[R-sig-Geo] Raster crosstab output: -1 values?

[Lyndon Estes]

Hi Megan,

Can you give some steps on how you prepared the data before stacking?
Was there any resampling, reprojecting, etc. involved in your forest
cover layer?  I have had similar results with rasters in the past
where NA values were represented by negative numbers.  What might have
happened is a relatively large negative number (in absolute terms) was
resampled down to a small one (in absolute terms) with the default
setting at bilinear, e.g.

resample(x)

But that's just a guess without knowing your processing steps.

Best, Lyndon

On Wed, Dec 19, 2012 at 6:03 PM, Megan Evans <megan.evans at anu.edu.au> wrote:
> Hi everyone,
>
> I'm computing a very large crosstab analysis (using the raster package) for
> around 700 tiles of 25m resolution vegetation raster data. Essentially, I
> want to figure out how much forest is contained within each land use, land
> tenure and jurisdictional boundary (eight Australian States) over a 39 year
> time period (20 years with data).
>
> The land tenure, land use and State layers have all been cut up into the
> same extent, resolution and projection as the forest cover data. I then
> create a raster stack of the forest cover, State and land tenure-use (the
> latter was combined into one raster layer) tiles, and subsequently a
> crosstab. This process is repeated for each tile and year (~700 loops,
> taking a rather long time). The forest cover data (in this particular year -
> 1972) has values of only 0 and 1 (non-forest/forest). However, I'm finding
> in some cases the crosstab output contains data in a "-1" category, despite
> this value not being part of the original forest cover data.
>
> I'm at a loss to explain this; all datasets have the same number of cells,
> resoluton, and no missing data. Would really appreciate any insights!
>
> Cheers, Megan
>
> Data details below:
>
> Forest Cover (ttile):
> class       : RasterLayer
> dimensions  : 16000, 28360, 453760000  (nrow, ncol, ncell)
> resolution  : 0.00025, 0.00025  (x, y)
> extent      : 112.91, 120, -28, -24  (xmin, xmax, ymin, ymax)
> coord. ref. : +proj=longlat +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +no_defs
> data source :
> D:/Analysis/R/Data/forestextent_reg/forest_v8_72_11/sg50/forst72.grd
> names       : layer
> values      : 0, 1  (min, max)
> Raster Attribute Table
>      fields : ID     COUNT
>         min :  0  30065009
>         max :  1 423694991
>
> State (st_tex):
> class       : RasterLayer
> dimensions  : 16000, 28360, 453760000  (nrow, ncol, ncell)
> resolution  : 0.00025, 0.00025  (x, y)
> extent      : 112.91, 120, -28, -24  (xmin, xmax, ymin, ymax)
> coord. ref. : +proj=longlat +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +no_defs
> data source : D:/Analysis/R/Data/sttiles/forest_v8_72_11/stsg50.grd
> names       : states_p
> values      : 8, 8  (min, max)
>
> Land Use/Tenure (lu_ten_tex):
> class       : RasterLayer
> dimensions  : 16000, 28360, 453760000  (nrow, ncol, ncell)
> resolution  : 0.00025, 0.00025  (x, y)
> extent      : 112.91, 120, -28, -24  (xmin, xmax, ymin, ymax)
> coord. ref. : +proj=longlat +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +no_defs
> data source : D:/Analysis/R/Data/lutentiles/forest_v8_72_11/lutensg50.grd
> names       : lu_ten
> values      : 1, 73  (min, max)
> Raster Attribute Table
>      fields : ID       COUNT
>         min :  1 -1816924096
>         max : 73  1681761600
>
> Relevant code:
> # Create raster stack between forestextent, lu and state
>         x <-stack(ttile, lu_ten_tex, st_tex)
>
>         #Crosstab will calculate the frequency of each level (0=non-forest,
> 1=primforest, 2=regforest) in each land use/tenure/state
>         vegfreq <-crosstab(x, digits=0, long=FALSE, progress="text")
>
>> vegfreq
> , , states_p = 8
>
>      lu_ten
> layer         0         1         3        11        13        61        63
> 33
>    0     400975   2059222   2355223  28336430  13144612   2565663 316999241
> 42855
>    1      15814      1098     19824   6497248   3958995    761517  17902798
> 345
>    -1        11      1280       153      3522       393        20     15961
> 0
>      lu_ten
> layer        43        73        23        53        71        51        12
> 22
>    0       8447     16777     64401     50205     19375     17463    334230
> 664199
>    1       1153      7223     66799       995     31825       137    396970
> 126201
>    -1         0         0         0         0         0         0         0
> 0
>      lu_ten
> layer        62         2        32
>    0     310439      1586     13062
>    1     201561        14      2938
>    -1         0         0         0
>
>
>
>
> --
> View this message in context: http://r-sig-geo.2731867.n2.nabble.com/Raster-crosstab-output-1-values-tp7582028.html
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>
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