Errors with RasterIO #712
Description
Dear all, I've created this issue since I have some questions/doubts regarding the behaviour of RasterIO. For example:
library(stars)
#> Loading required package: abind
#> Loading required package: sf
#> Linking to GEOS 3.11.2, GDAL 3.7.2, PROJ 9.3.0; sf_use_s2() is TRUE
W <- st_bbox(c(
xmin = 11.9264894188302, ymin = 35.4930391676817,
xmax = 15.6509648037934, ymax = 38.8119746624118
), crs = "OGC:CRS84")
(dt <- read_stars(
.x = "C:/Users/user/OneDrive - Politecnico di Milano/data-NDVI/c_gls_NDVI300_202301010000_GLOBE_OLCI_V2.0.1.nc",
sub = "NDVI"
))
#> NDVI,
#> stars_proxy object with 1 attribute in 1 file(s):
#> $NDVI
#> [1] "[...]/c_gls_NDVI300_202301010000_GLOBE_OLCI_V2.0.1.nc:NDVI"
#>
#> dimension(s):
#> from to offset delta refsys x/y
#> x 1 120960 -180 0.002976 WGS 84 [x]
#> y 1 47040 80 -0.002976 WGS 84 [y]
#> time 1 1 2023-01-01 UTC NA POSIXctNow, my understanding is that the input data (i.e. the .nc file) is an array-like object where the first two dimensions (i.e. x and y) have 120960 and 47040 elements, respectively, and we have only 1 time stamp. If I try to subset the region of interest, I get the following.
dt[W]
#> stars_proxy object with 1 attribute in 1 file(s):
#> $NDVI
#> [1] "[...]/c_gls_NDVI300_202301010000_GLOBE_OLCI_V2.0.1.nc:NDVI"
#>
#> dimension(s):
#> from to offset delta refsys x/y
#> x 64488 65740 -180 0.002976 WGS 84 [x]
#> y 13840 14955 80 -0.002976 WGS 84 [y]
#> time 1 1 2023-01-01 UTC NA POSIXctNow, based on my understanding of the second vignette included in the package, I started trying to replicate a similar spatial filter using the RasterIO options and got the following error:
read_stars(
.x = "C:/Users/user/OneDrive - Politecnico di Milano/data-NDVI/c_gls_NDVI300_202301010000_GLOBE_OLCI_V2.0.1.nc",
sub = "NDVI",
RasterIO = list(
nXOff = 64488,
nYOff = 13840
)
)
#> Error in CPL_read_gdal(as.character(x), as.character(options), as.character(driver), : the dims contain negative valuesFurthermore, when I specify also the size of the new objects that I would like to read, I get a different error
read_stars(
.x = "C:/Users/user/OneDrive - Politecnico di Milano/data-NDVI/c_gls_NDVI300_202301010000_GLOBE_OLCI_V2.0.1.nc",
sub = "NDVI",
RasterIO = list(
nXOff = 64488,
nXSize = 1253,
nYOff = 13840,
nYSize = 1116
)
)
#> Warning in CPL_read_gdal(as.character(x), as.character(options),
#> as.character(driver), : GDAL Error 5: C:\Users\user\OneDrive - Politecnico di
#> Milano\data-NDVI\c_gls_NDVI300_202301010000_GLOBE_OLCI_V2.0.1.nc: Access window
#> out of range in RasterIO(). Requested (64487,13839) of size 1253x1116 on
#> raster of 512x512.
#> Error in eval(expr, envir, enclos): read failureI’m even more confused now since I don’t understand why it says my raster is 512 x 512…
The .nc file used in this reprex is related to the NDVI data shared by CLMS: https://land.copernicus.eu/en/products/vegetation/normalised-difference-vegetation-index-v2-0-300m#download.
The file can be downloaded from the Provider’s manifest of Copernicus Land Monitoring Service at the following link: https://globalland.vito.be/download/manifest/ndvi_300m_v2_10daily_netcdf/manifest_clms_global_ndvi_300m_v2_10daily_netcdf_latest.txt
It corresponds to the first set of observations recorded during 2023 and the following is the direct link: https://globalland.vito.be/download/netcdf/ndvi/ndvi_300m_v2_10daily/2023/20230101/c_gls_NDVI300_202301010000_GLOBE_OLCI_V2.0.1.nc
Warning: each file listed in that txt file is approximately 1.5/2GB.
I’m sorry for the “hard-to-reproduce” bug, but I couldn’t replicate it with artificial data.
