similar to: SPATIAL QUESTION: HOW TO MAKE POLYGONS AROUND CLUSTERS OF POINTS AND EXTRACT AREAS AND COORDINATES OF THESE POLYGONS?

Dear list, are there any possibilities to fill a polygon with a point pattern or with a symbol pattern like '+' oder '-' instead of shading lines? Thanks in advance Dr. Michael Wolf Bezirksregierung M??nster Dezernat 61 Domplatz 1-3 48161 M??nster Tel.: ++ 49 (02 51) / 4 11 - 17 95 Fax.: ++ 49 (02 51) / 4 11 - 8 17 95 E-Mail: michael.wolf at bezreg-muenster.nrw.de

In converting some older code: ## builds an OWIN to generate a set of points on a grid within the OWIN object: bdry <- read.shape( "../../data/boundary.shp" ) outline.verts <- bdry$Shapes[[2]]$verts[1:bdry$Shapes[[2]]$Pstart[2],] outline.order <- nrow( outline.verts ) : 2 bdry.poly <- vector( 2, mode="list" ) bdry.poly[[1]] <- list(

Hello; Please coud you advise me of a simple way to select points (x,y coordinates) that fall within a polygon. I've got a set of polygons, each one defined by an arbitrary number of points, and several points inside each polygon. I know this is simple with a GIS, but I'd rather do it inside R. Thanks and best regards, Javier -----

Hi everyone, I am facing a problem I really do not know how to resolve about detecting significant spatial structures in a region I am studying. The study is about the Miombo forest (wooded savanna). I am working in a 10 ha permanent forest plot, where all trees are mapped and identified. I sampled 24 more or less regulately scattered plots of 25 x 25 m over the 10 ha. In each plot of 25 x 25 m

I am a new user of the R spatstat package and am having problems creating a polygonal observation window with owin(). Code follows: library("maps") library ("sp")` library("spatstat") mass.map <- map("state", "massachusetts:main", fill=T) # This returns a data frame includding x and y components that form a polygon of massachusetts mainland`

Dear R users, I wish to run spatial point pattern analysis (e.g. pair correlation function, mark correlation function) for which I need to create an observation window (window=owin) from which the spatial analysis is generated. The command I used to create this observation window as follows: X1<- ppp(x, y, window=owin(c(80.58,144.96),c(101.06,165.13)),

I'm looking for a way to plot lines on top of a levelplot(), where the lines are borders between cells of different values. The clines() function provides contours suitable for continuous data. I am dealing with discrete values, spatial clusters of nodes where each cluster has an integer value, and I want to plot the borderlines between these areas. So, in a levelplot having nodes with

I have a list of bounds for a series of polygons. I do understand the formula to determine whether point i is within polygon X (X[x1] < i[x] & X[x2] > i[x] & X[y1] < i[y] & X[y2] > i[y]), and I can apply this throughout the dataset. However, this naive algorithm doesn't scale very well. The data set contains 10,000 points consisting of (n,e) pairs where I'm

Dear all, I wonder which R algorithm could perform a search of local maxima in an spatial grid, in other words, having the coordinates of a map (x,y,z... up to 6 coordinates) and then the altitude/height at each point (h) (in total 7 numerical variables) I would like to localise the peaks (local maxima) of that topological surface. Which R algorithm can perform this? Thanks a lot, Josep Maria,

If I know the specific coordinate in a spatial data frame, how can I access the data at that coordinate? My coordinates are labeled "x" and "y" in a data.frame "e". The data is in column "leachate". I want to say, basically: e$leachate@coordinates(2,3<mailto:e$leachate@coordinates(2,3>). Thanks, Daniel [[alternative HTML version deleted]]

I am building a mask with area.urb.sp.W <- as(area.urb.sp, "owin") and got the message Erro em owin(poly = opls) : Polygon data contain duplicated vertices, self-intersection and overlaps between polygons how can I solve this problem in R? many thanks IVAN [[alternative HTML version deleted]]

I had a well-working R 1.7, however, today the programme did not start, and I recieved an error message. I have uninstalled the R 1.7, and then installed R 1.9. Still it does not start, giving the error message "Fatal error: invalid HOMEDRIVE". How can I get it to work? Bjorn Okland [[alternative HTML version deleted]]

Hi all, ?I'm trying to iterate in a SpatialPolygonDataFrame thatcontains 110 features. I tried to use the following code? iterate.spdf =function(x){ for (i in 1:nrow(x)){ p = x[i, ]} return(p)} but with no success as it returns with aSpatialPolygonDataFrame that contains onlyone feature. The code seems to overwrite the polygons to end up with only onefeature. ?Any suggestions?Ashraf, cheers

Dear all, I would like to inquire, if it is a desired feature that the combination with rbind() of two data frames with factors columns does not sort the factors levels of the combined data frame. > str(rbind(data.frame(a = factor(c(4, 3))), data.frame(a = factor(c(2, 1))))) 'data.frame': 4 obs. of 1 variable: $ a: Factor w/ 4 levels

Dear all, I am currently working with the spatstat package, using windows and pixel images. First: My aim is to transform a shapefile (see attached) into a pixel image. My idea is to start transforming the shapefile into a Spatial Polygon file: x <- readShapeSpatial("200001441.shp") y <- as(x, "SpatialPolygons") z <- as.owin(y) Given z, I want to identify each

Hello, I have fitted a Log-Gaussian Cox Process on my data but when I try to use "simulate.kppm" of the spatstat package I get this error: Error in rLGCP(model = model, mu = mu, param = param, ..., win = win) : The spatial domain of the pixel image ?mu? does not cover the simulation window ?win? I've used covariates as im, changed the npixel value of the spatstat options to

On 02/06/17 01:17, Lluis.Hurtado at uv.es wrote: > Dear all, > > I am currently working with the spatstat package, using windows and pixel images. > > First: > > My aim is to transform a shapefile (see attached) into a pixel image. > > My idea is to start transforming the shapefile into a Spatial Polygon file: > > x <-

This is not a request for coding help so there is no reproducible code, rather I am trying to figure out if anyone had had a similar experience. My question is related to partitioning the variance in rda (vegan) results for multiple groups of variables. I have a high dimensional dataset with 79 explanatory variables and 9 response variables. Within those 79 explanatory variables there are ~8

Hi! I have no idea if this is maybe an easy task utilizing R since I read there is geographical map data in some package: I have a huge number of geographical points with their coordinates in Germany. Now I want to determine for each point in which "Bundesland" = state it is located. Can anybody tell me if this is doable relatively easy in R and if so give me some hints or links

Hi, i am using spatstat package for spatial data analysis and now i have a problem to create a point pattern. The points are in file "points.txt" (first column for Latitude and second column for Longitude ) and I imported them and separated each columns in two arrays x and y. If I plots x and y ( e.g plot(x,y) ) the result appears in square area without problems and the scale is