swissRain: Swiss rainfall data
In geostatsp: Geostatistical Modelling with Likelihood and Bayes
Description
Usage
Format
Source
Examples
Description
Data from the SIC-97 project: Spatial Interpolation Comparison.
Usage
1
data("swissRain")
Format
swissRain is a SpatialPolygonsDataFrame
100 daily rainfall
measurements made in Switzerland on the 8th of May 1986.
swissAltitude is a raster of elevation data, and swissLandType is a raster
of land cover types.
Source
https://wiki.52north.org/AI_GEOSTATS/AI_GEOSTATSData and http://srtm.csi.cgiar.org and
https://lpdaac.usgs.gov/dataset_discovery/modis/modis_products_table
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data("swissRain")
plot(swissAltitude, main="elevation")
points(swissRain)
plot(swissBorder, add=TRUE)
# land type, a categorical variable
commonValues = sort(table(values(swissLandType)),decreasing=TRUE)[1:5]
commonValues=commonValues[!names(commonValues)==0]
thelevels = levels(swissLandType)[[1]]$ID
thebreaks = c(-0.5, 0.5+thelevels)
thecol = rep(NA, length(thelevels))
names(thecol) = as.character(thelevels)
thecol[names(commonValues)] = rainbow(length(commonValues))
plot(swissLandType, breaks=thebreaks, col=thecol,legend=FALSE,
main="land type")
points(swissRain)
plot(swissBorder, add=TRUE)
legend("topleft",fill=thecol[names(commonValues)],
legend=levels(swissLandType)[[1]][
match(as.integer(names(commonValues)),
levels(swissLandType)[[1]]$ID),
"Category"],
bty='n'
)
# code to assemble the dataset
## Not run:
dataDir = "/store/patirck/spatialData/"
download.file("http://mldata.org/repository/data/download/spat-interp-comparison-1997/",
destfile=paste(dataDir, "swiss.zip",sep=""))
unzip(paste(dataDir, 'swiss.zip',sep=""), exdir=dataDir)
swissRain = read.table(paste(dataDir, "sic_obs.dat",sep=""),sep=',',
col.names=c('ID','x','y','rain'))
# the following seems to make the coordinates line up with epsg:2056
swissRain$x = swissRain$x - 17791.29 + 2672591
swissRain$y = swissRain$y - 13224.66 + 1200225
# the readme file says rain is in tenths of mm
swissRain$rain= swissRain$rain / 10
library(sp)
library(rgdal)
# create projection without epsg code so rgdal doesn't need to be loaded
theproj = CRSargs(CRS("+init=epsg:2056"))
theproj = gsub("\+init=epsg:[[:digit:]]+ ", "", theproj)
theproj = CRS(theproj)
swissRain = SpatialPointsDataFrame(swissRain[,c('x','y')], data=swissRain[,c('ID','rain')],
proj4string=theproj)
#######
# Swiss Border
#######
library('raster')
swissBorder = getData('GADM', country='CHE', level=0)
isChar = which(unlist(lapply(swissBorder@data, is.character)))
isUtf = which(
unlist(lapply(swissBorder@data[,isChar],
Encoding)) == 'UTF-8')
swissBorder = swissBorder[,
!match(names(swissBorder), names(isUtf), nomatch=0)
]
library(rgdal)
swissBorder = spTransform(swissBorder, CRS(proj4string(swissRain)))
############
# land type
############
# see loaloa's help file for installation of the MODIS package
library(MODIS)
MODISoptions(gdalPath="/usr/bin/",
localArcPath=dataDir, outDirPath=dataDir)
options()[grep("MODIS", names(options()), value=TRUE)]
myProduct = "MCD12Q1"
getProduct(myProduct)
thehdf=getHdf(product=myProduct,
begin="2002-01-01",end="2002-01-02",
extent=extent(spTransform(swissBorder, CRS("+init=epsg:4326"))))
layerNames = getSds(thehdf[[1]][1])$SDSnames
ltLayer = grep("Type_1$", layerNames)
theString = rep(0, length(layerNames))
theString[ltLayer] = 1
theString = paste(theString, collapse="")
runGdal(product=myProduct,
begin="2002-01-01",end="2002-01-02",
outProj = proj4string(swissRain),
pixelSize=2000, job="loa",
SDSstring = theString,
extent=extent(spTransform(swissBorder, CRS("+init=epsg:4326"))))
# find file name
thenames = preStack(
path = paste(options()$MODIS_outDirPath, "loa",sep=""),
pattern=myProduct)
swissLandType = raster(thenames)
swissLandType = crop(swissLandType, extend(extent(swissBorder),20000))
swissLandType = as.factor(swissLandType)
# labels of land types
library(XML)
labels = readHTMLTable("http://nsidc.org/data/ease/ancillary.html")
labels = labels[[grep("Land Cover Classes", names(labels))]]