Created on 2024-10-05 with reprex v2.0.2
Session info
sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
#> version R version 4.3.1 (2023-06-16 ucrt)
#> os Windows 11 x64 (build 22631)
#> system x86_64, mingw32
#> ui RTerm
#> language (EN)
#> collate English_United Kingdom.utf8
#> ctype English_United Kingdom.utf8
#> tz Europe/Rome
#> date 2024-10-05
#> pandoc 3.2 @ C:/Program Files/RStudio/resources/app/bin/quarto/bin/tools/ (via rmarkdown)
#>
#> ─ Packages ───────────────────────────────────────────────────────────────────
#> package * version date (UTC) lib source
#> abind * 1.4-8 2024-09-12 [1] CRAN (R 4.3.1)
#> class 7.3-22 2023-05-03 [2] CRAN (R 4.3.1)
#> classInt 0.4-10 2023-09-05 [1] CRAN (R 4.3.1)
#> cli 3.6.3 2024-06-21 [1] CRAN (R 4.3.1)
#> DBI 1.2.3 2024-06-02 [1] CRAN (R 4.3.1)
#> digest 0.6.35 2024-03-11 [1] CRAN (R 4.3.3)
#> e1071 1.7-16 2024-09-16 [1] CRAN (R 4.3.1)
#> evaluate 0.24.0 2024-06-10 [1] CRAN (R 4.3.3)
#> fastmap 1.2.0 2024-05-15 [1] CRAN (R 4.3.3)
#> fs 1.6.4 2024-04-25 [1] CRAN (R 4.3.3)
#> glue 1.7.0 2024-01-09 [1] CRAN (R 4.3.2)
#> htmltools 0.5.8.1 2024-04-04 [1] CRAN (R 4.3.3)
#> KernSmooth 2.23-21 2023-05-03 [2] CRAN (R 4.3.1)
#> knitr 1.48 2024-07-07 [1] CRAN (R 4.3.3)
#> lifecycle 1.0.4 2023-11-07 [1] CRAN (R 4.3.2)
#> magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.3.1)
#> proxy 0.4-27 2022-06-09 [1] CRAN (R 4.3.1)
#> purrr 1.0.2 2023-08-10 [1] CRAN (R 4.3.1)
#> R.cache 0.16.0 2022-07-21 [1] CRAN (R 4.3.1)
#> R.methodsS3 1.8.2 2022-06-13 [1] CRAN (R 4.3.1)
#> R.oo 1.25.0 2022-06-12 [1] CRAN (R 4.3.1)
#> R.utils 2.12.2 2022-11-11 [1] CRAN (R 4.3.1)
#> Rcpp 1.0.13 2024-07-17 [1] CRAN (R 4.3.1)
#> reprex 2.0.2 2022-08-17 [1] CRAN (R 4.3.1)
#> rlang 1.1.4 2024-06-04 [1] CRAN (R 4.3.1)
#> rmarkdown 2.27 2024-05-17 [1] CRAN (R 4.3.3)
#> rstudioapi 0.16.0 2024-03-24 [1] CRAN (R 4.3.1)
#> sessioninfo 1.2.2 2021-12-06 [1] CRAN (R 4.3.1)
#> sf * 1.0-18 2024-10-04 [1] Github (r-spatial/sf@6f247a5)
#> stars * 0.6-7 2024-10-05 [1] Github (r-spatial/stars@ec1f849)
#> styler 1.10.2 2023-08-29 [1] CRAN (R 4.3.1)
#> units 0.8-5.4 2024-06-03 [1] local
#> vctrs 0.6.5 2023-12-01 [1] CRAN (R 4.3.2)
#> withr 3.0.1 2024-07-31 [1] CRAN (R 4.3.3)
#> xfun 0.45 2024-06-16 [1] CRAN (R 4.3.3)
#> yaml 2.3.9 2024-07-05 [1] CRAN (R 4.3.3)
#>
#> [1] C:/Users/user/AppData/Local/R/win-library/4.3
#> [2] C:/Program Files/R/R-4.3.1/library
#>
#> ──────────────────────────────────────────────────────────────────────────────EDIT: I just noticed that a similar issue was already discussed in #678 but I still get an error even if I'm using the github version of the package. Sorry, but I didn't find that issue sooner.
EDIT2: I also run some tests with read_ncdf but with, IMO, it also returns a confusing output (not necessarily related to the R package since it just complains about the CRS). I can add them here, but they probably deserve a separate issue so I don't mix too many things.