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I want to show 15 mile radius circles around points in a map using gBuffer. As far as I can tell I have the points and the map in the same projection, but when I produce the circles on the map, they are too large. Here is my code. The tigerline files for the state and counties can be found at https://www.census.gov/cgi-bin/geo/shapefiles/index.php.
library(tidyverse)
library(rgdal)
library(rgeos)
library(ggplot2)
state <- readOGR('C:\\Users\\Mesonet\\Desktop\\map_folder\\tl_2020_us_state\\tl_2020_us_state.shp')
state <- state[which(state$STATEFP == '46'),]
state <- spTransform(state, CRS("+init=epsg:3857"))
counties <- readOGR('C:\\Users\\Mesonet\\Desktop\\map_folder\\tl_2020_us_county\\tl_2020_us_county.shp')
counties <- counties[which(counties$STATEFP == '46'),]
counties <- spTransform(counties, CRS("+init=epsg:3857"))
sites <- data.frame(Lon = c(-98.1096,-98.27935), Lat = c(43.9029, 43.717258))
coordinates(sites) <- ~Lon + Lat
proj4string(sites) <- CRS("+proj=longlat")
sites <- spTransform(sites, CRS = CRS("+init=epsg:3857"))
# Miles to meters conversion
mile2meter <- function(x){x * 1609.344}
# Buffer creation
site_buffer <- gBuffer(sites, width = mile2meter(15))
png('C:\\Users\\Mesonet\\Desktop\\map_folder\\new_test.png', height = 3000, width = 42*100, res = 100)
ggplot() + geom_path(counties, mapping = aes(x = long, y = lat, group = group), size = 1.75,
alpha = 0.45, col = 'darkgreen') + geom_path(state, mapping = aes(x = long, y = lat, group =
group), size = 0.8) + theme(axis.text = element_blank()) + geom_polygon(site_buffer, mapping
= aes(x = long, y = lat, group = group), fill = '#0000FF', alpha = 1, size = 2)
dev.off()
These two locations are 15.35 miles apart, but the plot shows two circles that overlap each other by a couple miles. I can't figure out why, since from what I can see everything is in the same projection, but I might be wrong. Thank you.
I have a table containing all the latitudes and longitudes of some locations in a city called queryResult and I do the following:
1 - Get the Raster map of the city[Blackpool for instance]
cityMapRaster = get_map(location = 'Blackpool', zoom = 12, source = 'google', maptype = 'roadmap')
dataToShow <- ggmap(cityMapRaster) + geom_point(aes(x = Longitude, y = Latitude), data = queryResult, alpha = .5, color = "darkred", size = 1)
print(dataToShow)
and this will return the following points on the map
Now I want to draw the outer boundary [city border line] of all these latitude and longitudes similar to the following expected result
Update 1 : Providing input data and applying suggested ahull solution:
ggmap(cityMapRaster) + geom_point(aes(x = Longitude, y = Latitude), data = queryResult, alpha = .5, color = "darkred") + ahull.gg
I applied the ahull solution suggested by #spacedman and #cuttlefish44 and got the following result which is far different than the expected polygon:
You can download the .csv file containing all latitudes and longitudes from the following link : Blackpool Lat,Lon
Googles suggested area boundary looks like the following :
If you don't want a simple convex hull (and the polygon you've drawn is far from convex) then look at alpha-shapes in the alphahull package.
I wrote an example of how to get a polygon from an alpha-shape using that package and some points that make up a complex Norway boundary:
http://rpubs.com/geospacedman/alphasimple
You should be able to follow that to get a polygon for your data, and it might even be simpler now since that was a few years ago.
Here's a reproducible example of how to use chull to calculate a convex hull solution to this. I just generate some random points for queryResult, as you did not provide data.
If you prefer a concave hull boundary, then see the answer from #Spacedman
library(ggmap)
cityMapRaster = get_map(location = 'Blackpool', zoom = 12, source = 'google', maptype = 'roadmap')
extent = attr(cityMapRaster, "bb")
queryResult = data.frame(Longitude = rnorm(200, as.numeric(extent[2] + extent[4])/2, 0.01),
Latitude = rnorm(200, as.numeric(extent[1] + extent[3])/2, 0.02))
boundary = chull(as.matrix(queryResult))
ggmap(cityMapRaster) +
geom_point(aes(x = Longitude, y = Latitude),
data = queryResult, alpha = .5, color = "darkred", size = 2) +
geom_path(aes(x = Longitude, y = Latitude), data = queryResult[c(boundary, boundary[1]),])
I suppose queryResult is x and y datasets. As far as I see, your boundary isn't convex hull, so I used alphahull package.
