download geographic data
License: GNU General Public License v3.0
R package with data sets used in the material on the https://rspatial.org website to teach spatial data analysis with R.
You can install the package like this
remotes::install_github("rspatial/rspatial")
Hello,
I know that the new version 4.1. is expected to be released next month (April 2022). I wanted to point out that the Kyrgyzstan border needs an update. Well, in fact it needs it for quite a long time. On the picture below, in yellow is a shapefile from the national dataset, in blue the GADM lvl 1 (but that concerns all levels obviously). You can see that over the eastern border there are small areas that do not belong to Kyrgyzstan, but China.
Here is google maps for a comparison, showing borders following the national dataset.
I am just asking to include this in the upcoming update. Thank you!
In the 'sp_occurrence' help file (not run) examples, plot(gs) tries to plot an entire dataframe, which results in Error in plot.new() : figure margins too large. I think it should be plot(gs$lon, gs$lat).
It would also be very useful to provide a usage example for 'args'. From the argument description, it's difficult to uderstand how exactly it should be specified. For example, is it possible to download only records where the Year column is either NA or within a given range of values, or more recent than a given year?
Cheers and thanks again for the great package!
The documentation for sp_occurrence suggests using an * as a wildcard:
Line 40 in 6c78465
This doesn't work for me, and after some searching I think the API doesn't support wildcards https://discourse.gbif.org/t/searching-on-catalogue-number/3202
If I try the example from https://rspatial.org/sdm/2_sdm_occdata.html#importing-occurrence-data I get zero results:
library(geodata)
sp_occurrence("solanum", "acaule*", download=FALSE)[1] 0
Similarly,
sp_occurrence("solanum", "*", download=FALSE)[1] 0
Perhaps I don't understand, as I'm not familiar with the GBIF API. But if this should work, I think there's something missing in the documentation, and possibly also the rspatial tutorial, to explain it.
Unless there is something I missed, and a good reason not to include them, the function cmip6_world() currently does not allow the download of future climate data from WorldClim for the period 2081–2100. They are however available, as can be seen from the description page or from a (randomly selected) download page.
It all comes down to modify the .check_cmip6() function (line 150 in the worldclim.R file) with:
stopifnot(time %in% c("2021-2040", "2041-2060", "2061-2080", "2081-2100"))
Hiya!
Running this roads_us <- geodata::osm("United States", "highways", path = tempdir())
returns this error cannot open URL 'https://geodata.ucdavis.edu/geodata/osm/highways/USA_highways.gpkg': HTTP status was '404 Not Found'
It looks like USA_highways.gpkg doesn't exist in https://geodata.ucdavis.edu/geodata/osm/highways/
Thanks for the great package!
When running cmip6_tile(), no matter what you provide as the resargument (even values that supposedly aren't allowed), it downloads the layers at 0.5 arc-min resolution:
wc.fut <- geodata::cmip6_tile('MRI-ESM2-0',
'585',
'2061-2080',
var = 'bioc',
res = 2.5, # but tried also res=10, res=115, etc.
path = tempdir(),
lon = 80.69787,
lat = 7.621672)
res(wc.fut)
# [1] 0.008333333 0.008333333
A fix would be greatly appreciated, especially because the download at this resolution takes a looong time :)
Regards!
Looks like a newer version of terra no longer supports characters for the function trim resulting in the following error and affecting a number of the geodata functions
country <- "Kenya"
### works
### geodata_0.3-1 terra_1.3-9
> toupper(trim(country[1]))
[1] "KENYA"
### doesn't work
### geodata_0.3-1 terra_1.4-3
> toupper(trim(country[1]))
Error in (function (classes, fdef, mtable) :
unable to find an inherited method for function ‘trim’ for signature ‘"character"’
Hi,
I've used world() to download world maps at all five different resolutions. I notice that the countries available are different with each resolution. There are 252 polygons at resolution 2:
> w2
class : SpatVector
geometry : polygons
dimensions : 252, 2 (geometries, attributes)
extent : -180, 180, -90, 83.65833 (xmin, xmax, ymin, ymax)
coord. ref. : +proj=longlat +datum=WGS84 +no_defs
names : GID_0 NAME_0
type : <chr> <chr>
values : ABW Aruba
AFG Afghanistan
AGO Angola
But only 231 at the highest resolution. In particular, the following countries are missing:
> w2$NAME_0[! w2$NAME_0 %in% w1$NAME_0]
[1] "Gibraltar"
[2] "Monaco"
[3] "Maldives"
[4] "Marshall Islands"
[5] "Tuvalu"
[6] "United States Minor Outlying Islands"
[7] "Paracel Islands"
I checked the polygons, and Gibraltar isn't subsumed within Spain, it's just missing from the resolution = 1 map. It would make sense if the highest resolution maps included some countries that were too small to represent in the lower resolution layers, but this seems to be the opposite - shouldn't everything that appears in the second highest resolution map also appear in the highest resolution map?
I'm not sure if this is a geodata issue, or something upstream at GADM?
I want to download West Africa map and wonder if possible with geodata. Otherwise is it possible to download many individual countries at the same time or download 2 contiguous countries or merge them?
