre Elrico
Sep 5 '17 at 14:24
@AndreElrico I post on gis periodically but to my mind this question is more concerned with how the thegSimplifyhandlesSpatialPolygonDataFrameclass, less with quantitative geography aspect of the problem. I reckon it's not a clear cut but I presume that a lot of people who follow rgeos and gis look at both boards.
– Konrad
Sep 5 '17 at 14:27
1
just wanted to make sure you're aware of that site :-)
– Andre Elrico
Sep 5 '17 at 14:28
1
Answere here may be of relevance.
– Z.Lin
Sep 5 '17 at 14:34
1
Are you wedded torgeos? Otherwise, I believesf::st_simplify()could help you out here.
– coletl
Oct 9 '17 at 8:55
|
show 4 more comments
Background
I'm interested in simplifying polygons with use of the gSimplify function available through the rgeos package.
Reproducible example
A reproducible example can be generated with use of the code below:
# Data sourcing -----------------------------------------------------------
# Download an read US state shapefiles
tmp_shps <- tempfile()
tmp_dir <- tempdir()
download.file(
"http://www2.census.gov/geo/tiger/GENZ2014/shp/cb_2014_us_state_20m.zip",
tmp_shps
)
unzip(tmp_shps, exdir = tmp_dir)
# Libs
require(rgdal)
require(rgeos)
# Read
us_shps <- readOGR(dsn = tmp_dir, layer = "cb_2014_us_state_20m")
# Simplified --------------------------------------------------------------
# Simplifiy
us_shps_smpl <- gSimplify(spgeom = us_shps,
tol = 200,
topologyPreserve = TRUE)
Preview
par(mfrow = c(2,1))
plot(us_shps_smpl, main = "Simplified")
plot(us_shps, main = "Original")
Problem
In addittion to simplifying polygons the gSimplify function changed classes of the resulting object:
>> class(us_shps)
[1] "SpatialPolygonsDataFrame"
attr(,"package")
[1] "sp"
>> class(us_shps_smpl)
[1] "SpatialPolygons"
attr(,"package")
[1] "sp"
>> names(us_shps)
[1] "STATEFP" "STATENS" "AFFGEOID" "GEOID" "STUSPS" "NAME" "LSAD" "ALAND" "AWATER"
>> names(us_shps_smpl)
[1] "0" "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12" "13" "14" "15" "16" "17" "18" "19"
[21] "20" "21" "22" "23" "24" "25" "26" "27" "28" "29" "30" "31" "32" "33" "34" "35" "36" "37" "38" "39"
[41] "40" "41" "42" "43" "44" "45" "46" "47" "48" "49" "50" "51"
Questions
How can I safely reattached the data that was initially available in the original object and transform the resulting
SpatialPolygonsobject to aSpatialPolygonsDataFrameI reckon that one approach would simply involve attaching data frame;but this depends on the order of elements not changing. Are there any other better approaches (ideally preserving initial object class)?
r gis spatial sp rgeo
asked Sep 5 '17 at 14:17
KonradKonrad
8,24310 gold badges58 silver badges109 bronze badges
Background
I'm interested in simplifying polygons with use of the gSimplify function available through the rgeos package.
Reproducible example
A reproducible example can be generated with use of the code below:
# Data sourcing -----------------------------------------------------------
# Download an read US state shapefiles
tmp_shps <- tempfile()
tmp_dir <- tempdir()
download.file(
"http://www2.census.gov/geo/tiger/GENZ2014/shp/cb_2014_us_state_20m.zip",
tmp_shps
)
unzip(tmp_shps, exdir = tmp_dir)
# Libs
require(rgdal)
require(rgeos)
# Read
us_shps <- readOGR(dsn = tmp_dir, layer = "cb_2014_us_state_20m")
# Simplified --------------------------------------------------------------
# Simplifiy
us_shps_smpl <- gSimplify(spgeom = us_shps,
tol = 200,
topologyPreserve = TRUE)
Preview
par(mfrow = c(2,1))
plot(us_shps_smpl, main = "Simplified")
plot(us_shps, main = "Original")
Problem
In addittion to simplifying polygons the gSimplify function changed classes of the resulting object:
>> class(us_shps)
[1] "SpatialPolygonsDataFrame"
attr(,"package")
[1] "sp"
>> class(us_shps_smpl)
[1] "SpatialPolygons"
attr(,"package")
[1] "sp"
>> names(us_shps)
[1] "STATEFP" "STATENS" "AFFGEOID" "GEOID" "STUSPS" "NAME" "LSAD" "ALAND" "AWATER"
>> names(us_shps_smpl)
[1] "0" "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12" "13" "14" "15" "16" "17" "18" "19"
[21] "20" "21" "22" "23" "24" "25" "26" "27" "28" "29" "30" "31" "32" "33" "34" "35" "36" "37" "38" "39"
[41] "40" "41" "42" "43" "44" "45" "46" "47" "48" "49" "50" "51"
Questions
How can I safely reattached the data that was initially available in the original object and transform the resulting
SpatialPolygonsobject to aSpatialPolygonsDataFrameI reckon that one approach would simply involve attaching data frame;but this depends on the order of elements not changing. Are there any other better approaches (ideally preserving initial object class)?
