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
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
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