Relassify continuous raster data into binned classes with discrete colors

Question

I would like to:

1. Reclassify the raster ras into nine classes using reclassify

2. Provide a colorkey with values written beside each colour (see sample plot below). The colorkey should not be split, as in the sample plot, but rather shown as a single colour ramp with 9 colours.

3. Display the data using levelplot function (this I can do)

Thanks for your help. AEZ

library(rasterVis)

Please use these colors:

col <- colorRampPalette(c("yellow4", "yellow", "orange", "red3", "darkred"))
levelplot(reclassras, col.regions = col)

Below is the dput of my raster layer:

 ras=new("RasterLayer"
        , file = new(".RasterFile"
        , name = ""
        , datanotation = "FLT4S"
        , byteorder = "little"
        , nodatavalue = -Inf
        , NAchanged = FALSE
        , nbands = 1L
        , bandorder = "BIL"
        , offset = 0L
        , toptobottom = TRUE
        , blockrows = 4L
        , blockcols = 230L
        , driver = ""
        , open = FALSE
    )
        , data = new(".SingleLayerData"
        , values = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, 0.693928846555399, 0.788672037295368, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, 0.63077312659247, 0.646355947246998, 0.877268680738184, 
    1.18198745233929, 1.17243141777504, 1.16780606010241, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, 0.796574503892096, 0.619565545705973, 0.548990505935034, 
    0.595313378137405, 0.661379946396662, 0.780858688754648, 1.32843871685037, 
    1.3513059907622, 1.47504896477768, 1.33220740188043, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    1.02493198234592, 0.871180733341381, 0.588561527602423, 0.495423050558386, 
    0.398352388696117, 0.609004794796874, 0.757493518742196, 0.968962672868491, 
    1.3989459779932, 1.66210327179263, 1.4993019355018, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.605206815154586, 
    0.542575959157491, 0.509368162877491, 0.461856452801692, 0.543152629728101, 
    0.630122267439296, 0.70810504838076, 0.788478557501378, 0.918580431438071, 
    0.925176992886461, 0.712139151650403, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.523779588981426, 0.497759414675531, 
    0.539521493581999, 0.472379195067506, 0.503370029793095, 0.549265480778097, 
    0.570528210136693, 0.710933566259782, 0.726885712871992, 0.755087833088479, 
    0.692253167927366, 0.632483742020028, 0.572268262363865, 0.438810629423197, 
    0.495519373283201, 0.461307895792857, 0.413954466042644, 0.368257331706444, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.777296738735527, 
    0.750850589920605, 0.513284076851117, 0.491285172798063, 0.555785245510632, 
    0.611268469163931, 0.813189823687993, 0.756674620262126, 0.872121251992992, 
    0.613545590220432, 0.481851214001446, 0.496306521393404, 0.437621615262168, 
    0.339745859876615, 0.303638244461432, 0.311408628670555, 0.307152533981348, 
    0.31488062771456, 0.324014538449246, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, 0.682358704297568, 0.706551558881091, 0.502018311967365, 
    0.456684326929721, 0.473559918237202, 0.463389646751083, 0.441190726838794, 
    0.439217524749229, 0.584294316557062, 0.267633271553189, 0.256528025697032, 
    0.337787793432092, 0.330618969832041, 0.13803984358201, 0.157341965515659, 
    0.25899384267949, 0.217328457675264, 0.242480963818602, 0.272211051701126, 
    0.281644918669069, NA, NA, NA, NA, NA, NA, NA, NA, 0.414616765967516, 
    0.460428280883944, 0.439029889808256, 0.373948128082835, 0.352871572842356, 
    0.357951354005567, 0.328436868901166, 0.203201513096291, 0.141472917108049, 
    0.269096407445964, 0.15745212479733, 0.135179353417107, 0.219985246649717, 
    0.283005986377796, 0.209135929188723, 0.195612120899385, 0.163726230506747, 
    0.117276078938131, 0.169752099589576, 0.20586142557315, 0.244209631644345, 
    NA, NA, NA, NA, NA, 0.214238769725864, 0.208010897733397, 0.222208413054847, 
    0.212686463354896, 0.281732716326432, 0.300708262469288, 0.223204487650159, 
    0.200983714892431, 0.156651839437054, 0.224474592578023, 0.145079279318955, 
    0.137658404085203, 0.196204204670511, 0.157445860015357, 0.205907596393374, 
    0.250666664848486, 0.277186662044126, 0.265355210400489, 0.241808654124976, 
    0.199713317093066, 0.143711490248281, 0.0842822747178765, NA, 
    NA, NA, NA, 0.264092813395827, NA, 0.212441257972578, 0.189725290483582, 
