Applies the voxels_counting function on a grid base point cloud.
stand_counting(
cloud,
xy.res,
z.res = NULL,
points.min = NULL,
min_size,
edge_sizes = NULL,
length_out = 10,
bootstrap = FALSE,
R = NULL,
progress = TRUE,
parallel = FALSE,
threads = NULL
)A data.table of a point cloud with xyz coordinates in the first three columns.
A positive numeric vector describing the grid resolution of the xy coordinates to perform.
A positive numeric vector of length 1 describing the vertical resolution. If z.res = NULL vertical profiles are not used.
A positive numeric vector of length 1 minimum number of points to retain a sub-grid.
A positive numeric vector of length 1 describing the minimum cube edge length to perform. This is required if edge_sizes = NULL.
A positive numeric vector describing the edge length of the different cubes to perform within each subgrid when z.res = NULL. If edge_sizes = NULL, it uses the maximum range of values for the xyz coordinates.
A positive interger of length 1 indicating the number of different edge lengths to use for each subgrid. This is required if edge_sizes = NULL.
Logical. If TRUE, it computes a bootstrap on the H index calculations. FALSE as default.
A positive integer of length 1 indicating the number of bootstrap replicates. This need to be used if bootstrap = TRUE.
Logical, if TRUE displays a graphical progress bar. TRUE as default.
Logical, if TRUE it uses a parallel processing for the voxelization. FALSE as default.
An integer >= 0 describing the number of threads to use. This need to be used if parallel = TRUE.
A data.table with the summary of the voxels per grid created with their features.
data(pc_tree)
#Applying stand_counting.
# \donttest{
stand_counting(pc_tree, xy.res = c(4, 4), min_size = 3)
#> Estimating stand_counting
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#> X Y Edge.X Edge.Y Edge.Z N_voxels Volume Surface
#> 1: 8.63575 -1.53375 6.036600 6.036600 6.036600 1 219.97696 36.440539
#> 2: 8.63575 -1.53375 4.093419 4.093419 4.093419 2 137.17931 16.756080
#> 3: 8.63575 -1.53375 4.424126 4.424126 4.424126 2 173.18582 19.572887
#> 4: 8.63575 -1.53375 4.781550 4.781550 4.781550 2 218.64324 22.863219
#> 5: 8.63575 -1.53375 5.167850 5.167850 5.167850 2 276.03221 26.706676
#> 6: 8.63575 -1.53375 5.585360 5.585360 5.585360 2 348.48451 31.196245
#> 7: 8.63575 -1.53375 3.242369 3.242369 3.242369 8 272.69518 42.051837
#> 8: 8.63575 -1.53375 3.504320 3.504320 3.504320 8 344.27159 49.121029
#> 9: 8.63575 -1.53375 3.787433 3.787433 3.787433 8 434.63520 57.378598
#> 10: 8.63575 -1.53375 3.000000 3.000000 3.000000 9 243.00000 36.000000
#> 11: 8.63575 2.46625 3.800350 3.800350 3.800350 1 54.88718 14.442662
#> 12: 8.63575 2.46625 3.421197 3.421197 3.421197 2 80.08744 11.704591
#> 13: 8.63575 2.46625 3.512283 3.512283 3.512283 2 86.65597 12.336132
#> 14: 8.63575 2.46625 3.605794 3.605794 3.605794 2 93.76325 13.001748
#> 15: 8.63575 2.46625 3.701794 3.701794 3.701794 2 101.45344 13.703279
#> 16: 8.63575 2.46625 3.000000 3.000000 3.000000 4 108.00000 18.000000
#> 17: 8.63575 2.46625 3.079872 3.079872 3.079872 4 116.85785 18.971220
#> 18: 8.63575 2.46625 3.161870 3.161870 3.161870 4 126.44219 19.994843
