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Spatial Analysis

Spatial Analysis. Maps, Points, and Grid Counts. Maps in R. Simple maps and profiles can be constructed using basic R functions Basic uses Grid map with values in each square Piece-plot map of artifacts Piece-plot profile Contour map (and filled contour) 3d perspective map. Grid Map.

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Spatial Analysis

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  1. Spatial Analysis Maps, Points, and Grid Counts

  2. Maps in R • Simple maps and profiles can be constructed using basic R functions • Basic uses • Grid map with values in each square • Piece-plot map of artifacts • Piece-plot profile • Contour map (and filled contour) • 3d perspective map

  3. Grid Map • Use windows() to set size • Use plot() function with asp=1 and optionally, axes=FALSE • Use polygons() or lines() to identify excavation units • Use text() to print information

  4. # Open Debitage3a # Open script file Grid3a.R and run it Grid3a() text(Debitage3a$East, Debitage3a$North, Debitage3a$TCt) text(985, 1015.5, "Debitage Count") Grid3a(FALSE) text(Debitage3a$East, Debitage3a$North, round(Debitage3a$TWgt,0)) text(985, 1015.5, "Debitage Weight")

  5. Piece-Plot Map • Use windows() to set size • Use plot() function with asp=1 and optionally, axes=FALSE • Use polygons() or lines() to identify excavation units • Use points() to add piece-plotted artifacts

  6. # Open BTF3a Grid3a() color <- c("red", "blue", "green") points(BTF3a[,1:2], pch=20, col=color[as.numeric(BTF3a$Type)]) text(985, 1015.6, "Bifacial Thinning Flakes") legend(986, 1022, c("Fragment", "Cortex", "No Cortex"), pch=20, col=color)

  7. library(vegan) CBTmst <- spantree(dist(BTF3a[BTF3a$Type=="CBT",1:2])) summary(CBTmst$dist) Grid3a(FALSE) points(BTF3a[BTF3a$Type=="CBT",1:2], pch=20) lines(CBTmst, BTF3a[BTF3a$Type=="CBT",1:2]) text(985, 1015.6, "Cortical Bifacial Thinning Flakes") # Min. 1st Qu. Median Mean 3rd Qu. Max. # 0.03606 0.12200 0.20010 0.28680 0.29080 1.16200 CBTmst2 <- spantree(dist(BTF3a[BTF3a$Type=="CBT",1:2]), toolong=.3) Grid3a(FALSE) points(BTF3a[BTF3a$Type=="CBT",1:2], pch=20) lines(CBTmst2, BTF3a[BTF3a$Type=="CBT",1:2]) text(985, 1015.6, "Cortical Bifacial Thinning Flakes")

  8. library(grDevices) Grid3a() BTFr3a <- BTF3a[BTF3a$Type=="BTF",] points(BTFr3a[,1:2], pch=20, col="red") BTFrch <- chull(BTFr3a[,1:2]) polygon(BTFr3a$East[BTFrch], BTFr3a$North[BTFrch], border="red") CBT3a <- BTF3a[BTF3a$Type=="CBT",] points(CBT3a[,1:2], pch=20, col="blue") CBTch <- chull(CBT3a[,1:2]) polygon(CBT3a$East[CBTch], CBT3a$North[CBTch], border="blue") NCBT3a <- BTF3a[BTF3a$Type=="NCBT",] points(NCBT3a[,1:2], pch=20, col="green") NCBTch <- chull(NCBT3a[,1:2]) polygon(NCBT3a$East[NCBTch], NCBT3a$North[NCBTch], border="green")

  9. Piece-Plot Profile • Use windows() to set the graph window proportions • Use plot() but NOT asp=1 to exaggerate the vertical dimension • For north/south profiles select points within one meter East • For east/west profiles select points within one meter north

  10. Contour Map • Use kde2d() to construct a kernel density map for north and east • Use contour to plot the map • Can adjust bandwidth values to increase or decrease smoothing

  11. Grid3a(FALSE) BTFdensity <- kde2d(BTF3a$East, BTF3a$North, n=100, lims=c(982,987,1015,1022)) contour(BTFdensity,xlim=c(982,987), ylim=c(1015,1022), add=TRUE) text(985, 1015.6, "Bifacial Thinning Flakes")

  12. 3d Perspective Map • Not terribly useful but fun to look at • Cannot add grid to map or other labeling • Fiddle with expand=, theta=, and phi= options to get the best view

  13. BTFdensity <- kde2d(BTF3a$East, BTF3a$North, n=100, lims=c(982,987,1015,1022)) persp(BTFdensity,xlim=c(982,987),ylim=c(1015,1022), main="Bifacial Thinning Flakes", scale=FALSE, xlab="East", ylab="North", zlab="Density", theta=-30, phi=25, expand=5) persp(BTFdensity,xlim=c(982,987),ylim=c(1015,1022), main="Bifacial Thinning Flakes", scale=FALSE, xlab="East", ylab="North", zlab="Density", theta=-30, phi=40, expand=5)

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