classCol = grep("Class Number", names(labels))
labels[,classCol] = as.integer(as.character(labels[,classCol]))
labels[ grep("Water", labels$Category),
classCol
] = 0
labelVec = as.character(labels$Category)
names(labelVec) = as.character(labels[,classCol])
levels(swissLandType)[[1]]$Category =
labelVec[as.character(levels(swissLandType)[[1]]$ID)]
levels(swissLandType)[[1]]$col = NA
theForests = grep("forest", levels(swissLandType)[[1]]$Category,
ignore.case=TRUE)
library(RColorBrewer)
levels(swissLandType)[[1]][theForests,"col"] =
brewer.pal(length(theForests)+1, "Greens")[-1]
levels(swissLandType)[[1]][
grep("snow", levels(swissLandType)[[1]]$Category,ignore.case=TRUE),
"col"] = "#FFFFFF"
levels(swissLandType)[[1]][
grep("water", levels(swissLandType)[[1]]$Category,ignore.case=TRUE),
"col"] = "#0000FF"
levels(swissLandType)[[1]][
grep("grass", levels(swissLandType)[[1]]$Category,ignore.case=TRUE),
"col"] = "#CCBB00"
stillNA = is.na(levels(swissLandType)[[1]]$col)
levels(swissLandType)[[1]][stillNA, "col"] =
brewer.pal(sum(stillNA), "Set3")
swissLandType@legend@colortable = levels(swissLandType)[[1]]$col
levels(swissLandType)[[1]]$n = table(values(swissLandType))
plot(swissLandType)
mostCommon = levels(swissLandType)[[1]]$n >= 700
legend("topright",
fill=levels(swissLandType)[[1]][mostCommon,"col"],
legend = substr(
levels(swissLandType)[[1]][mostCommon,"Category"],
1, 12)
)
table(extract(swissLandType, swissRain), exclude=NULL)
####
# SwissAltitude
###
library(raster)
download.file('http://biogeo.ucdavis.edu/data/diva/alt/CHE_alt.zip',
destfile=paste(dataDir,'CHE_alt.zip',sep=""))
unzip(paste(dataDir, 'CHE_alt.zip',sep=""), exdir=dataDir)
swissAltitude = raster(paste(dataDir, "CHE_alt.gri",sep=""))
swissAltitude = projectRaster(swissAltitude,
crs=CRS(proj4string(swissRain)))
swissAltitude = aggregate(swissAltitude,fact=2)
save(swissRain, swissAltitude, swissBorder, swissLandType,
file="~/workspace/diseasemapping/pkg/geostatsp/data/swissRain.RData",
compress="xz")
## End(Not run)
geostatsp documentation built on July 14, 2018, 9:01 a.m.
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Description Usage Format Source Examples
Description
Data from the SIC-97 project: Spatial Interpolation Comparison.
Usage
1 | data("swissRain")
|
Format
swissRain is a SpatialPolygonsDataFrame
100 daily rainfall
measurements made in Switzerland on the 8th of May 1986.
swissAltitude is a raster of elevation data, and swissLandType is a raster
of land cover types.
Source
https://wiki.52north.org/AI_GEOSTATS/AI_GEOSTATSData and http://srtm.csi.cgiar.org and https://lpdaac.usgs.gov/dataset_discovery/modis/modis_products_table
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 | data("swissRain")
plot(swissAltitude, main="elevation")
points(swissRain)
plot(swissBorder, add=TRUE)
# land type, a categorical variable
commonValues = sort(table(values(swissLandType)),decreasing=TRUE)[1:5]
commonValues=commonValues[!names(commonValues)==0]
thelevels = levels(swissLandType)[[1]]$ID
thebreaks = c(-0.5, 0.5+thelevels)
thecol = rep(NA, length(thelevels))
names(thecol) = as.character(thelevels)
thecol[names(commonValues)] = rainbow(length(commonValues))
plot(swissLandType, breaks=thebreaks, col=thecol,legend=FALSE,
main="land type")
points(swissRain)
plot(swissBorder, add=TRUE)
legend("topleft",fill=thecol[names(commonValues)],
legend=levels(swissLandType)[[1]][
match(as.integer(names(commonValues)),
levels(swissLandType)[[1]]$ID),
"Category"],
bty='n'
)
# code to assemble the dataset
## Not run:
dataDir = "/store/patirck/spatialData/"
download.file("http://mldata.org/repository/data/download/spat-interp-comparison-1997/",
destfile=paste(dataDir, "swiss.zip",sep=""))
unzip(paste(dataDir, 'swiss.zip',sep=""), exdir=dataDir)
swissRain = read.table(paste(dataDir, "sic_obs.dat",sep=""),sep=',',
col.names=c('ID','x','y','rain'))
# the following seems to make the coordinates line up with epsg:2056
swissRain$x = swissRain$x - 17791.29 + 2672591
swissRain$y = swissRain$y - 13224.66 + 1200225
# the readme file says rain is in tenths of mm
swissRain$rain= swissRain$rain / 10