    0.168955415365627, 0.158197543230828, 0.147705597579244, 0.157228804810736, 
    0.211249178305103, 0.222557582448186, 0.215124944446001, 0.210152099165574, 
    0.224764230646078, 0.192500267075076, 0.174923484036373, 0.121073670585186, 
    0.140937204004106, 0.213437474831745, 0.248947340425651, 0.265571783211699, 
    0.266099597629565, 0.254099129610638, 0.225777564711763, 0.178602219399, 
    NA, NA, NA, 0.245068225382459, 0.250977120426067, 0.255618295682899, 
    0.215763680642785, 0.192426673071868, 0.15695069948531, 0.113984884275593, 
    0.132801862169494, 0.166848777379759, 0.115940552527949, 0.157310632213977, 
    0.227022907248424, 0.239855727768449, 0.239340572413914, 0.231675634554819, 
    0.215388496476701, 0.185506053849589, 0.104971870404521, 0.112957653991221, 
    0.184468284077724, 0.222974948120878, 0.234747755547275, 0.240936436264378, 
    0.246124530363775, 0.242871371021741, NA, NA, NA, NA, 0.237419647069358, 
    0.238880206380025, 0.231523511204313, 0.179362897056799, 0.16381508377734, 
    0.133186183020653, 0.0908146529276369, 0.141301676274407, 0.17155039695241, 
    0.176667304881711, 0.192368230921037, 0.21608936753556, 0.226766198129308, 
    0.221609735358686, 0.196435659994756, 0.18030618027393, 0.178648959768383, 
    0.131173639965412, 0.0673928945097901, 0.144030029855376, 0.183644454323076, 
    0.164135425763568, 0.177071512975595, 0.218027665373501, 0.24020227724051, 
    NA, NA, NA, NA, 0.222719673381422, 0.203163737836875, 0.193893900175302, 
    0.173629261933378, 0.118612596801245, 0.120337304279883, 0.132270235949265, 
    0.145957944294342, 0.158947316774427, 0.171811369315789, 0.178481215022077, 
    0.182769116915529, 0.193576475278923, 0.187526186900056, 0.116642925509998, 
    0.0810130524927432, 0.155361056173399, 0.148275096869829, 0.110248050354185, 
    0.150980011296809, 0.149035884104822, 0.0943587027445095, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, 0.155642765186448, 0.165539811602326, 
    0.138858875725954, 0.115966143137369, 0.110762436834703, 0.116558297180592, 
    0.109461897495481, 0.137020886546595, 0.130569369589671, 0.106845763992692, 
    0.139732412594499, 0.167204357520135, 0.121743769239998, 0.0978888268526515, 
    0.161034204706105, 0.182178539628265, 0.179821789305561, 0.183479109899686, 
    0.160540641903203, 0.112272216175425, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, 0.163697841087448, 0.17328205868045, 0.160040552656876, 
    0.134655975429996, 0.12409849785916, 0.107880400167541, 0.0924636872864672, 
    0.103225290747982, 0.0767026155342135, 0.0661780888537736, 0.112966312114504, 
    0.16666404802081, 0.172067566098574, 0.172700784074864, 0.192001569629986, 
    0.206098509476636, 0.210359965210036, 0.209377663322926, 0.197655864616846, 
    0.180297988050893, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.181675191082483, 
    0.176935554759326, 0.16390655974363, 0.154194456563158, 0.142896144640483, 
    0.133243173249838, 0.114015642056713, 0.0928738807683648, 0.116223803463035, 
    0.146600649670514, 0.180171520048675, 0.197023191340036, 0.203375499409087, 
    NA, NA, NA, NA, 0.220951932247611, 0.216562385948588, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.176899006540279, 
    0.169734384672319, 0.164263225996517, 0.143295516102167, 0.13599420407605, 
    NA, 0.177143713627865, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.189498742688049, 
    0.185499135750397, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA)
        , offset = 0
        , gain = 1
        , inmemory = TRUE
        , fromdisk = FALSE
        , isfactor = FALSE
        , attributes = list()
        , haveminmax = TRUE
        , min = 0.0661780888537736
        , max = 1.66210327179263
        , band = 1L
        , unit = ""
        , names = "myfile"
    )
        , legend = new(".RasterLegend"
        , type = character(0)
        , values = logical(0)
        , color = logical(0)
        , names = logical(0)
        , colortable = logical(0)
    )
        , title = character(0)
        , extent = new("Extent"
        , xmin = 73.39696
        , xmax = 96.59696
        , ymin = 33.98298
        , ymax = 49.18298
    )
        , rotated = FALSE
        , rotation = new(".Rotation"
        , geotrans = numeric(0)
        , transfun = function () 
    NULL
    )
        , ncols = 29L
        , nrows = 19L
        , crs = new("CRS"
        , projargs = "+proj=longlat +a=6378140 +b=6356755.288157528 +no_defs"
    )
        , history = list()
        , z = list()
    )

