[R-sig-Geo] help

[Ahmed Eldeiry]

The attached file contains collected soil salinity samples and extracted
pixels values from Ikonos image.
I am trying to interpolate soil salinity data and use regression models
with the axillary data

I created a grid as follows:
mydata <- read.table("C:............//mydata.txt", header = TRUE)
coordinates(mydata) <- c("x", "y")
diff(sort(unique(coordinates(mydata)[,2])))
diff(sort(unique(coordinates(mydata)[,1])))
bb = bbox(mydata)
mydata.gt = GridTopology(c(bb[1,1],bb[2,1]), c(30,30),
round(c(diff(bb[1,]), diff(bb[2,]))/30) + 1)
plot(mydata)
plot(SpatialGrid(mydata.gt),col='red',add=T)
mydata.sg = SpatialGrid(mydata.gt)
fullgrid(mydata.sg)=F
mydata.grid = SpatialPixelsDataFrame(mydata.sg, data.frame(x = rep(NA,
8*15))

This above grid works fine with simple and ordinary kriging, however, I got
this error when using universal kriging or linear model:

salinity.uk <- krige(salinity~ndvi, mydata, mydata.grid, vt.fit)  #### UK

salinity.lm <- lm(salinity~ndvi, mydata)         #### LM
mydata.grid$pred <- predict(sal.lm, mydata.grid)

*Error in eval(expr, envir, enclos) : object 'ndvi' not found*

Therefore, I created another grid that contains the whole data as follows:

mydata_g <- read.table("C:............//mydata.txt", header = TRUE)
coordinates(mydata_g) <- ~ x+y
rast <- raster(ncol =8, nrow=15)
extent(rast) <- extent(mydata_g)
rasterize(mydata_g, rast, mydata_g$salinity, c(30,30), fun = mean)
gridded(mydata_g) <- TRUE









*Warning messages:1: In points2grid(points, tolerance, round) :  grid has
empty column/rows in dimension 12: In points2grid(points, tolerance, round)
:  grid topology may be corrupt in dimension 13: In points2grid(points,
tolerance, round) :  grid has empty column/rows in dimension 24: In
points2grid(points, tolerance, round) :  grid topology may be corrupt in
dimension 2*

fullgrid(mydata_g) <- F
plot(f40_g)    ### it is empty

I would appreciate if someone could help me how to create a grid that
contains the rest of columns beside x and y coordinates and also displays
only the shape of the field which has the following coordinates
list(x=c(621606,621685,621685,621606,621606),y=c(4211472,4211472,4211396,4211396,4211472))

Best Regards,
Ahmed
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <https://stat.ethz.ch/pipermail/r-sig-geo/attachments/20140707/cf2515a4/attachment.html>
-------------- next part --------------
x	y	salinity	blue	green	red	near	ndvi
621564	4211184	3.6	505	584	501	790	0.22
621592	4211182	4	409	469	319	1025	0.53
621632	4211180	3.6	426	495	347	995	0.48
621650	4211217	4.2	415	452	317	948	0.5
621614	4211219	3.6	416	461	334	950	0.48
621569	4211222	3.1	441	492	374	838	0.38
621571	4211268	4.7	428	480	357	878	0.42
621611	4211265	6.6	417	453	319	981	0.51
621663	4211262	3.8	412	450	311	1014	0.53
621689	4211301	6.2	416	441	308	1000	0.53
621648	4211304	6.1	434	491	369	903	0.42
621608	4211307	6.4	421	482	351	912	0.44
621564	4211310	3.6	430	459	338	931	0.47
621567	4211354	4	414	451	331	923	0.47
621611	4211351	5.4	406	449	321	938	0.49
621653	4211348	7.7	453	514	417	903	0.37
621706	4211344	5.6	423	471	336	976	0.49
621739	4211387	7.4	435	501	399	874	0.37
621693	4211391	10.6	543	675	644	750	0.08
621640	4211394	10.7	463	551	463	822	0.28
621578	4211399	8.2	414	463	350	885	0.43
621564	4211446	3.2	425	474	368	841	0.39
621619	4211441	9.4	439	495	411	690	0.25
621674	4211437	9.2	464	553	482	688	0.18
621727	4211434	8	463	546	461	741	0.23
621774	4211430	4.8	435	498	400	811	0.34
621777	4211476	5.7	444	496	388	751	0.32
621717	4211480	7.2	478	566	513	607	0.08
621666	4211484	7.9	460	549	471	708	0.2
621616	4211488	5.6	417	467	348	784	0.39
621565	4211491	3.1	428	506	395	921	0.4
621624	4211534	7.8	466	541	471	717	0.21
621678	4211530	8.2	514	622	586	670	0.07
621746	4211526	8	501	580	521	609	0.08
621772	4211524	5.2	485	548	449	733	0.24
621770	4211571	3.6	503	559	460	690	0.2
621713	4211576	4.5	471	530	421	716	0.26
621662	4211579	4	475	547	468	691	0.19
621611	4211583	3.8	434	481	382	781	0.34
621566	4211586	3	486	583	491	906	0.3
621556	4211596	3.2	501	638	611	810	0.14
621612	4211592	3.7	446	490	408	722	0.28
621658	4211589	7.9	484	547	455	701	0.21
621712	4211585	5.6	471	526	417	741	0.28
621768	4211581	5.4	510	568	460	699	0.21
621771	4211527	6.5	470	535	403	810	0.34
621720	4211528	9.2	492	582	527	622	0.08
621670	4211531	11.3	497	603	554	667	0.09
621622	4211535	10.8	458	536	445	702	0.22
621569	4211538	5.3	439	481	343	924	0.46
621568	4211483	4	424	487	356	843	0.41
621620	4211479	10.1	425	478	359	796	0.38
621668	4211476	11.5	472	554	478	652	0.15
621719	4211472	10.3	485	565	497	601	0.09
621769	4211469	5	446	499	380	794	0.35
621763	4211398	3.6	425	472	364	898	0.42
621708	4211402	11.9	514	645	582	757	0.13
621660	4211406	11.3	500	597	522	809	0.22
621614	4211409	12.2	471	542	449	813	0.29
621570	4211411	8.5	438	493	392	822	0.35
621563	4211364	4.8	416	469	356	887	0.43
621612	4211360	5.7	423	462	347	887	0.44
621663	4211356	10.1	465	540	444	889	0.33
621710	4211353	7.1	456	526	405	927	0.39
621693	4211299	7.5	415	446	315	984	0.52
621650	4211302	8	427	471	341	923	0.46
621603	4211305	7.4	437	488	369	896	0.42
621572	4211308	4.5	407	445	317	963	0.5
621568	4211260	4.8	437	491	372	833	0.38
621611	4211257	5.1	419	458	322	997	0.51
621662	4211254	4.2	415	451	316	983	0.51
621650	4211208	3.7	411	447	309	950	0.51
621609	4211211	3.4	416	461	323	923	0.48
621573	4211213	3.5	427	467	341	933	0.46
621571	4211193	3.5	441	505	404	851	0.36
621610	4211190	4	432	491	363	926	0.44
621640	4211188	4.7	429	482	377	871	0.4
621628	4211173	4.6	409	452	302	1137	0.58
621599	4211176	3.8	415	463	320	1016	0.52
621565	4211177	4.2	552	688	657	772	0.08