r gis spatial sp rgeo
r gis spatial sp rgeo
asked Sep 5 '17 at 14:17
KonradKonrad
8,24310 gold badges58 silver badges109 bronze badges
asked Sep 5 '17 at 14:17
KonradKonrad
8,24310 gold badges58 silver badges109 bronze badges
asked Sep 5 '17 at 14:17
KonradKonrad
8,24310 gold badges58 silver badges109 bronze badges
asked Sep 5 '17 at 14:17
KonradKonrad
8,24310 gold badges58 silver badges109 bronze badges
asked Sep 5 '17 at 14:17
KonradKonrad
8,24310 gold badges58 silver badges109 bronze badges
8,24310 gold badges58 silver badges109 bronze badges
gis.stackexchange.com they can help you for surely
– Andre Elrico
Sep 5 '17 at 14:24
@AndreElrico I post on gis periodically but to my mind this question is more concerned with how the thegSimplifyhandlesSpatialPolygonDataFrameclass, less with quantitative geography aspect of the problem. I reckon it's not a clear cut but I presume that a lot of people who follow rgeos and gis look at both boards.
– Konrad
Sep 5 '17 at 14:27
1
just wanted to make sure you're aware of that site :-)
– Andre Elrico
Sep 5 '17 at 14:28
1
Answere here may be of relevance.
– Z.Lin
Sep 5 '17 at 14:34
1
Are you wedded torgeos? Otherwise, I believesf::st_simplify()could help you out here.
– coletl
Oct 9 '17 at 8:55
|
show 4 more comments
gis.stackexchange.com they can help you for surely
– Andre Elrico
Sep 5 '17 at 14:24
@AndreElrico I post on gis periodically but to my mind this question is more concerned with how the thegSimplifyhandlesSpatialPolygonDataFrameclass, less with quantitative geography aspect of the problem. I reckon it's not a clear cut but I presume that a lot of people who follow rgeos and gis look at both boards.
– Konrad
Sep 5 '17 at 14:27
1
just wanted to make sure you're aware of that site :-)
– Andre Elrico
Sep 5 '17 at 14:28
1
Answere here may be of relevance.
– Z.Lin
Sep 5 '17 at 14:34
1
Are you wedded torgeos? Otherwise, I believesf::st_simplify()could help you out here.
– coletl
Oct 9 '17 at 8:55
gis.stackexchange.com they can help you for surely
– Andre Elrico
Sep 5 '17 at 14:24
gis.stackexchange.com they can help you for surely
– Andre Elrico
Sep 5 '17 at 14:24
@AndreElrico I post on gis periodically but to my mind this question is more concerned with how the the
gSimplify handles SpatialPolygonDataFrame class, less with quantitative geography aspect of the problem. I reckon it's not a clear cut but I presume that a lot of people who follow rgeos and gis look at both boards.– Konrad
Sep 5 '17 at 14:27
@AndreElrico I post on gis periodically but to my mind this question is more concerned with how the the
gSimplify handles SpatialPolygonDataFrame class, less with quantitative geography aspect of the problem. I reckon it's not a clear cut but I presume that a lot of people who follow rgeos and gis look at both boards.– Konrad
Sep 5 '17 at 14:27
1
1
just wanted to make sure you're aware of that site :-)
– Andre Elrico
Sep 5 '17 at 14:28
just wanted to make sure you're aware of that site :-)
– Andre Elrico
Sep 5 '17 at 14:28
1
1
Answere here may be of relevance.
– Z.Lin
Sep 5 '17 at 14:34
Answere here may be of relevance.