This was previously working fine (except for the 'geo' argument, mentioned in this other issue), but now it's returning only one row, even if the console output says there are more:
occ_gbif <- sp_occurrence(genus = "Daboia", species = "mauritanica")
# trying URL 'https://api.gbif.org/v1/occurrence/search?scientificname=Daboia+mauritanica&limit=1&coordinatestatus=true'
# Content type 'application/json' length 3922 bytes
# ==================================================
# downloaded 3922 bytes
#
# 105 records found
# 0-105
# 105 records downloaded
nrow(occ_gbif)
# [1] 1
str(occ_gbif)
# 'data.frame': 1 obs. of 73 variables:
# $ acceptedScientificName : chr "Daboia mauritanica Gray, 1849"
# $ acceptedTaxonKey : int 5789511
# [...]
I often like to have students use geodata::sp_occurrence instead of the more widely used rgbif functions, because it's simpler to install and the resulting object is simpler to handle. However, this breaks downstream code that uses the original GBIF column names "decimalLongitude" and "decimalLatitude", and makes it difficult to have everyone use whichever function they prefer and then use the remaining scripts seamlessly. Is there a good reason for geodata::sp_occurrence to change these names to 'lon' and 'lat'? Could an option be provided for keeping the original column names? Cheers
Hi I was trying to run gadm function in geodata package, but since yesterday, it's been returnning connection errors:
Error in file(con, "r") :
cannot open the connection to 'https://geodata.ucdavis.edu/gadm/gadm4.1.txt'
In addition: Warning message:
In file(con, "r") :
URL 'https://geodata.ucdavis.edu/gadm/gadm4.1.txt': Timeout of 6000 seconds was reached
trying URL 'https://geodata.ucdavis.edu/gadm/gadm4.1/pck/gadm41_MOZ_1_pk.rds'
Error in utils::download.file(url = url, destfile = filename, quiet = quiet, :
cannot open URL 'https://geodata.ucdavis.edu/gadm/gadm4.1/pck/gadm41_MOZ_1_pk.rds'
download failed
Here's my code:
moz <- geodata::gadm(country="MOZ", level=1, path=tempdir())
Not sure if this is because the serve is down or sometihng else?
Download fails when using
file_path <- paste0(dirname(here::here()), "/silvoarable_review/DATASET.FROM.SCRIPT/")
geodata::worldclim_global(var = 'bio', res = 2.5, path = file_path)
Error message:
trying URL 'https://geodata.ucdavis.edu/climate/worldclim/2_1/base/wc2.1_2.5m_bio.zip'
Content type 'application/zip' length 658405521 bytes (627.9 MB)
===========
downloaded 149.5 MB
Warning: downloaded length 156811264 != reported length 658405521Warning: URL 'https://geodata.ucdavis.edu/climate/worldclim/2_1/base/wc2.1_2.5m_bio.zip': Timeout of 60 seconds was reachedError in utils::download.file(url = url, destfile = filename, quiet = quiet, :
download from 'https://geodata.ucdavis.edu/climate/worldclim/2_1/base/wc2.1_2.5m_bio.zip' failed
Error in .downloadDirect(paste0(.wcurl, "base/", zip), pzip, ...) :
download failed
However, the old function from the raster package seems to work fine (?):
raster::getData(name = 'worldclim', var = 'bio', res = 2.5, path = file_path)
Warning: getData will be removed in a future version of raster
. Please use the geodata package insteadtrying URL 'https://biogeo.ucdavis.edu/data/climate/worldclim/1_4/grid/cur/bio_2-5m_bil.zip'
Content type 'application/zip' length 129319755 bytes (123.3 MB)
==================================================
downloaded 123.3 MB
class : RasterStack
dimensions : 3600, 8640, 31104000, 19 (nrow, ncol, ncell, nlayers)
resolution : 0.04166667, 0.04166667 (x, y)
extent : -180, 180, -60, 90 (xmin, xmax, ymin, ymax)
crs : +proj=longlat +datum=WGS84 +no_defs
names : bio1, bio2, bio3, bio4, bio5, bio6, bio7, bio8, bio9, bio10, bio11, bio12, bio13, bio14, bio15, ...
min values : -278, 9, 8, 64, -86, -559, 53, -278, -501, -127, -506, 0, 0, 0, 0, ...
max values : 319, 213, 96, 22704, 489, 258, 725, 376, 365, 382, 289, 10577, 2437, 697, 265, ...
Currently, geodata only has a function for downloading the Gridded Population of the World (GPW) population density data via: geodata::population(). Is it possible to get the GPW population count data added as a function, or perhaps an argument within the population() call? This would be very helpful for some reproducible code I am trying to write.
Greetings,
I have terra version 1.5-17 installed on a macOS ventura 13.3.1. I want to install the geodata package using the following command:
remotes::install_github("rspatial/geodata"),
but it requires version 1.6.41 of terra package. I was unable to update the terra package to the version required by geodata. Any help?
Best regards,
KD
The function worldclim_tile, to download climate data from WorldClim (version 2.1) in tiles, does not return the correct WorldClim bioclimatic layers.
worldclim_tile gets layers from UCDavis (https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/tile/) and not from WorldClim directly (https://www.worldclim.org/data/worldclim21.html), so seems like something happened when preparing the tiles.