#> 19: 8.63575 2.46625 3.246051 3.246051 3.246051 4 136.81261 21.073698
#> 20: 8.63575 2.46625 3.332474 3.332474 3.332474 4 148.03358 22.210764
#> 21: 12.63575 -1.53375 3.881850 3.881850 3.881850 1 58.49467 15.068760
#> 22: 12.63575 -1.53375 3.665795 3.665795 3.665795 2 98.52232 13.438055
#> 23: 12.63575 -1.53375 3.772276 3.772276 3.772276 2 107.35949 14.230068
#> 24: 12.63575 -1.53375 3.562320 3.562320 3.562320 3 135.61884 25.380247
#> 25: 12.63575 -1.53375 3.000000 3.000000 3.000000 4 108.00000 18.000000
#> 26: 12.63575 -1.53375 3.087141 3.087141 3.087141 4 117.68730 19.060885
#> 27: 12.63575 -1.53375 3.176814 3.176814 3.176814 4 128.24352 20.184297
#> 28: 12.63575 -1.53375 3.269092 3.269092 3.269092 4 139.74660 21.373920
#> 29: 12.63575 -1.53375 3.364049 3.364049 3.364049 4 152.28148 22.633657
#> 30: 12.63575 -1.53375 3.461766 3.461766 3.461766 4 165.94071 23.967641
#> 31: 12.63575 2.46625 3.272350 3.272350 3.272350 1 35.04122 10.708274
#> 32: 12.63575 2.46625 3.000000 3.000000 3.000000 2 54.00000 9.000000
#> 33: 12.63575 2.46625 3.029106 3.029106 3.029106 2 55.58700 9.175481
#> 34: 12.63575 2.46625 3.058494 3.058494 3.058494 2 57.22065 9.354383
#> 35: 12.63575 2.46625 3.088167 3.088167 3.088167 2 58.90230 9.536774
#> 36: 12.63575 2.46625 3.118128 3.118128 3.118128 2 60.63337 9.722721
#> 37: 12.63575 2.46625 3.148380 3.148380 3.148380 2 62.41532 9.912294
#> 38: 12.63575 2.46625 3.178925 3.178925 3.178925 2 64.24964 10.105562
#> 39: 12.63575 2.46625 3.209766 3.209766 3.209766 2 66.13787 10.302600
#> 40: 12.63575 2.46625 3.240907 3.240907 3.240907 2 68.08159 10.503478
#> X Y Edge.X Edge.Y Edge.Z N_voxels Volume Surface
#> Density_mean Density_sd H Hmax Equitavility Negentropy
#> 1: 1129.0173 NA 0.000000000 0.0000000 NaN 0.00000000
#> 2: 1227.6738 490.3642 0.652714053 0.6931472 0.94166733 0.04043313
#> 3: 1050.9947 726.8000 0.568302928 0.6931472 0.81988782 0.12484425
#> 4: 899.7421 879.8931 0.430004503 0.6931472 0.62036536 0.26314268
#> 5: 770.2568 892.4793 0.303336761 0.6931472 0.43762244 0.38981042
#> 6: 659.4063 900.3550 0.087163900 0.6931472 0.12575093 0.60598328
#> 7: 489.1820 427.6987 1.769505113 2.0794415 0.85095208 0.30993643
#> 8: 418.7819 475.6247 1.573421589 2.0794415 0.75665584 0.50601995
#> 9: 358.5135 551.4770 1.188607837 2.0794415 0.57159954 0.89083370
#> 10: 507.9259 450.8237 1.838350512 2.1972246 0.83666937 0.35887406
#> 11: 1123.2001 NA 0.000000000 0.0000000 NaN 0.00000000
#> 12: 692.9759 952.3469 0.074159041 0.6931472 0.10698888 0.61898814
#> 13: 657.4994 913.7950 0.049608033 0.6931472 0.07156926 0.64353915
#> 14: 623.8392 874.0840 0.029470720 0.6931472 0.04251726 0.66367646
#> 15: 591.9021 834.0831 0.013096540 0.6931472 0.01889431 0.68005064
#> 16: 450.6111 585.2601 0.817029145 1.3862944 0.58936195 0.56926522
#> 17: 427.5424 622.7369 0.688428257 1.3862944 0.49659602 0.69786610
#> 18: 405.6546 646.6090 0.562173598 1.3862944 0.40552253 0.82412076
#> 19: 384.8874 664.5126 0.419316150 1.3862944 0.30247267 0.96697821
#> 20: 365.1833 676.8233 0.257410815 1.3862944 0.18568265 1.12888355
#> 21: 896.4905 NA 0.000000000 0.0000000 NaN 0.00000000