– Z.Lin
Sep 5 '17 at 14:34
1
1
Are you wedded to
rgeos? Otherwise, I believe sf::st_simplify() could help you out here.– coletl
Oct 9 '17 at 8:55
Are you wedded to
rgeos? Otherwise, I believe sf::st_simplify() could help you out here.– coletl
Oct 9 '17 at 8:55
|
show 4 more comments
1 Answer
1
active
oldest
votes
The sf package is based entirely on data frames, so its geometry manipulations always preserve the data attached to each feature. The package hasn't caught up with all the standard spatial packages in R yet, but it's fairly easy to go back and forth between sf and sp objects when you need more functionality.
Here, st_simplify() does the work, but you'll need to project your polygons first:
library(sf)
# Download and read example data
tmp_shps <- tempfile()
tmp_dir <- tempdir()
download.file(
"http://www2.census.gov/geo/tiger/GENZ2014/shp/cb_2014_us_state_20m.zip",
tmp_shps
)
unzip(tmp_shps, exdir = tmp_dir)
us_shps <- st_read(paste(tmp_dir, "cb_2014_us_state_20m.shp", sep = "/"))
# st_simplify needs a projected CRS
us_shps_merc <- st_transform(us_shps, 3857)
simple_us_merc <- st_simplify(us_shps_merc)
# Change back to original CRS
simple_us <- st_transform(simple_us_merc, st_crs(us_shps))
# Change to sp object, if you like
simple_us_sp <- as(st_zm(simple_us), "Spatial")
answered Oct 9 '17 at 9:12
coletlcoletl
6273 silver badges15 bronze badges
i found that if st_simplify drops some polygons, the geometry column will become an empty list in those rows ("list()"). those "empty geometry" rows will have to be removed before as(.,"Spatial") is applied or an error appears
– Richard DiSalvo
Mar 27 at 2:41
add a comment |
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The sf package is based entirely on data frames, so its geometry manipulations always preserve the data attached to each feature. The package hasn't caught up with all the standard spatial packages in R yet, but it's fairly easy to go back and forth between sf and sp objects when you need more functionality.
Here, st_simplify() does the work, but you'll need to project your polygons first:
library(sf)
# Download and read example data
tmp_shps <- tempfile()
tmp_dir <- tempdir()
download.file(
"http://www2.census.gov/geo/tiger/GENZ2014/shp/cb_2014_us_state_20m.zip",
tmp_shps
)
unzip(tmp_shps, exdir = tmp_dir)
us_shps <- st_read(paste(tmp_dir, "cb_2014_us_state_20m.shp", sep = "/"))
# st_simplify needs a projected CRS
us_shps_merc <- st_transform(us_shps, 3857)
simple_us_merc <- st_simplify(us_shps_merc)
# Change back to original CRS
simple_us <- st_transform(simple_us_merc, st_crs(us_shps))
# Change to sp object, if you like
simple_us_sp <- as(st_zm(simple_us), "Spatial")
answered Oct 9 '17 at 9:12
coletlcoletl
6273 silver badges15 bronze badges
i found that if st_simplify drops some polygons, the geometry column will become an empty list in those rows ("list()"). those "empty geometry" rows will have to be removed before as(.,"Spatial") is applied or an error appears
– Richard DiSalvo
Mar 27 at 2:41
add a comment |
The sf package is based entirely on data frames, so its geometry manipulations always preserve the data attached to each feature. The package hasn't caught up with all the standard spatial packages in R yet, but it's fairly easy to go back and forth between sf and sp objects when you need more functionality.
Here, st_simplify() does the work, but you'll need to project your polygons first:
library(sf)
# Download and read example data
tmp_shps <- tempfile()
tmp_dir <- tempdir()
download.file(
"http://www2.census.gov/geo/tiger/GENZ2014/shp/cb_2014_us_state_20m.zip",
tmp_shps
)
unzip(tmp_shps, exdir = tmp_dir)
us_shps <- st_read(paste(tmp_dir, "cb_2014_us_state_20m.shp", sep = "/"))
# st_simplify needs a projected CRS
us_shps_merc <- st_transform(us_shps, 3857)
simple_us_merc <- st_simplify(us_shps_merc)
# Change back to original CRS
simple_us <- st_transform(simple_us_merc, st_crs(us_shps))
# Change to sp object, if you like
simple_us_sp <- as(st_zm(simple_us), "Spatial")
answered Oct 9 '17 at 9:12
coletlcoletl
6273 silver badges15 bronze badges
i found that if st_simplify drops some polygons, the geometry column will become an empty list in those rows ("list()"). those "empty geometry" rows will have to be removed before as(.,"Spatial") is applied or an error appears
– Richard DiSalvo
Mar 27 at 2:41
add a comment |
The sf package is based entirely on data frames, so its geometry manipulations always preserve the data attached to each feature. The package hasn't caught up with all the standard spatial packages in R yet, but it's fairly easy to go back and forth between sf and sp objects when you need more functionality.