## example `queryResult`
set.seed(1)
df <- data.frame(Longitude = runif(200, -3.05, -2.97), Latitude = rnorm(200, 53.82, 0.02))
library(alphahull)
ahull.obj <- ahull(df, alpha = 0.03)
plot(ahull.obj) # to check
# ahull_track() returns the output as a list of geom_path objs
ahull.gg <- ahull_track(df, alpha=0.03, nps = 1000)
## change graphic param
for(i in 1:length(ahull.gg)) ahull.gg[[i]]$aes_params$colour <- "green3"
ggmap(cityMapRaster) +
geom_point(aes(x = Longitude, y = Latitude), data = df, alpha = .5, color = "darkred") +
ahull.gg
## if you like not curve but linear
ashape.obj <- ashape(df, alpha = 0.015)
plot(ashape.obj) # to check
ashape.df <- as.data.frame(ashape.obj$edge[,c("x1", "x2", "y1", "y2")])
ggmap(cityMapRaster) +
geom_point(aes(x = Longitude, y = Latitude), data = df, alpha = .5, color = "darkred") +
geom_segment(aes(x = x1, y = y1, xend = x2, yend = y2), data = ashape.df, colour="green3", alpha=0.8)
I have a series of co-ordinates from which I have sampled data, here is an example of it on a map:
library(ggplot2)
library(ggmap)
library(dismo)
lon <- c(-64.723946, -64.723754, -64.723808, -64.724004)
lat <- c(32.350843, 32.350783, 32.350618, 32.350675)
df <- as.data.frame(cbind(lon,lat))
mapgilbert <- get_map(location = c(lon = mean(df$lon), lat = mean(df$lat)), zoom = 18, maptype = "satellite", scale = 2)
ggmap(mapgilbert) +
geom_point(data = df, aes(x = lon, y = lat, fill = "red", alpha = 0.8), size = 5, shape = 21) +
guides(fill=FALSE, alpha=FALSE, size=FALSE) +
scale_x_continuous(limits = c(-64.725, -64.723), expand = c(0,0)) +
scale_y_continuous(limits = c(32.350, 32.351), expand = c(0,0))
Here is the image this produces:
I want to draw lines between the north and south, and east and west points on the map - to make a sort of plus sign.
BUT I want this line to comprise points rather than just be a line, so I need to calculate the coordinates of the points. The lines are approximately thirty metres and I require a point every metre. I feel like the sp package might allow something like this but I can't figure out how.
Thanks,
Kez
Rearrange your your dataframe; all you really need is seq. Here Hadley-style, but build as manually as you prefer:
library(dplyr)
library(tidyr)
# group rows by opposite pairs
df2 <- df %>% group_by(group = lon %in% range(lon)) %>%
# summarize lat and lon for each group into a list of a sequence from the first to the second
summarise_each(funs(list(seq(.[1], .[2], length.out = 10)))) %>%
# expand list columns with tidyr::unnest
unnest()
head(df2)
# Source: local data frame [6 x 3]
#
# group lon lat
# (lgl) (dbl) (dbl)
# 1 FALSE -64.72395 32.35084
# 2 FALSE -64.72393 32.35082
# 3 FALSE -64.72392 32.35079
# 4 FALSE -64.72390 32.35077
# 5 FALSE -64.72388 32.35074
# 6 FALSE -64.72387 32.35072
# all I changed here is data = df2
mapgilbert <- get_map(location = c(lon = mean(df$lon), lat = mean(df$lat)), zoom = 18, maptype = "satellite", scale = 2)
ggmap(mapgilbert) +
geom_point(data = df2, aes(x = lon, y = lat, fill = "red", alpha = 0.8), size = 5, shape = 21) +
guides(fill=FALSE, alpha=FALSE, size=FALSE) +
scale_x_continuous(limits = c(-64.725, -64.723), expand = c(0,0)) +
scale_y_continuous(limits = c(32.350, 32.351), expand = c(0,0))
I have a map with the 8 points plotted on it:
library(ggplot2)
library(ggmap)
data = data.frame(
ID = as.numeric(c(1:8)),
longitude = as.numeric(c(-63.27462, -63.26499, -63.25658, -63.2519, -63.2311, -63.2175, -63.23623, -63.25958)),
latitude = as.numeric(c(17.6328, 17.64614, 17.64755, 17.64632, 17.64888, 17.63113, 17.61252, 17.62463))
)
island = get_map(location = c(lon = -63.247593, lat = 17.631598), zoom = 13, maptype = "satellite")
islandMap = ggmap(island, extent = "panel", legend = "bottomright")
RL = geom_point(aes(x = longitude, y = latitude), data = data, color = "#ff0000")
islandMap + RL + scale_x_continuous(limits = c(-63.280, -63.21), expand = c(0, 0)) + scale_y_continuous(limits = c(17.605, 17.66), expand = c(0, 0))
Now I want to plot a circle around each of the 8 plotted locations. The circle has to have a radius of 450 meters.