#> 22: 502.6397 699.7898 0.045494984 0.6931472 0.06563539 0.64765220
#> 23: 474.6639 667.4997 0.019330851 0.6931472 0.02788852 0.67381633
#> 24: 354.8429 576.3660 0.196023146 1.0986123 0.17842796 0.90258914
#> 25: 375.2500 530.7591 0.641665079 1.3862944 0.46286351 0.74462928
#> 26: 354.3644 528.6871 0.569650394 1.3862944 0.41091590 0.81664397
#> 27: 334.6413 521.3135 0.516605101 1.3862944 0.37265181 0.86968926
#> 28: 316.0160 512.7884 0.466511522 1.3862944 0.33651693 0.91978284
#> 29: 298.4272 507.4900 0.401308295 1.3862944 0.28948274 0.98498607
#> 30: 281.8175 503.5746 0.316780028 1.3862944 0.22850849 1.06951433
#> 31: 464.5006 NA 0.000000000 0.0000000 NaN 0.00000000
#> 32: 276.3333 368.9526 0.127525682 0.6931472 0.18398067 0.56562150
#> 33: 271.0485 366.3661 0.106159937 0.6931472 0.15315641 0.58698724
#> 34: 265.8647 364.8019 0.077368810 0.6931472 0.11161960 0.61577837
#> 35: 260.7800 361.8290 0.053454634 0.6931472 0.07711873 0.63969255
#> 36: 255.7926 357.6726 0.034771762 0.6931472 0.05016505 0.65837542
#> 37: 250.9006 352.1162 0.025079802 0.6931472 0.03618251 0.66806738
#> 38: 246.1021 346.7814 0.013233745 0.6931472 0.01909226 0.67991344
#> 39: 241.3954 340.6983 0.007943344 0.6931472 0.01145982 0.68520384
#> 40: 236.7787 334.5864 0.003545891 0.6931472 0.00511564 0.68960129
#> Density_mean Density_sd H Hmax Equitavility Negentropy
# }
#Applying stand_counting using bootstrap in the H index.
# \donttest{
stand_counting(pc_tree,
xy.res = c(4, 4),
min_size = 3,
bootstrap = TRUE,
R = 10)
#> Estimating stand_counting
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|
|======================= | 33%
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#> X Y Edge.X Edge.Y Edge.Z N_voxels Volume Surface
#> 1: 8.63575 -1.53375 6.036600 6.036600 6.036600 1 219.97696 36.440539
#> 2: 8.63575 -1.53375 4.093419 4.093419 4.093419 2 137.17931 16.756080
#> 3: 8.63575 -1.53375 4.424126 4.424126 4.424126 2 173.18582 19.572887
#> 4: 8.63575 -1.53375 4.781550 4.781550 4.781550 2 218.64324 22.863219
#> 5: 8.63575 -1.53375 5.167850 5.167850 5.167850 2 276.03221 26.706676
#> 6: 8.63575 -1.53375 5.585360 5.585360 5.585360 2 348.48451 31.196245
#> 7: 8.63575 -1.53375 3.242369 3.242369 3.242369 8 272.69518 42.051837
#> 8: 8.63575 -1.53375 3.504320 3.504320 3.504320 8 344.27159 49.121029
#> 9: 8.63575 -1.53375 3.787433 3.787433 3.787433 8 434.63520 57.378598
#> 10: 8.63575 -1.53375 3.000000 3.000000 3.000000 9 243.00000 36.000000
#> 11: 8.63575 2.46625 3.800350 3.800350 3.800350 1 54.88718 14.442662
#> 12: 8.63575 2.46625 3.421197 3.421197 3.421197 2 80.08744 11.704591
#> 13: 8.63575 2.46625 3.512283 3.512283 3.512283 2 86.65597 12.336132
#> 14: 8.63575 2.46625 3.605794 3.605794 3.605794 2 93.76325 13.001748
#> 15: 8.63575 2.46625 3.701794 3.701794 3.701794 2 101.45344 13.703279
#> 16: 8.63575 2.46625 3.000000 3.000000 3.000000 4 108.00000 18.000000
#> 17: 8.63575 2.46625 3.079872 3.079872 3.079872 4 116.85785 18.971220
#> 18: 8.63575 2.46625 3.161870 3.161870 3.161870 4 126.44219 19.994843
#> 19: 8.63575 2.46625 3.246051 3.246051 3.246051 4 136.81261 21.073698
#> 20: 8.63575 2.46625 3.332474 3.332474 3.332474 4 148.03358 22.210764