Here an example:
bioclim <- worldclim_tile(
var = "bio",
res = 0.5,
lon = 51.19113,
lat = 25.28342,
path = tempdir(),
version = "2.1"
)
summary(bioclim)
tile_32_wc2.1_30s_bio_13 tile_32_wc2.1_30s_bio_14
Min. :32.94 Min. : 33.4
1st Qu.:43.99 1st Qu.:146.4
Median :51.59 Median :444.0
Mean :56.53 Mean :425.7
3rd Qu.:70.71 3rd Qu.:651.2
Max. :91.41 Max. :961.8
NA's :31810 NA's :31810
Note the values for tile_32_wc2.1_30s_bio_13 (Precipitation of Wettest Month) are lower than the values for tile_32_wc2.1_30s_bio_14 (Precipitation of Driest Month). The layers downloaded directly from WorldClim seem to be OK.
Session Info:
R version 4.2.0 (2022-04-22 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19045)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.utf8 LC_CTYPE=English_United States.utf8
[3] LC_MONETARY=English_United States.utf8 LC_NUMERIC=C
[5] LC_TIME=English_United States.utf8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] mapview_2.11.0.9006 geodata_0.5-8 sf_1.0-14 terra_1.7-39 janitor_2.2.0
[6] lubridate_1.9.2 forcats_1.0.0 stringr_1.5.0 dplyr_1.1.2 purrr_1.0.1
[11] readr_2.1.4 tidyr_1.3.0 tibble_3.2.1 ggplot2_3.4.2 tidyverse_2.0.0
loaded via a namespace (and not attached):
[1] tidyselect_1.2.0 lattice_0.20-45 snakecase_0.11.0 colorspace_2.1-0 vctrs_0.6.2
[6] generics_0.1.3 stats4_4.2.0 htmltools_0.5.6 base64enc_0.1-3 utf8_1.2.3
[11] rlang_1.1.1 e1071_1.7-13 pillar_1.9.0 glue_1.6.2 withr_2.5.0
[16] DBI_1.1.3 sp_2.0-0 lifecycle_1.0.3 munsell_0.5.0 gtable_0.3.3
[21] raster_3.6-23 htmlwidgets_1.6.2 codetools_0.2-18 tzdb_0.4.0 fastmap_1.1.1
[26] crosstalk_1.2.0 class_7.3-20 fansi_1.0.4 leafem_0.2.0 Rcpp_1.0.11
[31] KernSmooth_2.23-20 satellite_1.0.4 scales_1.2.1 classInt_0.4-9 leaflet_2.1.2
[36] hms_1.1.3 png_0.1-8 digest_0.6.33 stringi_1.7.12 grid_4.2.0
[41] cli_3.6.1 tools_4.2.0 magrittr_2.0.3 proxy_0.4-27 pkgconfig_2.0.3
[46] timechange_0.2.0 rstudioapi_0.15.0 R6_2.5.1 units_0.8-3 compiler_4.2.0
Hi, we are trying to use the geodata package but when attempting to get worldclim data, the following error appears:
The geodata server is down for maintenance.
It is expected to be back online on April 13, 2023.
It's past that date, so we're not sure what is going on.
Thanks!
Hi,
I'm starting to switch my code over to geodata from raster::getData. Comparing the data collected by each function, I was surprised that the layers didn't match - variables are recorded on different scales, with different extents, and different ranges.
After looking at the URLs for each function, I see now that getData downloads WorldClim version 1.4, and worldclim_global downloads version 2.1. Perhaps you could add this to the help page for worldclim_global? It might help others making the switch and finding the results of their analyses have changed.
Thanks all your work building and sharing these tools, they're indispensable for our work.
Best,
Tyler
Functions that download raster maps, such as elevation* and population, download a .zip file and then save a .tif file alongside it. It seems that the .zip is not needed further, so I'd suggest adding unlink(pzip) at the end of these functions, to save users disk space.
Hello I am writing from GBIF.
I am doing a small outreach to those R packages that use GBIF occurrence search.
Under the terms of the GBIF data user agreement, users who download data agree to cite a DOI. Good citation also rewards data-publishing institutions and individuals by reinforcing the value of sharing open data and demonstrating its impact to their funders.
https://docs.ropensci.org/rgbif/articles/gbif_citations.html
https://www.gbif.org/citation-guidelines
Unfortunately, when using the occurrence search, rather than the occurrence download, one does not receive a citable DOI.
Because occurrence search is easier for some users to use, we have created something called derived datasets, which allows users to create a citable DOI after they have pulled the data from the GBIF public API.
https://www.gbif.org/derived-dataset
As a package maintainer, it would be appreciated by GBIF, if you could remind users in the documentation or with warning messages to cite the GBIF mediated data properly, perhaps by linking to one of these articles:
https://docs.ropensci.org/rgbif/articles/gbif_citations.html
https://www.gbif.org/citation-guidelines
https://www.gbif.org/derived-dataset
Also important to remind users to keep the datasetKey column because this allows for proper attribution to the original data providers.
The code below doesn't complain, but silently downloads only the first country:
countries <- gadm(country = c("Portugal", "Spain", "France"), level = 1, path = tempdir())
unique(countries$COUNTRY)
# [1] "Portugal"
It would be helpful to emit at least a warning message about that. Cheers!