This is what I mean, but then using ggplot: https://gis.stackexchange.com/questions/119736/ggmap-create-circle-symbol-where-radius-represents-distance-miles-or-km
How can I achieve this?
If you only work on a small area of the earth, here is a approximation. Each degree of the latitude represents 40075 / 360 kilometers. Each degrees of longitude represents (40075 / 360) * cos(latitude) kilomemters. With this, we can calculate approximately a data frame including all points on circles, knowing the circle centers and radius.
library(ggplot2)
library(ggmap)
data = data.frame(
ID = as.numeric(c(1:8)),
longitude = as.numeric(c(-63.27462, -63.26499, -63.25658, -63.2519, -63.2311, -63.2175, -63.23623, -63.25958)),
latitude = as.numeric(c(17.6328, 17.64614, 17.64755, 17.64632, 17.64888, 17.63113, 17.61252, 17.62463))
)
#################################################################################
# create circles data frame from the centers data frame
make_circles <- function(centers, radius, nPoints = 100){
# centers: the data frame of centers with ID
# radius: radius measured in kilometer
#
meanLat <- mean(centers$latitude)
# length per longitude changes with lattitude, so need correction
radiusLon <- radius /111 / cos(meanLat/57.3)
radiusLat <- radius / 111
circleDF <- data.frame(ID = rep(centers$ID, each = nPoints))
angle <- seq(0,2*pi,length.out = nPoints)
circleDF$lon <- unlist(lapply(centers$longitude, function(x) x + radiusLon * cos(angle)))
circleDF$lat <- unlist(lapply(centers$latitude, function(x) x + radiusLat * sin(angle)))
return(circleDF)
}
# here is the data frame for all circles
myCircles <- make_circles(data, 0.45)
##################################################################################
island = get_map(location = c(lon = -63.247593, lat = 17.631598), zoom = 13, maptype = "satellite")
islandMap = ggmap(island, extent = "panel", legend = "bottomright")
RL = geom_point(aes(x = longitude, y = latitude), data = data, color = "#ff0000")
islandMap + RL +
scale_x_continuous(limits = c(-63.280, -63.21), expand = c(0, 0)) +
scale_y_continuous(limits = c(17.605, 17.66), expand = c(0, 0)) +
########### add circles
geom_polygon(data = myCircles, aes(lon, lat, group = ID), color = "red", alpha = 0)
Well, as the referred posting already suggests - switch to a projection that is based in meters, and then back:
library(rgeos)
library(sp)
d <- SpatialPointsDataFrame(coords = data[, -1],
data = data,
proj4string = CRS("+init=epsg:4326"))
d_mrc <- spTransform(d, CRS("+proj=merc +a=6378137 +b=6378137 +lat_ts=0.0 +lon_0=0.0 +x_0=0.0 +y_0=0 +k=1.0 +units=m +nadgrids=#null +no_defs"))
Now, the width can be specified in meters:
d_mrc_bff_mrc <- gBuffer(d_mrc, byid = TRUE, width = 450)
Transform it back and add it to the plot using geom_path:
d_mrc_bff <- spTransform(d_mrc_bff_mrc, CRS("+init=epsg:4326"))
d_mrc_bff_fort <- fortify(d_mrc_bff)
islandMap +
RL +
geom_path(data=d_mrc_bff_fort, aes(long, lat, group=group), color="red") +
scale_x_continuous(limits = c(-63.280, -63.21), expand = c(0, 0)) +
scale_y_continuous(limits = c(17.605, 17.66), expand = c(0, 0))
Calculating distance in km given latitude and longitude isn't super straightforward; 1 degree lat/long is a greater distance at the equator than at the poles, for example. If you want an easy workaround that you can eyeball for accuracy, you might try:
islandMap + RL +
scale_x_continuous(limits = c(-63.280, -63.21), expand = c(0, 0)) +
scale_y_continuous(limits = c(17.605, 17.66), expand = c(0, 0)) +
geom_point(aes(x = longitude, y = latitude), data = data, size = 20, shape = 1, color = "#ff0000")
You'll need to adjust the size paramter in the 2nd geom_point to get closer to what you want. I hope that helps!
