Sub-sample an existing sample. Four sampling methods are available:
clhs
, balanced
, srs
and strat
.
Usage
sample_existing(
existing,
nSamp,
raster = NULL,
type = "clhs",
access = NULL,
buff_inner = NULL,
buff_outer = NULL,
details = FALSE,
filename = NULL,
overwrite = FALSE,
...
)
Arguments
- existing
sf 'POINT'. Existing plot network.
- nSamp
Numeric. Number of desired samples.
- raster
SpatRaster. Raster to guide the location of the samples. If
type = "clhs"
this raster can also be used to define the population distributions to be used for sampling.- type
Character. A string indicating the type of sampling method to use. Possible values are
"clhs"
,"balanced"
,"srs"
and"strat"
.- access
sf. Road access network - must be lines.
- buff_inner
Numeric. Inner buffer boundary specifying distance from access where plots cannot be sampled.
- buff_outer
Numeric. Outer buffer boundary specifying distance from access where plots can be sampled.
- details
Logical. If
FALSE
(default) output is sf object of systematic samples. IfTRUE
returns a list of sf objects wheretessellation
is the tessellation grid for sampling, andsamples
are the systematic samples.- filename
Character. Path to write output samples.
- overwrite
Logical. Choice to overwrite existing
filename
if it exists.- ...
Additional arguments for the sampling method selected.
Note
When type = "clhs"
or type = "balanced"
all attributes in existing
will be used for sampling.
Remove attributes not indented for sampling' prior to using this algorithm.
See also
Other sample functions:
sample_ahels()
,
sample_balanced()
,
sample_clhs()
,
sample_nc()
,
sample_srs()
,
sample_strat()
,
sample_sys_strat()
,
sample_systematic()
Examples
r <- system.file("extdata", "mraster.tif", package = "sgsR")
mr <- terra::rast(r)
#--- generate an existing sample adn extract metrics ---#
e <- sample_systematic(raster = mr, cellsize = 200)
e <- extract_metrics(existing = e, mraster = mr)
#--- perform clhs (default) sub-sampling ---#
sample_existing(
existing = e,
nSamp = 50
)
#> Sub-sampling based on ALL 'existing' metric distributions. Ensure only attributes of interest are included.
#> Simple feature collection with 50 features and 3 fields
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: 431230.4 ymin: 5337736 xmax: 438491.6 ymax: 5343117
#> Projected CRS: UTM Zone 17, Northern Hemisphere
#> First 10 features:
#> zq90 pzabove2 zsd geometry
#> 133 9.93 77.9 2.50 POINT (432223.2 5340588)
#> 877 14.70 99.7 1.57 POINT (438084.1 5339074)
#> 459 12.30 96.0 2.63 POINT (434996.2 5341864)
#> 375 13.70 82.9 3.60 POINT (433842.4 5338982)
#> 371 22.60 96.7 5.76 POINT (433962.3 5339975)
#> 197 13.20 84.1 3.71 POINT (432284.7 5337760)
#> 782 3.75 7.2 0.79 POINT (437967.8 5343117)
#> 225 10.70 69.0 3.10 POINT (432483.3 5337736)
#> 391 4.47 19.7 1.04 POINT (434256.7 5340745)
#> 410 7.15 79.6 2.10 POINT (434575.2 5341714)
#--- perform balanced sub-sampling ---#
sample_existing(
existing = e,
nSamp = 50,
type = "balanced"
)
#> Simple feature collection with 50 features and 3 fields
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: 431141.3 ymin: 5337719 xmax: 438419.7 ymax: 5343206
#> Projected CRS: UTM Zone 17, Northern Hemisphere
#> First 10 features:
#> zq90 pzabove2 zsd geometry
#> 22 4.97 28.9 1.15 POINT (431206.4 5340509)
#> 35 18.20 93.1 4.61 POINT (431500.9 5341279)
#> 38 6.25 22.7 1.53 POINT (431429 5340683)
#> 45 16.50 91.3 3.78 POINT (431237.2 5339095)
#> 49 15.90 96.9 2.62 POINT (431141.3 5338301)
#> 86 13.90 64.7 4.06 POINT (431874 5341033)
#> 149 11.20 97.0 2.42 POINT (432613.6 5342152)
#> 159 13.80 83.4 3.39 POINT (432373.8 5340166)
#> 202 16.50 77.9 3.93 POINT (433034.6 5342303)
#> 209 10.60 70.9 2.62 POINT (432866.8 5340913)
#--- perform simple random sub-sampling ---#
sample_existing(
existing = e,
nSamp = 50,
type = "srs"
)
#> Simple feature collection with 50 features and 3 fields
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: 431302.3 ymin: 5337749 xmax: 438371.7 ymax: 5343110
#> Projected CRS: UTM Zone 17, Northern Hemisphere
#> First 10 features:
#> zq90 pzabove2 zsd geometry
#> 207 14.30 67.3 3.38 POINT (432914.8 5341310)
#> 764 11.80 86.9 3.21 POINT (437649.4 5342148)
#> 784 5.20 15.9 1.18 POINT (437919.9 5342720)
#> 622 16.30 89.7 3.38 POINT (435708.1 5337749)
#> 618 16.50 90.4 3.95 POINT (435852 5338941)
#> 865 24.30 83.7 7.17 POINT (438371.7 5341457)
#> 33 14.80 90.7 3.15 POINT (431548.8 5341676)
#> 724 9.61 51.8 2.68 POINT (436988.6 5340012)
#> 108 11.70 75.4 3.07 POINT (432120.5 5341406)
#> 830 8.29 88.8 1.70 POINT (437567.1 5338129)