If we misspell a taxon name, sp_occurrence adequately returns 0 when download=FALSE, i.e. zero records on GBIF for the specified taxon. But if download=TRUE (the default), a puzzling error message appears:
sp_occurrence(genus = "Pathera", species = "leo", download = FALSE)
# [1] 0
sp_occurrence(genus = "Pathera", species = "leo")
# Error in sp_occurrence(genus = "Pathera", species = "leo") :
start <= end is not TRUE
Could it instead emit a message indicating what the problem is? Cheers!
I am using cmip6_tile of geodata but download failed error is issued:
bio10 <- cmip6_tile(lon=-15, lat=15, model="CNRM-CM6-1", ssp="585", time="2061-2080", var="bio", res=10, path=tempdir())
trying URL 'https://geodata.ucdavis.edu/cmip6/tiles/CNRM-CM6-1/ssp585/wc2.1_30s_bioc_CNRM-CM6-1_ssp585_2061-2080_tile-30.tif'
download failed
Any idea on solving this?
Trying to run the elevation_3s() fails with:
Error in utils::download.file(url = url, destfile = filename, quiet = quiet, :
cannot open URL 'https://srtm.csi.cgiar.org/wp-content/uploads/files/srtm_5x5/TIFF/srtm_44_06.zip'
download failed
When trying to access the download URL directly I get:
NET::ERR_CERT_DATE_INVALID
Subject: srtm.csi.cgiar.org
Issuer: R3
Expires on: 2 Nov 2022
Is there anyone we can contact to address this problem, and install a new certificate?
I've been finding that the worldclim_countries and worldclim_tile functions always download the 30-arcmin version of rasters despite specifying res to be something else. This happens even after I clean out the previously downloaded files and restart R.
library(geodata)
bios <- geodata::worldclim_country('MDG', var='bio', res=10, path=getwd())
bios
class : SpatRaster
dimensions : 1740, 900, 19 (nrow, ncol, nlyr)
resolution : 0.008333333, 0.008333333 (x, y)
extent : 43, 50.5, -26, -11.5 (xmin, xmax, ymin, ymax)
coord. ref. : lon/lat WGS 84 (EPSG:4326)
source : MDG_wc2.1_30s_bio.tif
names : wc2.1~bio_1, wc2.1~bio_2, wc2.1~bio_3, wc2.1~bio_4, wc2.1~bio_5, wc2.1~bio_6, ...
min values : 11.29167, 6.12500, 54.04762, 90.91286, 18.6, 2.0, ...
max values : 28.05000, 16.55833, 77.26189, 327.99295, 36.8, 21.2, ...
Same thing for:
worldclim_tileHowever, worldclim_global does get the correct resolution rasters when res is specified.
> sessionInfo()
R version 4.2.1 (2022-06-23 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 18363)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.utf8 LC_CTYPE=English_United States.utf8 LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C LC_TIME=English_United States.utf8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] geodata_0.4-11 terra_1.6-17
loaded via a namespace (and not attached):
[1] compiler_4.2.1 tools_4.2.1 Rcpp_1.0.9 codetools_0.2-18
Error in utils::download.file(url = url, destfile = filename, quiet = quiet, :
cannot open URL 'https://geodata.ucdavis.edu/climate/worldclim/2_1/base/wc2.1_5m_elev.zip'
In addition: Warning message:
In utils::download.file(url = url, destfile = filename, quiet = quiet, :
InternetOpenUrl failed: 'A connection with the server could not be established'
Error in .downloadDirect(theurl, pzip, unzip = TRUE, ...) :
download failed
Sorry for taking your time. However, I have the following problem when using the soil_word function:
For example:
gph <- soil_world(var="bdod", depth=100, path=tempdir())
Report an error:
Error in soil_world(var = "bdod", depth = 100, path = tempdir()) :
file not yet available: bdod_60-100cm_mean_30s.tif
The above error occurs when the depth is 100 or 200. This warning does not appear when the parameter depth is set to other depths.
Reinstalling the package didn't work either. Looking forward to your reply.
Hello,
The functions below are currently returning "no such file or directory" or "invalid 'url' argument" errors. Maybe their files have been renamed or (re)moved in the server?
elev <- elevation_global(res = 10, path = tempdir())
pop <- population(year = 2020, res = 10, path = tempdir())
Hi
I am trying to adapt the example from here (https://rstudio-pubs-static.s3.amazonaws.com/224303_df34f170cd9144cda6477ae8232887f7.html), which uses the CMIP5 data (now obsolete), to the latest WorldClim models (http://www.worldclim.org/) using the new CMIP6 data,
For retrieving the data, I am using the geodata package.
Here is the script as far as I could run it:
[edited to just show the relevant part]
library(geodata)
# Get climate data
currentEnv <- worldclim_global(var="bio", res=2.5, path=getwd())
currentEnv <- dropLayer(currentEnv, c("bio2", "bio3", "bio4", "bio10", "bio11", "bio13", "bio14", "bio15"))
#Error in (function (classes, fdef, mtable) :
# unable to find an inherited method for function ‘dropLayer’ for signature ‘"SpatRaster"’
Could a working example of using the latest CMIP6 data with geodata be provided?
Dear Robert,
By now 'geodata' already downloads a great set of environmental variables, but it's still missing the marine environment. When you get a chance for another enhancement, it would be great if 'geodata' could also access the Bio-ORACLE (https://bio-oracle.org/) dataset of present and future marine variables.
