Error: Input must be a vector, not a <RasterStack> object.

[priyapatel1]

I need some help here, it's unclear to me what I'm doing wrong.

We have a rasterStack object that we are trying to run landscape metrics on. The check_landscape function comes out clear.

This is the error that I'm getting when trying to run landscape metrics on a rasterStack:

Error: Input must be a vector, not a object.

rlang::last_error()
<error/vctrs_error_scalar_type>
Input must be a vector, not a object.
Backtrace:

1. base::$<-(...)
2. vctrs:::stop_scalar_type(...)
3. vctrs:::stop_vctrs(msg, "vctrs_error_scalar_type", actual = x)
   Run rlang::last_trace() to see the full context.

Would appreciate your help asap.

[Nowosad]

@priyapatel1 can you show us the code you are using?

[priyapatel1]

Hi there, here is the code we used:

## Use this to install the package 
#install.packages("landscapemetrics")
#install.packages("Rcpp")
#install.packages("rgdal")

# Load Libraries
library(landscapemetrics)
library(raster)
library(Rcpp)
library(rgdal)
## Set this to where the files are saved. 
setwd("C:/Users/Bryant/Documents/RESEARCH/SoE")

## List of .tif files 
files <- list.files(pattern="\\.tif$")

df_class <- NULL

for (file in files) {
  print(file)
  landtest <- stack(file)
  classtest <- landscapemetrics::check_landscape(landtest)
  print(classtest$n_classes)
  class_level <- calculate_lsm(
    landtest,
    level = "class",
    metric = NULL,
    directions = 8,
    count_boundary = FALSE,
    consider_boundary = FALSE,
    edge_depth = 1,
    cell_center = FALSE,
    classes_max = 9,
    # run with 9 after
    neighbourhood = 8,
    ordered = TRUE,
    verbose = TRUE,
    progress = FALSE
  )

  class_level$filename <- file
  class_level$nclasses <- classtest$n_classes
  df_class <- rbind(class_level, df_class)

}

write.csv(df_class,file = "class_level_perband.csv")

We have a series of multi-band rasters that we need to loop through. Let me know if you want a copy of the .tif as well.

[mhesselbarth]

The code looks good to me. If you can share the .tif (or at least one or two where it fails) that would be great

[priyapatel1]

Hi there - the tif can be found here:

https://drive.google.com/file/d/1wi4JwidehURy1AD_hUJqkSQZC6oKO1vZ/view?usp=sharing

[Nowosad]

@priyapatel1, I was unable to reproduce your problem on our test data. Feel free to reopen the issue if the problem still exist and (if possible) try to create a small reproducible example.

library(landscapemetrics)
library(tibble)
df_class <- NULL
classtest <- landscapemetrics::check_landscape(landscape)
#> Warning: Caution: Coordinate reference system not metric - Units of results
#> based on cellsizes and/or distances may be incorrect.
class_level <- calculate_lsm(
  landscape,
  level = "class",
  metric = NULL,
  directions = 8,
  count_boundary = FALSE,
  consider_boundary = FALSE,
  edge_depth = 1,
  cell_center = FALSE,
  classes_max = 9,
  # run with 9 after
  neighbourhood = 8,
  ordered = TRUE,
  verbose = TRUE,
  progress = FALSE
)
#> Warning: Please use 'check_landscape()' to ensure the input data is valid.
#> Warning: Class 1: PAFRAC = NA for class with < 10 patches
#> Warning: Class 3: PAFRAC = NA for class with < 10 patches
class_level$filename <- "my_file"
class_level$nclasses <- classtest$n_classes
df_class <- rbind(class_level, df_class)

^{Created on 2022-10-07 with reprex v2.0.2}