#> 21: 12.63575 -1.53375 3.881850 3.881850 3.881850 1 58.49467 15.068760
#> 22: 12.63575 -1.53375 3.665795 3.665795 3.665795 2 98.52232 13.438055
#> 23: 12.63575 -1.53375 3.772276 3.772276 3.772276 2 107.35949 14.230068
#> 24: 12.63575 -1.53375 3.562320 3.562320 3.562320 3 135.61884 25.380247
#> 25: 12.63575 -1.53375 3.000000 3.000000 3.000000 4 108.00000 18.000000
#> 26: 12.63575 -1.53375 3.087141 3.087141 3.087141 4 117.68730 19.060885
#> 27: 12.63575 -1.53375 3.176814 3.176814 3.176814 4 128.24352 20.184297
#> 28: 12.63575 -1.53375 3.269092 3.269092 3.269092 4 139.74660 21.373920
#> 29: 12.63575 -1.53375 3.364049 3.364049 3.364049 4 152.28148 22.633657
#> 30: 12.63575 -1.53375 3.461766 3.461766 3.461766 4 165.94071 23.967641
#> 31: 12.63575 2.46625 3.272350 3.272350 3.272350 1 35.04122 10.708274
#> 32: 12.63575 2.46625 3.000000 3.000000 3.000000 2 54.00000 9.000000
#> 33: 12.63575 2.46625 3.029106 3.029106 3.029106 2 55.58700 9.175481
#> 34: 12.63575 2.46625 3.058494 3.058494 3.058494 2 57.22065 9.354383
#> 35: 12.63575 2.46625 3.088167 3.088167 3.088167 2 58.90230 9.536774
#> 36: 12.63575 2.46625 3.118128 3.118128 3.118128 2 60.63337 9.722721
#> 37: 12.63575 2.46625 3.148380 3.148380 3.148380 2 62.41532 9.912294
#> 38: 12.63575 2.46625 3.178925 3.178925 3.178925 2 64.24964 10.105562
#> 39: 12.63575 2.46625 3.209766 3.209766 3.209766 2 66.13787 10.302600
#> 40: 12.63575 2.46625 3.240907 3.240907 3.240907 2 68.08159 10.503478
#> X Y Edge.X Edge.Y Edge.Z N_voxels Volume Surface
#> Density_mean Density_sd H Hmax Equitavility Negentropy
#> 1: 1129.0173 NA 0.000000000 0.0000000 NaN 0.00000000
#> 2: 1227.6738 490.3642 0.652714053 0.6931472 0.94166733 0.04043313
#> 3: 1050.9947 726.8000 0.568302928 0.6931472 0.81988782 0.12484425
#> 4: 899.7421 879.8931 0.430004503 0.6931472 0.62036536 0.26314268
#> 5: 770.2568 892.4793 0.303336761 0.6931472 0.43762244 0.38981042
#> 6: 659.4063 900.3550 0.087163900 0.6931472 0.12575093 0.60598328
#> 7: 489.1820 427.6987 1.769505113 2.0794415 0.85095208 0.30993643
#> 8: 418.7819 475.6247 1.573421589 2.0794415 0.75665584 0.50601995
#> 9: 358.5135 551.4770 1.188607837 2.0794415 0.57159954 0.89083370
#> 10: 507.9259 450.8237 1.838350512 2.1972246 0.83666937 0.35887406
#> 11: 1123.2001 NA 0.000000000 0.0000000 NaN 0.00000000
#> 12: 692.9759 952.3469 0.074159041 0.6931472 0.10698888 0.61898814
#> 13: 657.4994 913.7950 0.049608033 0.6931472 0.07156926 0.64353915
#> 14: 623.8392 874.0840 0.029470720 0.6931472 0.04251726 0.66367646
#> 15: 591.9021 834.0831 0.013096540 0.6931472 0.01889431 0.68005064
#> 16: 450.6111 585.2601 0.817029145 1.3862944 0.58936195 0.56926522
#> 17: 427.5424 622.7369 0.688428257 1.3862944 0.49659602 0.69786610
#> 18: 405.6546 646.6090 0.562173598 1.3862944 0.40552253 0.82412076
#> 19: 384.8874 664.5126 0.419316150 1.3862944 0.30247267 0.96697821
#> 20: 365.1833 676.8233 0.257410815 1.3862944 0.18568265 1.12888355
#> 21: 896.4905 NA 0.000000000 0.0000000 NaN 0.00000000
#> 22: 502.6397 699.7898 0.045494984 0.6931472 0.06563539 0.64765220
#> 23: 474.6639 667.4997 0.019330851 0.6931472 0.02788852 0.67381633
#> 24: 354.8429 576.3660 0.196023146 1.0986123 0.17842796 0.90258914