Cheers!
When downloading 30 arcsecond WorldClim data using the cmip6_world function, the resulting raster files are empty (no data?). All values are NA or NaN.
future <- cmip6_world(model = "CanESM5",
ssp = "585",
time = "2061-2080",
var = "bioc",
res = 0.5,
path = ".")
summary(future)
wc2_1 wc2_2 wc2_3 wc2_4 wc2_5 wc2_6 wc2_7
Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
Median : NA Median : NA Median : NA Median : NA Median : NA Median : NA Median : NA
Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
NA's :100352 NA's :100352 NA's :100352 NA's :100352 NA's :100352 NA's :100352 NA's :100352
wc2_8 wc2_9 wc2_10 wc2_11 wc2_12 wc2_13 wc2_14
Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
Median : NA Median : NA Median : NA Median : NA Median : NA Median : NA Median : NA
Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
NA's :100352 NA's :100352 NA's :100352 NA's :100352 NA's :100352 NA's :100352 NA's :100352
wc2_15 wc2_16 wc2_17 wc2_18 wc2_19
Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
Median : NA Median : NA Median : NA Median : NA Median : NA
Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
NA's :100352 NA's :100352 NA's :100352 NA's :100352 NA's :100352
I am trying to run the following lines of code:
cur.tmax <- cmip6_world(ssp="585", model=cur.gcm, time="2041-2060", var="tmax", res=2.5)
cur.tmin <- cmip6_world(ssp="585", model=cur.gcm, time="2041-2060", var="tmin", res=2.5)
and receive the following error:
trying URL 'https://geodata.ucdavis.edu/cmip6/2.5m/GFDL-ESM4/ssp585/wc2.1_2.5m_tmax_GFDL-ESM4_ssp585_2041-2060.tif'
download failed
(equivalent error for tmin).
Downloading those files directly from the URL also does not work. The precipitation variable works okay, all other tmin and tmax work for the specified time period and ssp using other GCMs.
When the country argument for worldclim_country() has length >1, only the first element is used, and the other are silently ignored.
tavg <- geodata::worldclim_country(country = c("Luxembourg", "Netherlands", "Belgium"), var = "tavg", path = tempdir())
terra::plot(tavg[[1]])
terra::plot(vect(system.file("ex/lux.shp", package="terra")), add = TRUE) # only Luxembourg was taken
I think there should be at least a warning about this, or (ideally) the function could take more than one country at a time.
It works for a smaller country like Iceland:
wc <- worldclim_country("Iceland", "bio", ".") wc
class : SpatRaster
dimensions : 840, 1920, 12 (nrow, ncol, nlyr)
resolution : 0.008333333, 0.008333333 (x, y)
extent : -28, -12, 60, 67 (xmin, xmax, ymin, ymax)
coord. ref. : lon/lat WGS 84 (EPSG:4326)
source : ISL_wc2.1_30s_tavg.tif
names : ISL_wavg_1, ISL_wavg_2, ISL_wavg_3, ISL_wavg_4, ISL_wavg_5, ISL_wavg_6, ...
min values : -8.8, -9.8, -11.2, -10.2, -6.1, -2.7, ...
max values : 6.3, 5.9, 5.4, 5.9, 7.7, 10.8, ...
while
wc4 <- worldclim_country("US", "bio", ".") wc4
class : SpatRaster
dimensions : 6540, 43140, 19 (nrow, ncol, nlyr)
resolution : 0.008333333, 0.008333333 (x, y)
extent : -179.5, 180, 18.5, 73 (xmin, xmax, ymin, ymax)
coord. ref. : lon/lat WGS 84 (EPSG:4326)
source : USA_wc2.1_30s_bio.tif
names : wc2.1bio_1, wc2.1bio_2, wc2.1bio_3, wc2.1bio_4, wc2.1bio_5, wc2.1bio_6, ...
