RGIS.Rmd

---
title: "R GIS Resource"
author: "Raghu Sidharthan"
output:  html_document
---


**Common GIS Tasks using R Libraries**

[RBasic1](RBasic1), 
[RBasic2](RBasic2),
[RBasic3](RBasic3),
[Leaflet](Leaflet)

**1. Reading and Writing Shapefiles**

```{r,results='hide',echo=TRUE,eval=FALSE}
# Using rgdal package
taz <- readOGR("C:\\Temp\\", "tazInput") 
taz <- readOGR('.\\inp.geojson',layer='OGRGeoJSON')

writeOGR(taz,'.', layer = "taz_mod", driver = "ESRI Shapefile")


# maptools package

# For polygon
taz <- readShapePoly("C:/Temp/tazInput.shp",IDvar="ID",proj4string=CRS("+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0")) 

# For Line file - e.g. NEtwork
linkNet <- readShapeLines(paste0(PrjDr,'\\network.shp'))

# For Spatial Points


#To get the projection used in a shapefile use this
taz@proj4string # Prints the projection string
#To set projection (if there is no projection)
taz@proj4string <-  CRS("+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0")
#This should be consistent with the coordinates used in the shapefile (even if projection information is not stored)
#Transform the proj4string
taz <- spTransform(taz,CRS("+proj=utm +zone=17 +north"))

#Creating a SpatialPointsDataFrame from bare coordinates
parLong <- -117.2274;	parLatt <-   33.91980
pts <- cbind(x=parLong,y=parLatt)
pointobj <- SpatialPoints(pts,proj4string=CRS("+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0"))
pointobj <- SpatialPointsDataFrame(pts, sites, coords.nrs = numeric(0),
proj4string = CRS("+proj=lcc +lat_1=30.12 +lat_2=31.88 +lat_0=29.67 +lon_0=-100.33 +x_0=700000 +y_0=3000000 +ellps=GRS80 +datum=NAD83 +units=us-ft +no_defs +towgs84=0,0,0]"), match.ID = TRUE)

#Centroid of polygons
trueCentroids = gCentroid(sids,byid=TRUE)


#Printing the shapefile to a PNG file with a given resolution
png("jointPlot.png",width=8.0,height=6.0,units="in",res=1200) # use pdf() for PDF files
plot(SCAGTAZt2_trans);#plot(HSR_TAZs,add=T)
dev.off()

```

**2. Frequently used functions**

```{r,results='hide',echo=TRUE,eval=FALSE}

#This function sets the projection for a SPDF without Projection and transforms to Web Projection
sfctaCRS <- ("+init=epsg:2227")
setProjWeb <- function(inSh,origPrj){
  inSh@proj4string <- CRS(origPrj)
  inSh  <- spTransform(inSh, CRS("+init=epsg:4269"))
}
linkNet3 <- setProjWeb(linkNet2,sfctaCRS)


# Crops a shapefile between the specified x and y projection coordinates
cropByCen <- function(inSh,x1,x2,y1,y2){
  cenDT = data.table(gCentroid(inSh, byid = TRUE)@coords)
  retSH <- inSh[cenDT$y>y1 & cenDT$y<y2 & cenDT$x>x1 & cenDT$x<x2,]
  return(retSH)
}
netCase1_crop <- cropByCen(netCase1,860000,890000,580000,600000)

# Do Spatial Union and create a higher level polygons of the type SpatialPolygonsDataFrame
doPolyUnion <- function(inpPoly,unionVec){
  retPoly <- unionSpatialPolygons(inpPoly, unionVec)
  dummyData = data.table(row.names(retPoly))
  row.names(dummyData) <- row.names(retPoly)
  retPoly = SpatialPolygonsDataFrame(retPoly,dummyData)
  retPoly@data$V1 <- (retPoly@data$V1)
  return(retPoly)
}

```

**3. Miscellaneous Items**

```{r,results='hide',echo=TRUE,eval=FALSE}

#Intersection of a SpatialPoints and SpatialPolygonsDataFrame – implemented in sp
check <- over(pointobj,SCAGTAZt2)
returns a data.frame of the second argument with row entries corresponding to the first argument


#Intersection of polygon and polygon – implemented in library(rgeos)
check1 <- over(SCAGTAZt2_tr,HSR_TAZs)
check3 <- over(SCAGTAZt2_tr,HSR_TAZs,returnList = TRUE)

#Dissolve all boundaries  - use gUnaryUnion function
plot((tracts10))
plot(gUnaryUnion(tracts10))
#The result is a SpatialPolygon. 

#Function to get the TAZ location of a dataframe of points
taz <- readOGR("C:\\Project\\", "taz")
getTAZ <- function(parLong,parLatt){
pts <- cbind(parLong,parLatt)
pointobj <- SpatialPoints(pts,proj4string=CRS("+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0"))
getTAZ <- over(pointobj,taz)$ID
}

#Use of spbind to merge a dataframe to a spatial object

xx <- readShapePoly(system.file("shapes/sids.shp", package="maptools")[1], 
  IDvar="FIPSNO", proj4string=CRS("+proj=longlat +ellps=clrk66"))
xtra <- read.dbf(system.file("share/nc_xtra.dbf", package="maptools")[1])
o <- match(xx$CNTY_ID, xtra$CNTY_ID)
xtra1 <- xtra[o,]
row.names(xtra1) <- xx$FIPSNO
xx1 <- spCbind(xx, xtra1)
names(xx1)
identical(xx1$CNTY_ID, xx1$CNTY_ID.1)

#Dissolving the boundaries – using maptools
if (!rgeosStatus()) gpclibPermit()
nc1 <- readShapePoly(system.file("shapes/sids.shp", package="maptools")[1],
 proj4string=CRS("+proj=longlat +datum=NAD27"))
lps <- coordinates(nc1)
ID <- cut(lps[,1], quantile(lps[,1]), include.lowest=TRUE)
reg4 <- unionSpatialPolygons(nc1, ID)
row.names(reg4)



#For calculating the area of polygons

# Transforming the projection to a planar system for calculating the polygon area
spData <-spTransform(inpshp,CRS("+proj=lcc +lat_1=34.03333333333333 +lat_2=35.46666666666667 +lat_0=33.5 +lon_0=-118 +x_0=2000000
+y_0=500000.0000000001 +datum=NAD83 +units=us-ft +no_defs +ellps=GRS80 +towgs84=0,0,0"))
temp1 <- sapply(slot(spData, "polygons"), function(x) sapply(slot(x, "Polygons"), slot, "area"))

# Getting the latitude/longitude extend of a shapefile 
extent(nhood) # library(raster)

# Get the polygon ID from the SpatialPolygonDataFrame
sapply(slot(Zoning, "polygons"), function(x) slot(x, "ID"))
sapply(Zoning@polygons, function(x) slot(x, "ID"))

# adds the plot to the existing plot
plot(tazDist,add=TRUE)

# gIntersection and gSimplify
# gSimplify – to smooth the polygon edges so that gIntersection becomes faster
# When applied to lines it is possible for the resulting geometry to lose simplicity (gIsSimple). If topologyPreserve is not specified it is also possible that the resulting geometries may no longer be valid (gIsValid). Remember to check the resulting geometry as many other functions rely on simplicity and or validity when performing their calculations.
# Use length(taz@polygons) to see how many polygons ware there in the output. If there is a reduction in the number of polygons then make the tolerance value smaller (0.01 to 0.001)
# TODO: Add a procedure to identify the smallest polygon and plot it before and after – to understand the magnitude of changes



```