Here, st_simplify() does the work, but you'll need to project your polygons first:
library(sf)
# Download and read example data
tmp_shps <- tempfile()
tmp_dir <- tempdir()
download.file(
"http://www2.census.gov/geo/tiger/GENZ2014/shp/cb_2014_us_state_20m.zip",
tmp_shps
)
unzip(tmp_shps, exdir = tmp_dir)
us_shps <- st_read(paste(tmp_dir, "cb_2014_us_state_20m.shp", sep = "/"))
# st_simplify needs a projected CRS
us_shps_merc <- st_transform(us_shps, 3857)
simple_us_merc <- st_simplify(us_shps_merc)
# Change back to original CRS
simple_us <- st_transform(simple_us_merc, st_crs(us_shps))
# Change to sp object, if you like
simple_us_sp <- as(st_zm(simple_us), "Spatial")
answered Oct 9 '17 at 9:12
coletlcoletl
6273 silver badges15 bronze badges
The sf package is based entirely on data frames, so its geometry manipulations always preserve the data attached to each feature. The package hasn't caught up with all the standard spatial packages in R yet, but it's fairly easy to go back and forth between sf and sp objects when you need more functionality.
Here, st_simplify() does the work, but you'll need to project your polygons first:
library(sf)
# Download and read example data
tmp_shps <- tempfile()
tmp_dir <- tempdir()
download.file(
"http://www2.census.gov/geo/tiger/GENZ2014/shp/cb_2014_us_state_20m.zip",
tmp_shps
)
unzip(tmp_shps, exdir = tmp_dir)
us_shps <- st_read(paste(tmp_dir, "cb_2014_us_state_20m.shp", sep = "/"))
# st_simplify needs a projected CRS
us_shps_merc <- st_transform(us_shps, 3857)
simple_us_merc <- st_simplify(us_shps_merc)
# Change back to original CRS
simple_us <- st_transform(simple_us_merc, st_crs(us_shps))
# Change to sp object, if you like
simple_us_sp <- as(st_zm(simple_us), "Spatial")
answered Oct 9 '17 at 9:12
coletlcoletl
6273 silver badges15 bronze badges
edited Mar 27 at 2:49
answered Oct 9 '17 at 9:12
coletlcoletl
6273 silver badges15 bronze badges
answered Oct 9 '17 at 9:12
coletlcoletl
6273 silver badges15 bronze badges
answered Oct 9 '17 at 9:12
coletlcoletl
6273 silver badges15 bronze badges
6273 silver badges15 bronze badges
i found that if st_simplify drops some polygons, the geometry column will become an empty list in those rows ("list()"). those "empty geometry" rows will have to be removed before as(.,"Spatial") is applied or an error appears
– Richard DiSalvo
Mar 27 at 2:41
add a comment |
i found that if st_simplify drops some polygons, the geometry column will become an empty list in those rows ("list()"). those "empty geometry" rows will have to be removed before as(.,"Spatial") is applied or an error appears
– Richard DiSalvo
Mar 27 at 2:41
i found that if st_simplify drops some polygons, the geometry column will become an empty list in those rows ("list()"). those "empty geometry" rows will have to be removed before as(.,"Spatial") is applied or an error appears
– Richard DiSalvo
Mar 27 at 2:41
i found that if st_simplify drops some polygons, the geometry column will become an empty list in those rows ("list()"). those "empty geometry" rows will have to be removed before as(.,"Spatial") is applied or an error appears
– Richard DiSalvo
Mar 27 at 2:41
add a comment |
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gis.stackexchange.com they can help you for surely
– Andre Elrico
Sep 5 '17 at 14:24
@AndreElrico I post on gis periodically but to my mind this question is more concerned with how the the
gSimplifyhandlesSpatialPolygonDataFrameclass, less with quantitative geography aspect of the problem. I reckon it's not a clear cut but I presume that a lot of people who follow rgeos and gis look at both boards.– Konrad
Sep 5 '17 at 14:27
1
just wanted to make sure you're aware of that site :-)
– Andre Elrico
Sep 5 '17 at 14:28
1
Answere here may be of relevance.
– Z.Lin
Sep 5 '17 at 14:34
1
Are you wedded to
rgeos? Otherwise, I believesf::st_simplify()could help you out here.– coletl
Oct 9 '17 at 8:55