This page is a encyclopedia article.
The page identifier is Op_en5843 |
|---|
| Moderator:Jouni (see all) |
|
|
| Upload data
|
Massachusetts Health and Environment Information System (MassHEIS) is a database maintained by Silent Spring Institute.
This user interface downloads data directly from the MassHEIS database.
library(OpasnetUtils)
library(OpasnetUtilsExt)
library(ggplot2)
library(rgdal)
library(maptools)
library(RColorBrewer)
library(classInt)
library(raster)
library(xtable)
data <- MassHEIS.data(datatable)
print(xtable(head(data)), type = 'html')
if(datatable == "EPAParticulateMatter") {
data <- data[data$Year == year, ]
title <- paste("PM2.5 concentration, annual mean in Massachusetts, ", year, " (ug /m3)", sep ="")
coordinates(data)=c("longitude","latitude")
# ggplot(data, aes(x = Year, y = anmean)) + geom_bar()
}
if(datatable == "SuperfundSites") {
colnames(data)[colnames(data) == "HRS_SCORE"] <- "anmean"
title <- "Superfund sites, HRS_SCORE"
coordinates(data)=c("LONGITUDE","LATITUDE")
}
# Plot the data
proj4string(data)<-("+init=epsg:4326")
epsg4326String <- CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs")
shp<-spTransform(data,epsg4326String)
#Create blank raster
rast<-raster()
#Set raster extent to that of point data
extent(rast)<-extent(shp)
#Choose number of columns and rows
ncol(rast) <- 64
nrow(rast) <- 64
#Rasterize point data
rast2<-rasterize(shp, rast, shp$anmean, fun=mean)
start <- min(shp$anmean)
end <- max(shp$anmean)
steps <- approx(c(start,end),n=6)$y
colors <- rev(rainbow(length(steps), start=0, end=0.50))
par(mfrow=c(6,1), mar=c(3,1,0,1), cex=1.5)
colorstrip <- function(colors, labels)
{
count <- length(colors)
m <- matrix(1:count, count, 1)
image(m, col=colors, ylab="", axes=FALSE)
axis(1,approx(c(0, 1), n=length(labels))$y, labels)
}
cat("<span style='font-size: 1.2em;font-weight:bold;'>", title, "</span>\n")
colorstrip(colors, steps)
#Plot data
google.show_raster_on_maps(rast2, col=colors, style="height:500px;")
|
<mfanonymousfilelist></mfanonymousfilelist>