Notice the lack of min and max values and the extent that doesn't make sense. If I take the summary, it is nothing but NaNs
summary(wc4)
wc2.1_30s_bio_1 wc2.1_30s_bio_2 wc2.1_30s_bio_3
Min. : NA Min. : NA Min. : NA
1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
Median : NA Median : NA Median : NA
Mean :NaN Mean :NaN Mean :NaN
3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
Max. : NA Max. : NA Max. : NA
NA's :100812 NA's :100812 NA's :100812
wc2.1_30s_bio_4 wc2.1_30s_bio_5 wc2.1_30s_bio_6
Min. : NA Min. : NA Min. : NA
1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
Median : NA Median : NA Median : NA
Mean :NaN Mean :NaN Mean :NaN
3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
Max. : NA Max. : NA Max. : NA
NA's :100812 NA's :100812 NA's :100812
wc2.1_30s_bio_7 wc2.1_30s_bio_8 wc2.1_30s_bio_9
Min. : NA Min. : NA Min. : NA
1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
Median : NA Median : NA Median : NA
Mean :NaN Mean :NaN Mean :NaN
3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
Max. : NA Max. : NA Max. : NA
NA's :100812 NA's :100812 NA's :100812
wc2.1_30s_bio_10 wc2.1_30s_bio_11 wc2.1_30s_bio_12
Min. : NA Min. : NA Min. : NA
1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
Median : NA Median : NA Median : NA
Mean :NaN Mean :NaN Mean :NaN
3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
Max. : NA Max. : NA Max. : NA
NA's :100812 NA's :100812 NA's :100812
wc2.1_30s_bio_13 wc2.1_30s_bio_14 wc2.1_30s_bio_15
Min. : NA Min. : NA Min. : NA
1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
Median : NA Median : NA Median : NA
Mean :NaN Mean :NaN Mean :NaN
3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
Max. : NA Max. : NA Max. : NA
NA's :100812 NA's :100812 NA's :100812
wc2.1_30s_bio_16 wc2.1_30s_bio_17 wc2.1_30s_bio_18
Min. : NA Min. : NA Min. : NA
1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
Median : NA Median : NA Median : NA
Mean :NaN Mean :NaN Mean :NaN
3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
Max. : NA Max. : NA Max. : NA
NA's :100812 NA's :100812 NA's :100812
wc2.1_30s_bio_19
Min. : NA
1st Qu.: NA
Median : NA
Mean :NaN
3rd Qu.: NA
Max. : NA
NA's :100812
Warning message:
[summary] used a sample
The 'geo' argument says "only records that have a georeference (longitude and latitude values) will be downloaded", but this doesn't seem to be the case:
gf <- sp_occurrence(genus = "Daboia", species = "mauritanica", geo = F)
gt <- sp_occurrence(genus = "Daboia", species = "mauritanica", geo = T)
all.equal(gf, gt) # TRUE
gt[ , c("lon", "lat")] # NA coordinates still there
Cheers!
All geodata functions (at least all the several ones I've tried) have been giving 'Couldn't connect to server' errors since yesterday. Looks like the server is down?
soil_ph <- soil_world(var = "phh2o", depth = 5, stat = "mean", path = tempdir())
# Error in file(con, "r") :
# cannot open the connection to 'https://geodata.ucdavis.edu/geodata/soil/soilgrids/files.txt'
# In addition: Warning message:
# In file(con, "r") :
# URL 'https://geodata.ucdavis.edu/geodata/soil/soilgrids/files.txt': status was 'Couldn't connect to server'
gadm(country="FRA", level=1, path=tempdir())
# Error in file(con, "r") :
# cannot open the connection to 'https://geodata.ucdavis.edu/gadm/gadm3.6.txt'
# In addition: Warning message:
# In file(con, "r") :
# URL 'https://geodata.ucdavis.edu/gadm/gadm3.6.txt': status was 'Couldn't connect to server'
The "Usage" section of the gadm() help file says level=1 by default, but the function fails if level isn't provided:
countries <- gadm(country = "Portugal", path = tempdir())
Error in gadm(country = "Portugal", path = tempdir()) :
provide a "level=" argument; levels can be 0, 1, or 2 for most countries, and higher for some
...whereas for world() the "Usage" defaults are working as expected. Cheers
Hi I'm trying to get the soil_world data, specifically trying to map soil classification in the Mediterranean and Anatolian regions.
no matter the soil type I'm getting:
file not yet available: Gleysols_30s.tif
Could you consider possibility to add procedure for downloading and processing rasters from EarthEnv, namely "Global 1-km Consensus Land Cover"?
This resource provides raster not very fine resolution in compare with ESA WorldCover, and there is no descete classification into particular class. It provides set of 12 quantative rasters, each of which represents the probability of a land area being in one of these classes.
This resource is widely used in research, related article DOI: 10.1111/geb.12182 has 353 citations.
Hello,
Considering function soil_af_isda(), the URLs to download some of the variables appear to be broken, namely: bdr, clay, C.tot, N.tot, sand, silt and texture. All others variables are working as expected.
Thanks for your generosity.
This was working fine with 'geodata' version 0.4.1, but after updating to 0.4.3, world() now returns an object with no geometries or attributes:
world(resolution = 5, level = 0, path = tempdir())
The same thing is happening for other values of 'resolution' too. gadm() seems to keep working normally, though.
I am able to get the center latitude and longitude of each US county and Canadian census geographic unit (CGU). However, there are some false counties that arise through the process, particularly in the Great Lakes region. In this region, there are some random polygons within the Great Lakes (state/international borders) that produce these false counties. Is there a way to remove these aquatic polygons so that I only get the central latitude and longitude of the land polygons?
library(ggplot2)
library(dplyr)
library(geodata)
library(sf)
# Gets the polygons of each US county and Canadian CGU
aa <- gadm(country = c('CAN', 'USA'), level = 2, path=tempdir()) %>%
st_as_sf()
# Gets the central latitude and longitude of each county and CGU
centroids_aa <- aa %>%
st_centroid(of_largest_polygon = TRUE)
# Map of centroids (there are obviously incorrect counties and CGUs for sites within the Great Lakes)
ggplot() +
geom_sf(data = aa,
mapping = aes(geometry = geometry),
color = "black") +
geom_sf(data = centroids_aa,
mapping = aes(geometry = geometry),
color = "black",
fill = 'red',
shape = 21,
size = 2) +
coord_sf(xlim = c(-93, -81.5), ylim = c(41.5, 50), expand = F) +
theme_bw() +
theme(plot.margin = grid::unit(c(2,2,0,2), "mm"),
text = element_text(size = 16),
axis.text.x = element_text(size = 14, color = "black"),
axis.text.y = element_text(size = 14, color = "black"),
panel.grid.major = element_blank())
I'm using worldclim_tile() to obtain Bioclim layers at 0.5-min resolution for the first time, and I've run into what seems to be incorrect labeling of the layers. Running
BClim <- worldclim_tile(var="bio", res=0.5, lat=33.75, lon=-118, path="data/")
Returns a RasterStack with layers labeled in order from 1 to 19. However, the values in those layers don't align with anything like what they should be, given the identity of the variables. I first noticed it in comparing bio12 (annual precipitation) and bio13 (precip in the wettest month) — the former should, arithmetically, always be larger than the latter. However, the range of values for the bio12 layer in the stack downloaded above is about 5 to 25, and the range for the bio13 layer is about 26 to 66. (Squinting at hist() outputs to get those.) Subtracting the bio13 layer values from bio12 layer values gets me between about -54 and -8.