An accurate solution is using the geosphere::destPoint() function. This works without switching projections.
Define function to determine 360 points with a certain radius around one point:
library(dplyr)
library(geosphere)
fn_circle <- function(id1, lon1, lat1, radius){
data.frame(ID = id1, degree = 1:360) %>%
rowwise() %>%
mutate(lon = destPoint(c(lon1, lat1), degree, radius)[1]) %>%
mutate(lat = destPoint(c(lon1, lat1), degree, radius)[2])
}
Apply function to each row of data and convert to data.frame:
circle <- apply(data, 1, function(x) fn_circle(x[1], x[2], x[3], 450))
circle <- do.call(rbind, circle)
Then the map can be easily obtained by:
islandMap +
RL +
scale_x_continuous(limits = c(-63.280, -63.21), expand = c(0, 0)) +
scale_y_continuous(limits = c(17.605, 17.66), expand = c(0, 0)) +
geom_polygon(data = circle, aes(lon, lat, group = ID), color = "red", alpha = 0)
A solution using st_buffer() from the sf package.
library(ggmap)
library(ggplot2)
library(sf)
data <- data.frame(
ID = 1:8,
longitude = c(-63.27462, -63.26499, -63.25658, -63.2519,
-63.2311, -63.2175, -63.23623, -63.25958),
latitude = c(17.6328, 17.64614, 17.64755, 17.64632,
17.64888, 17.63113, 17.61252, 17.62463)
)
Convert data.frame to sf object:
points_sf <- sf::st_as_sf(data, coords = c("longitude", "latitude"), crs = 4326)
For this example we use UTM zone 20, which contains the coordinates of the island:
data_sf_utm <- sf::st_transform(points_sf, "+proj=utm +zone=20")
Now we can buffer the point by 450 meters:
circle <- sf::st_buffer(data_sf_utm, dist = 450)
ggmap seems to have some issues with geom_sf. Setting inherit.aes to FALSE returns the desired map.
island <- ggmap::get_map(location = c(lon = -63.247593, lat = 17.631598), zoom = 14, maptype = "satellite")
ggmap(island, extent = "panel", legend = "bottomright") +
geom_sf(data = points_sf, color = "red", inherit.aes = FALSE) +
geom_sf(data = circle, color = "red", alpha = 0, inherit.aes = FALSE)
Created on 2020-10-11 by the reprex package (v0.3.0)
I want to plot a map with some points on it. I tried this code:
lon <- c(103.25,103.28)
lat <- c(3.80, 3.78)
df <- as.data.frame(cbind(lon,lat))
Getting the map:
mapgilbert <- get_map(location = c(lon = mean(df$lon), lat = mean(df$lat)), zoom = 12,maptype = "satellite", scale = 3)
Plotting the map with some points on it:
ggmap(mapgilbert) +
geom_point(data = df, aes(x = lon, y = lat, fill = "red", alpha = 0.8),size = 5, shape = 21) +guides(fill=FALSE, alpha=FALSE, size=FALSE)
Based on this code, the same color of points appear. My question is, I want to create multiple color of points on the map. Kindly assist, your help is highly appreciated. Thank you.
You need to add a categorical variable (what should the colors express?) to govern the color aesthetics:
#create some dummy data
df$coloringCategory <- rep(c("A","B"),length(df$lat)/2)
#in ggplot include the categorical variable
geom_point(data = df, aes(x = lon, y = lat, color= coloringCategory, alpha = 0.8),size = 5, shape = 21)