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The source function runs code from another R script file (see help(source) for details). Normally you'd see it more like: source("LISA.R") with the filename in quotation marks. Without the quotation …

Quick: use the over(pts,poly) function to return which polygon each point is in. [You might have to construct pts as a SpatialPoints object from your data frame]. Then the return value tells you which …

Don't use readTIFF for reading GeoTIFF files. It will not read the spatial information and may mess up in other ways too: ghanaPop = readTIFF(ghanaPopLocation) #Get initial GEOTIFF loaded use raster …

This is what the raster::extract function does, and it can extract values from a stack by cell number, or x-y coordinate. See help(extract) for more.

The rosm package can download tiles from OpenStreetMap and construct an RGB raster that you can use as the first layer in a tmap plot. …

Taking a vector and subsetting it by a condition will return those values that match the condition. You seem to want to make a boxplot of: RupandehiForest2010$Forest.Percent[RupandehiForest2010$Forest …

853703, 825353, 805353) Add another point close to point 4: library(sp) x = c(x,x[4]+1000) y = c(y,y[4]) SP <- SpatialPoints(coords = cbind(x,y)) SP$ID <- paste("point", 1:length(SP), sep = "") Plot … points, add labels: library(maptools) plot(SP) pointLabel(coordinates(SP),labels=SP$ID) Note point4 and point8 labels don't overlap. …

/topo_E06000023.json") plot(m$geom) plot(st_union(m$geom)) …

as.data.frame(mydata) length funct functN 1 500.8422 t 1 2 293.6068 t 1 11 612.0664 wcs 2 21 629.7057 wcs 2 those numbers are valid line types, so you can then do: plot … (mydata, lty=mydata$functN) If you want the solid and dashed lines the other way round then subtract it from 3: plot(mydata, lty=3-mydata$functN) which will transform 2 to 1 and 1 to 2. …

and plot the extent, then add the rasters: em = merge(extent(rr1),extent(rr2)) plot(em, type="n") plot(rr1,add=TRUE, legend=FALSE) plot(rr2, add=TRUE, legend=FALSE) Use type="n" so a box isn't drawn … From experiments it seems to me that plot(r, ext=e) only has an effect if e is within r, in other words for focusing on a part of a raster, not zooming out. …

This is unnecessary because the object is already in that coordinate system: proj4string(countries_sp) <- CRS("+init=epsg:4326") This doesn't do a coordinate transformation - the crs argument is i …

of each row: > multi = function(spdf){ sapply(spdf@polygons, function(p){length(p@Polygons)}) >1 } So it returns true or false: > multi(nc) [1] FALSE FALSE FALSE TRUE FALSE FALSE ... etc Plot … the multu polys with some colours so you can see the parts: > plot(nc[multi(nc),], col=1:10) And if you want row indexes you can have them: > which(multi(nc)) [1] 4 56 57 87 91 95 and if you …

California is not at latitude -120, unless there's been an earthquake and its drifted off into the Pacific (although +30 longitude probably puts it in the South Atlantic...). It seems that latitude an …

You might be able to do this by converting your points to sf objects and then mapview lets you use hide=TRUE when you add map layers. Then you can use all your points as a hidden map layer, and that s …

Now plot the raster and overlay the coastline: plot(fdiff_north) plot(sldf_prj, add=TRUE) Note its better to use sf packages and classes, you can do that with: library(sf) coast = rnaturalearth::ne_coastline … (returnclass="sf") coast_t = st_transform(coast, crs(fdiff_north)) plot(fdiff_north) plot(st_geometry(coast_t), add=TRUE) And you get the same map but probably bit quicker and with less memory. …