Looking across the 19 layers with plot() shows ranges of values that look like they should correspond to Bioclim variables, but not the ones labeled.
plot(BClim)
As one final check, I went back to getData() from raster, which pulls down WoldClim 1.4 instead of 2.1, and obtained values that make much more sense for the labeled variables.
BClim2 <- getData(name="worldclim", var="bio", res=0.5, lat=33.75, lon=-118, path="data/")
plot(BClim2)
Unable to download spam crop data -
`z <- geodata::crop_spam(crop = "whea", path = tempdir(), var = "harv_area")
`trying URL 'https://s3.amazonaws.com/mapspam/2010/v1.1/geotiff/spam2010v1r1_global_harv_area.geotiff.zip'
download failed
Dear Robert,
I just realised that one of the GCMs (among 8 of them I checked), has a totally different range of data (seems rescaled) than the current time (also compared to the other GCMs) which would really cause an issue in climate change studies (projections). The problematic GCM model is "BCC-CSM2-MR". I checked several others, c("CanESM5", "CNRM-CM6-1","CNRM-ESM2-1", "IPSL-CM6A-LR", "MIROC-ES2L", "MIROC6", "MRI-ESM2-0"), and they were OK.
Cheers,
Babak
Not a big deal, but the functions with a 'path' argument throw an error if "dir.exists(path) is not TRUE". Unless there's a reason otherwise, it would be useful to add them something like if(!dir.exists(path)) dir.create(path, recursive = TRUE)
NAME_1, VARNAME_1, NL_NAME_1, TYPE_1 columns are left empty for England at administrative level 1 - consistent issue across GADM versions and resolution level.
I'm running a GIS practical using geodata and had an odd issue crop up twice - once myself during testing and once from a student. The cmip6_files.txt file used in .check_cmip6 somehow got truncated: I don't know the mechanism by which this happened but the resulting empty file then causes the cmip6_* commands to fail with:
utils::read.table(tmpfile, sep = "_") :Of course the ideal solution is to find out what truncated it - I don't think it is anything I or the student did as it is quite an obscure file to accidentally truncate - but maybe .check_cmip6 could defensively wrap the file load in a try statement?
Lines 184 to 195 in 35c7cc8
Based on the help file, I believe I've specified all of the inputs correctly, and the function does not seem to be able to retrieve any of these files:
cmip6_tile(-105, 70, "CanESM5", "245", "2041-2060", "bioc", path=tempdir(), res = 2.5)
trying URL 'https://geodata.ucdavis.edu/cmip6/tiles/CanESM5/ssp245/wc2.1_30s_bioc_CanESM5_ssp245_2041-2060_tile-3.tif'
Error in utils::download.file(url = url, destfile = filename, quiet = quiet, :
cannot open URL 'https://geodata.ucdavis.edu/cmip6/tiles/CanESM5/ssp245/wc2.1_30s_bioc_CanESM5_ssp245_2041-2060_tile-3.tif'
In addition: Warning messages:
1: In utils::download.file(url = url, destfile = filename, quiet = quiet, :
downloaded length 0 != reported length 282
2: In utils::download.file(url = url, destfile = filename, quiet = quiet, :
cannot open URL 'https://geodata.ucdavis.edu/cmip6/tiles/CanESM5/ssp245/wc2.1_30s_bioc_CanESM5_ssp245_2041-2060_tile-3.tif': HTTP status was '404 Not Found'
Error in .downloadDirect(turl, outfname[i], ...) : download failed
cmip6_tile(-105, 70, "CanESM5", "245", "2041-2060", "bioc", path=tempdir(), res = 10)
trying URL 'https://geodata.ucdavis.edu/cmip6/tiles/CanESM5/ssp245/wc2.1_30s_bioc_CanESM5_ssp245_2041-2060_tile-3.tif'
Error in utils::download.file(url = url, destfile = filename, quiet = quiet, :
cannot open URL 'https://geodata.ucdavis.edu/cmip6/tiles/CanESM5/ssp245/wc2.1_30s_bioc_CanESM5_ssp245_2041-2060_tile-3.tif'
In addition: Warning messages:
1: In utils::download.file(url = url, destfile = filename, quiet = quiet, :
downloaded length 0 != reported length 282
2: In utils::download.file(url = url, destfile = filename, quiet = quiet, :
cannot open URL 'https://geodata.ucdavis.edu/cmip6/tiles/CanESM5/ssp245/wc2.1_30s_bioc_CanESM5_ssp245_2041-2060_tile-3.tif': HTTP status was '404 Not Found'
