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Spatial patterns: I have a dataset of coordinates and marks (diameter) attributed to the points. I am trying to create a window (owin()) for each plot (I have 2 plots), but I don't know how to set the window for both plots:

My window:

#data: rea_spd "SpatialPointsDataFrame'
w <- owin(xrange = c(min(rea_spd$Longitude_), max(rea_spd$Longitude_)),
          yrange=c(min(rea_spd$Latitude_N), max(rea_spd$Latitude_N)))
plot(w)
#this produces a window for all the data, but I don't know how to adapt it to have a window for each plot.
#After, I calculated Kcross, which works, but I still need to have two windows, otherwise, I will violate the statistical assumptions:
kmultrea <- envelope(reav, Kcross, nsim=999, i="A", j="S",
                     global=F, savefuns=TRUE, conf.level= 0.95)
plot(kmultrea,main="Cross-K - Protected area", xlab = "Distance r [m]", 
     xlim = c(0,30), ylim=c(0, 6000), legend = F)
pk <- LF.gof(kmultrea) #
pk

I tried to follow this example, but I still do not receive the points inside the windows:

m = matrix(0,20,20)
m[1+20*cbind(c$x,c$y)]=1
imask = owin(c(0,1),c(0,1),mask = t(m)==1 )
pp1 = ppp(x=c$x,y=c$y,window=imask)
plot(pp1) 

Determining if trees within forest gaps are clustered using R?

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I think I have found the solution:

#Define ppp and owin window:                                                          poi_rr1 <- as.ppp(poi1)
ww <- as.owin(poly1)
poi_rr1 <- poi_rr1[ww]
marks(poi_rr1) <- factor(poi_rr1$marks$TypeD)  

# ESTIMATE BANDWIDTH                                                                   
bw1 <- bw.diggle(poi_rr1, correction="isotropic", hmax=NULL, nr=400) 

#Calculate Kcross                                                                            
kcross1 <- envelope(poi_rr1, Kcross, nsim=99, i="A", j="S", correction = "isotropic", bw = 9.380343, global=F, savefuns=TRUE, conf.level= 0.95)

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