Motorist

dput doesn't work so well for rasters (you should always check that the code you provide runs in a clean R session - it doesn't in this case). You could replace your whole example raster with ras <- raster(matrix(runif(100), nrow=10)). Also, I don't understand your second point (colorkey should be "joined"). – Furness

Answer 1

You can cut your raster, and then specify the colour breaks with at, and the colorkey breaks with a list containing at and labels, passed to the colorkey arg:

    levelplot(cut(ras, 9), col.regions=col, 
              at=0:9, margin=FALSE,
              colorkey=list(labels=list(at=0:8 + 0.5, labels=levels(cut(ras[], 9)))))

Above, we are saying that we want to split ras into 9 equal-width bins. These bins will be denoted by the numbers 1 through 9, and at=0:9 specifies that we want colours to change at values 0 through 9. To label the colorkey correctly, we pass a list called labels, with argument at indicating where we want the labels to be located, and argument labels providing the corresponding labels. Note that you can pass whatever you want to the labels element of the labels list passed to the colorkey argument (e.g. to match the format of your example plot, you might want to use something like labels=list(at=0:8 + 0.5, labels=sub('\\((.+),(.+)]', '>\\1 ~ \\2', levels(cut(ras[], 9))))).

You could instead use ratify to coerce the raster layer to a factor, and set the factor levels to the desired label text, but this can be a bit fiddly if levels are missing.

Furness

Glad you were able to use my dput output. By "joined" I meant the colorkey should be same as what you have provided here. Thanks very much for the wonderful solution. I guess it should be possible to exculsively specify the 9 colors instead of using colorRamp? I will try to specify my own discrete colors. Please let me know how to replace the square brackets with parantheses. Many thanks. – Motorist

@aez849 - the default behaviour of cut is to produce half-open intervals, so round and square brackets mean different things here (round = exclusive, square = inclusive). To replace square with round, you can use labels=list(at=0:8 + 0.5, labels=sub('\\]', ')', levels(cut(ras[], 9)))). You can provide a vector of colours rather than a colorRampPalette to col.regions, but you'll still need to specify the breaks, and provide the location and text for labels. Yep, all the info to reconstruct the raster is in the dput output - it's just not the most useful way to provide the data. – Furness

@jbaums- Many thanks for this very easily applicable solution. My plots look even better now. Lastly (hopefully), I am trying to round the labels to 2 decimal places within the code but keep getting errors. Any quick fix? – Motorist