Error in .downloadDirect(turl, outfname[i], ...) : download failed
cmip6_tile(-60, 45, "CanESM5", "245", "2041-2060", "bioc", path=tempdir(), res = 10)
trying URL 'https://geodata.ucdavis.edu/cmip6/tiles/CanESM5/ssp245/wc2.1_30s_bioc_CanESM5_ssp245_2041-2060_tile-17.tif'
Error in utils::download.file(url = url, destfile = filename, quiet = quiet, :
cannot open URL 'https://geodata.ucdavis.edu/cmip6/tiles/CanESM5/ssp245/wc2.1_30s_bioc_CanESM5_ssp245_2041-2060_tile-17.tif'
In addition: Warning messages:
1: In utils::download.file(url = url, destfile = filename, quiet = quiet, :
downloaded length 0 != reported length 282
2: In utils::download.file(url = url, destfile = filename, quiet = quiet, :
cannot open URL 'https://geodata.ucdavis.edu/cmip6/tiles/CanESM5/ssp245/wc2.1_30s_bioc_CanESM5_ssp245_2041-2060_tile-17.tif': HTTP status was '404 Not Found'
Error in .downloadDirect(turl, outfname[i], ...) : download failed
cmip6_tile(0, 0, "CanESM5", "245", "2041-2060", "bioc", path=tempdir(), res = 10)
trying URL 'https://geodata.ucdavis.edu/cmip6/tiles/CanESM5/ssp245/wc2.1_30s_bioc_CanESM5_ssp245_2041-2060_tile-43.tif'
Error in utils::download.file(url = url, destfile = filename, quiet = quiet, :
cannot open URL 'https://geodata.ucdavis.edu/cmip6/tiles/CanESM5/ssp245/wc2.1_30s_bioc_CanESM5_ssp245_2041-2060_tile-43.tif'
In addition: Warning messages:
1: In utils::download.file(url = url, destfile = filename, quiet = quiet, :
downloaded length 0 != reported length 282
2: In utils::download.file(url = url, destfile = filename, quiet = quiet, :
cannot open URL 'https://geodata.ucdavis.edu/cmip6/tiles/CanESM5/ssp245/wc2.1_30s_bioc_CanESM5_ssp245_2041-2060_tile-43.tif': HTTP status was '404 Not Found'
Error in .downloadDirect(turl, outfname[i], ...) : download failed
I have a suggestion for the convenience function country_codes. It works fine as is, but it might be nice to allow users to query it directly for a particular country or region.
Here's my idea:
country_codes <- function(query = NULL) {
path <- system.file(package="geodata")
#d <- utils::read.csv(paste(path, "/ex/countries.csv", sep=""), stringsAsFactors=FALSE, encoding="UTF-8")
res <- readRDS(file.path(path, "ex/countries.rds"))
if(is.null(query)){
res
} else {
hits <- apply(res, 1, function(x) any(grepl(query, x,
ignore.case = TRUE)))
res[hits, ]
}
}
The default behaviour is unchanged. But if I want to quickly look up a particular location, I can do:
> country_codes("mexico")
NAME ISO3 ISO2 NAME_ISO NAME_FAO NAME_LOCAL
145 Mexico MEX MX MEXICO Mexico México|Estados Unidos Mexicanos
SOVEREIGN UNREGION1 UNREGION2 continent
145 México Central America Americas North America
country_codes("mx")
NAME ISO3 ISO2 NAME_ISO NAME_FAO NAME_LOCAL
145 Mexico MEX MX MEXICO Mexico México|Estados Unidos Mexicanos
SOVEREIGN UNREGION1 UNREGION2 continent
145 México Central America Americas North America
> country_codes("samoa")
NAME ISO3 ISO2 NAME_ISO NAME_FAO NAME_LOCAL
6 American Samoa ASM AS AMERICAN SAMOA American Samoa American Samoa
197 Samoa WSM WS SAMOA Samoa Samoa
SOVEREIGN UNREGION1 UNREGION2 continent
6 United States Polynesia Oceania Oceania
197 Samoa Polynesia Oceania Oceania
> country_codes("guinea")
NAME ISO3 ISO2 NAME_ISO NAME_FAO
71 Equatorial Guinea GNQ GQ EQUATORIAL GUINEA Equatorial Guinea
96 Guinea-Bissau GNB GW GUINEA-BISSAU Guinea-Bissau
97 Guinea GIN GN GUINEA Guinea
175 Papua New Guinea PNG PG PAPUA NEW GUINEA Papua New Guinea
NAME_LOCAL SOVEREIGN UNREGION1 UNREGION2 continent
71 Guinea Ecuatorial Equatorial Guinea Middle Africa Africa Africa
96 Guiné-Bissau Guinea-Bissau Western Africa Africa Africa
97 Guinee Guinea Western Africa Africa Africa
175 Papua Niu Gini Papua New Guinea Melanesia Oceania Oceania
Not anything you can't do with an extra line or two of code, but maybe useful nevertheless?
Thanks for all your work, I'm really enjoying terra et al. as I update my scripts!
Best,
Tyler
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