library(sp)
library(rgdal)
# create projection without epsg code so rgdal doesn't need to be loaded
theproj = CRSargs(CRS("+init=epsg:2056"))
theproj = gsub("\+init=epsg:[[:digit:]]+ ", "", theproj)
theproj = CRS(theproj)
swissRain = SpatialPointsDataFrame(swissRain[,c('x','y')], data=swissRain[,c('ID','rain')],
proj4string=theproj)
#######
# Swiss Border
#######
library('raster')
swissBorder = getData('GADM', country='CHE', level=0)
isChar = which(unlist(lapply(swissBorder@data, is.character)))
isUtf = which(
unlist(lapply(swissBorder@data[,isChar],
Encoding)) == 'UTF-8')
swissBorder = swissBorder[,
!match(names(swissBorder), names(isUtf), nomatch=0)
]
library(rgdal)
swissBorder = spTransform(swissBorder, CRS(proj4string(swissRain)))
############
# land type
############
# see loaloa's help file for installation of the MODIS package
library(MODIS)
MODISoptions(gdalPath="/usr/bin/",
localArcPath=dataDir, outDirPath=dataDir)
options()[grep("MODIS", names(options()), value=TRUE)]
myProduct = "MCD12Q1"
getProduct(myProduct)
thehdf=getHdf(product=myProduct,
begin="2002-01-01",end="2002-01-02",
extent=extent(spTransform(swissBorder, CRS("+init=epsg:4326"))))
layerNames = getSds(thehdf[[1]][1])$SDSnames
ltLayer = grep("Type_1$", layerNames)
theString = rep(0, length(layerNames))
theString[ltLayer] = 1
theString = paste(theString, collapse="")
runGdal(product=myProduct,
begin="2002-01-01",end="2002-01-02",
outProj = proj4string(swissRain),
pixelSize=2000, job="loa",
SDSstring = theString,
extent=extent(spTransform(swissBorder, CRS("+init=epsg:4326"))))
# find file name
thenames = preStack(
path = paste(options()$MODIS_outDirPath, "loa",sep=""),
pattern=myProduct)
swissLandType = raster(thenames)
swissLandType = crop(swissLandType, extend(extent(swissBorder),20000))
swissLandType = as.factor(swissLandType)
# labels of land types
library(XML)
labels = readHTMLTable("http://nsidc.org/data/ease/ancillary.html")
labels = labels[[grep("Land Cover Classes", names(labels))]]
classCol = grep("Class Number", names(labels))
labels[,classCol] = as.integer(as.character(labels[,classCol]))
labels[ grep("Water", labels$Category),
classCol
] = 0
labelVec = as.character(labels$Category)
names(labelVec) = as.character(labels[,classCol])
levels(swissLandType)[[1]]$Category =
labelVec[as.character(levels(swissLandType)[[1]]$ID)]
levels(swissLandType)[[1]]$col = NA
theForests = grep("forest", levels(swissLandType)[[1]]$Category,
ignore.case=TRUE)
library(RColorBrewer)
levels(swissLandType)[[1]][theForests,"col"] =
brewer.pal(length(theForests)+1, "Greens")[-1]
levels(swissLandType)[[1]][
grep("snow", levels(swissLandType)[[1]]$Category,ignore.case=TRUE),
"col"] = "#FFFFFF"
levels(swissLandType)[[1]][
grep("water", levels(swissLandType)[[1]]$Category,ignore.case=TRUE),
"col"] = "#0000FF"
levels(swissLandType)[[1]][
grep("grass", levels(swissLandType)[[1]]$Category,ignore.case=TRUE),
"col"] = "#CCBB00"
stillNA = is.na(levels(swissLandType)[[1]]$col)
levels(swissLandType)[[1]][stillNA, "col"] =
brewer.pal(sum(stillNA), "Set3")
swissLandType@legend@colortable = levels(swissLandType)[[1]]$col
levels(swissLandType)[[1]]$n = table(values(swissLandType))
plot(swissLandType)
mostCommon = levels(swissLandType)[[1]]$n >= 700
legend("topright",
fill=levels(swissLandType)[[1]][mostCommon,"col"],
legend = substr(
levels(swissLandType)[[1]][mostCommon,"Category"],
1, 12)
)
table(extract(swissLandType, swissRain), exclude=NULL)
####
# SwissAltitude
###
library(raster)
download.file('http://biogeo.ucdavis.edu/data/diva/alt/CHE_alt.zip',
destfile=paste(dataDir,'CHE_alt.zip',sep=""))
unzip(paste(dataDir, 'CHE_alt.zip',sep=""), exdir=dataDir)
swissAltitude = raster(paste(dataDir, "CHE_alt.gri",sep=""))
swissAltitude = projectRaster(swissAltitude,
crs=CRS(proj4string(swissRain)))
swissAltitude = aggregate(swissAltitude,fact=2)
save(swissRain, swissAltitude, swissBorder, swissLandType,
file="~/workspace/diseasemapping/pkg/geostatsp/data/swissRain.RData",
compress="xz")
## End(Not run)
|
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