calculate slope of rast object

Source: R/slope_rast.R

calculate slope of rast object

slope_rast(
  r,
  period = c(2001, 2020),
  outfile = NULL,
  fun = rtrend::slope_mk,
  ...,
  overwrite = FALSE,
  .progress = "text"
)

rast_filter_time(r, period = c(2001, 2020))

Arguments

r

A yearly rast object, which should have time attribute

period

c(year_begin, year_end)

outfile

The path of outputed tiff file. If specified, slope and pvalue will be written into outfile.

fun

the function used to calculate slope, see slope() for details.

...

other parameters ignored

overwrite

logical. If TRUE, outfile is overwritten.

.progress

name of the progress bar to use, see create_progress_bar

Value

A terra rast object, with bands of slope and pvalue.

See also

terra::rast()

Examples

library(rtrend)
library(terra)
#> terra 1.7.55

f <- system.file("rast/MOD15A2_LAI_China_G050_2001-2020.tif", package = "rtrend")
r <- rast(f)
r
#> class       : SpatRaster 
#> dimensions  : 80, 140, 20  (nrow, ncol, nlyr)
#> resolution  : 0.5, 0.5  (x, y)
#> extent      : 70, 140, 15, 55  (xmin, xmax, ymin, ymax)
#> coord. ref. : lon/lat WGS 84 (EPSG:4326) 
#> source      : MOD15A2_LAI_China_G050_2001-2020.tif 
#> names       :      LAI,      LAI,      LAI,     LAI,      LAI,      LAI, ... 
#> min values  : 0.000000, 0.000000, 0.000000, 0.00000, 0.000000, 0.000000, ... 
#> max values  : 5.692542, 5.479348, 5.585326, 5.33587, 5.822826, 5.533152, ... 
#> time (days) : 2001-01-01 to 2020-01-01 
time(r)
#>  [1] "2001-01-01" "2002-01-01" "2003-01-01" "2004-01-01" "2005-01-01"
#>  [6] "2006-01-01" "2007-01-01" "2008-01-01" "2009-01-01" "2010-01-01"
#> [11] "2011-01-01" "2012-01-01" "2013-01-01" "2014-01-01" "2015-01-01"
#> [16] "2016-01-01" "2017-01-01" "2018-01-01" "2019-01-01" "2020-01-01"

slp <- slope_rast(r,
  period = c(2001, 2020), 
  outfile = "LAI_trend.tif", overwrite = TRUE,
  fun = rtrend::slope_mk, .progress = "none"
)
# if you want to show progress, set `.progress = "text"`
slp
#> class       : SpatRaster 
#> dimensions  : 80, 140, 2  (nrow, ncol, nlyr)
#> resolution  : 0.5, 0.5  (x, y)
#> extent      : 70, 140, 15, 55  (xmin, xmax, ymin, ymax)
#> coord. ref. : lon/lat WGS 84 (EPSG:4326) 
#> source(s)   : memory
#> names       :       slope, pvalue 
#> min values  : -0.01830315,      0 
#> max values  :  0.04475858,      1 
plot(slp)


file.remove("LAI_trend.tif")
#> [1] TRUE