#> 25: 375.2500 530.7591 0.641665079 1.3862944 0.46286351 0.74462928
#> 26: 354.3644 528.6871 0.569650394 1.3862944 0.41091590 0.81664397
#> 27: 334.6413 521.3135 0.516605101 1.3862944 0.37265181 0.86968926
#> 28: 316.0160 512.7884 0.466511522 1.3862944 0.33651693 0.91978284
#> 29: 298.4272 507.4900 0.401308295 1.3862944 0.28948274 0.98498607
#> 30: 281.8175 503.5746 0.316780028 1.3862944 0.22850849 1.06951433
#> 31: 464.5006 NA 0.000000000 0.0000000 NaN 0.00000000
#> 32: 276.3333 368.9526 0.127525682 0.6931472 0.18398067 0.56562150
#> 33: 271.0485 366.3661 0.106159937 0.6931472 0.15315641 0.58698724
#> 34: 265.8647 364.8019 0.077368810 0.6931472 0.11161960 0.61577837
#> 35: 260.7800 361.8290 0.053454634 0.6931472 0.07711873 0.63969255
#> 36: 255.7926 357.6726 0.034771762 0.6931472 0.05016505 0.65837542
#> 37: 250.9006 352.1162 0.025079802 0.6931472 0.03618251 0.66806738
#> 38: 246.1021 346.7814 0.013233745 0.6931472 0.01909226 0.67991344
#> 39: 241.3954 340.6983 0.007943344 0.6931472 0.01145982 0.68520384
#> 40: 236.7787 334.5864 0.003545891 0.6931472 0.00511564 0.68960129
#> Density_mean Density_sd H Hmax Equitavility Negentropy
#> H_boot_mean H_boot_sd Equitavility_boot Negentropy_boot
#> 1: 0.0000000 0.00000000 NaN 0.00000000
#> 2: 0.6729306 0.02131013 0.9708337 0.02021656
#> 3: 0.6432095 0.06446929 0.9279551 0.04993770
#> 4: 0.6142044 0.12710999 0.8861096 0.07894280
#> 5: 0.5762041 0.18829632 0.8312867 0.11694313
#> 6: 0.3901555 0.31938123 0.5628755 0.30299164
#> 7: 1.8107582 0.10958978 0.8707906 0.26868338
#> 8: 1.6242944 0.13331083 0.7811205 0.45514713
#> 9: 1.3546930 0.26986746 0.6514696 0.72474855
#> 10: 1.8420557 0.20561569 0.8383557 0.35516887
#> 11: 0.0000000 0.00000000 NaN 0.00000000
#> 12: 0.2598555 0.29899968 0.3748922 0.43329170
#> 13: 0.3713776 0.33917491 0.5357846 0.32176957
#> 14: 0.2285737 0.32058619 0.3297621 0.46457352
#> 15: 0.2851168 0.35117664 0.4113366 0.40803038
#> 16: 1.0342028 0.19417507 0.7460196 0.35209153
#> 17: 0.9160282 0.22023388 0.6607747 0.47026612
#> 18: 0.7983731 0.30946703 0.5759044 0.58792130
#> 19: 0.9179467 0.36180768 0.6621585 0.46834771
#> 20: 0.6853832 0.45846077 0.4943995 0.70091117
#> 21: 0.0000000 0.00000000 NaN 0.00000000
#> 22: 0.4340863 0.33444616 0.6262542 0.25906088
#> 23: 0.5583839 0.28410591 0.8055777 0.13476327
#> 24: 0.5699357 0.37770617 0.5187778 0.52867657
#> 25: 0.8394854 0.18153200 0.6055607 0.54680894
#> 26: 0.7735209 0.34335352 0.5579774 0.61277341
#> 27: 0.6037548 0.13993045 0.4355171 0.78253952
#> 28: 0.6719169 0.26052246 0.4846856 0.71437742
#> 29: 0.6446617 0.27836866 0.4650251 0.74163263
#> 30: 0.4334034 0.21644852 0.3126345 0.95289096
#> 31: 0.0000000 0.00000000 NaN 0.00000000
#> 32: 0.4103364 0.29810870 0.5919903 0.28281075
#> 33: 0.3996536 0.30936944 0.5765782 0.29349362
#> 34: 0.5084137 0.29744921 0.7334859 0.18473351
#> 35: 0.4372702 0.33033581 0.6308475 0.25587702
#> 36: 0.2322844 0.31802554 0.3351155 0.46086279
#> 37: 0.2255000 0.32270720 0.3253278 0.46764716
#> 38: 0.4891731 0.32842939 0.7057277 0.20397403
#> 39: 0.3505453 0.36113413 0.5057299 0.34260192
#> 40: 0.3483465 0.36345179 0.5025578 0.34480064
#> H_boot_mean H_boot_sd Equitavility_boot Negentropy_boot
# }