source("https://github.com/mdsumner/quarto-blog/releases/download/latest/geodata-ucdavis-tools.R")The R package geodata provides functions for downloading climate, elevation, soil, crop, species occurrence, and administrative boundary data. All of its raster and vector data is hosted on a single Apache web server at geodata.ucdavis.edu.
Every file on that server is directly accessible via HTTP. This means we can enumerate, inspect, and in some cases read them using GDAL’s virtual filesystem — without downloading anything first.
This post documents the full site structure, the file formats served, and which files can be streamed via /vsicurl/ (they all can, but without efficient tiling it’s probably best to make local copies for large raster).
Helper functions
The code snippets below use a small set of helper functions that wrap gdalraster::vsi_read_dir() and related GDAL calls. Source them with:
This provides: vsi_list(), geodata_files(), gdalinfo(), check_block_size(), and streamability_report().
Site structure
The server has three top-level paths that contain spatial data:
| Path | Contents |
|---|---|
/climate/ |
WorldClim 2.1 and 1.4, CMIP5 legacy data |
/cmip6/ |
Downscaled CMIP6 projections |
/geodata/ |
Soil, landcover, crops, elevation, travel time, OSM, buildings |
/gadm/ |
GADM administrative boundaries (versions 2.8, 3.6, 4.0, 4.1) |
The root URL itself and some intermediate directories serve an index.html that says “Hello World!” rather than an Apache directory listing. The data directories below these do have standard Apache autoindex enabled, which is what makes vsi_read_dir() work.
Enumerating files
GDAL’s /vsicurl/ handler can parse Apache directory listings. The gdalraster package exposes this via vsi_read_dir():
library(gdalraster)GDAL 3.13.0dev-a3b7b01d3e-dirty (released 2026-02-23), GEOS 3.12.1, PROJ 9.7.0## flat directory — returns filenames
vsi_read_dir("/vsicurl/https://geodata.ucdavis.edu/geodata/soil/soilgrids/") [1] "agg" "bdod_0-5cm_mean_30s.tif"
[3] "bdod_15-30cm_mean_30s.tif" "bdod_30-60cm_mean_30s.tif"
[5] "bdod_5-15cm_mean_30s.tif" "cec_0-5cm_mean_30s.tif"
[7] "cec_15-30cm_mean_30s.tif" "cec_30-60cm_mean_30s.tif"
[9] "cec_5-15cm_mean_30s.tif" "cfvo_0-5cm_mean_30s.tif"
[11] "cfvo_15-30cm_mean_30s.tif" "cfvo_30-60cm_mean_30s.tif"
[13] "cfvo_5-15cm_mean_30s.tif" "clay_0-5cm_mean_30s.tif"
[15] "clay_15-30cm_mean_30s.tif" "clay_30-60cm_mean_30s.tif"
[17] "clay_5-15cm_mean_30s.tif" "files.txt"
[19] "fill" "nitrogen_0-5cm_mean_30s.tif"
[21] "nitrogen_15-30cm_mean_30s.tif" "nitrogen_30-60cm_mean_30s.tif"
[23] "nitrogen_5-15cm_mean_30s.tif" "ocd_0-5cm_mean_30s.tif"
[25] "ocd_15-30cm_mean_30s.tif" "ocd_30-60cm_mean_30s.tif"
[27] "ocd_5-15cm_mean_30s.tif" "phh2o_0-5cm_Q0.05_30s.tif"
[29] "phh2o_0-5cm_Q0.95_30s.tif" "phh2o_0-5cm_mean_30s.tif"
[31] "phh2o_15-30cm_mean_30s.tif" "phh2o_30-60cm_mean_30s.tif"
[33] "phh2o_5-15cm_Q0.05_30s.tif" "phh2o_5-15cm_Q0.95_30s.tif"
[35] "phh2o_5-15cm_mean_30s.tif" "raw"
[37] "sand_0-5cm_mean_30s.tif" "sand_15-30cm_mean_30s.tif"
[39] "sand_30-60cm_mean_30s.tif" "sand_5-15cm_mean_30s.tif"
[41] "silt_0-5cm_mean_30s.tif" "silt_15-30cm_mean_30s.tif"
[43] "silt_30-60cm_mean_30s.tif" "silt_5-15cm_mean_30s.tif"
[45] "soc_0-5cm_mean_30s.tif" "soc_15-30cm_mean_30s.tif"
[47] "soc_30-60cm_mean_30s.tif" "soc_5-15cm_mean_30s.tif" For structured enumeration with URLs and GDAL dataset names:
soilgrids <- geodata_files("geodata/soil/soilgrids")
head(soilgrids) url
1 https://geodata.ucdavis.edu/geodata/soil/soilgrids/bdod_0-5cm_mean_30s.tif
2 https://geodata.ucdavis.edu/geodata/soil/soilgrids/bdod_15-30cm_mean_30s.tif
3 https://geodata.ucdavis.edu/geodata/soil/soilgrids/bdod_30-60cm_mean_30s.tif
4 https://geodata.ucdavis.edu/geodata/soil/soilgrids/bdod_5-15cm_mean_30s.tif
5 https://geodata.ucdavis.edu/geodata/soil/soilgrids/cec_0-5cm_mean_30s.tif
6 https://geodata.ucdavis.edu/geodata/soil/soilgrids/cec_15-30cm_mean_30s.tif
file ext
1 bdod_0-5cm_mean_30s.tif tif
2 bdod_15-30cm_mean_30s.tif tif
3 bdod_30-60cm_mean_30s.tif tif
4 bdod_5-15cm_mean_30s.tif tif
5 cec_0-5cm_mean_30s.tif tif
6 cec_15-30cm_mean_30s.tif tif
gdaldsn
1 /vsicurl/https://geodata.ucdavis.edu/geodata/soil/soilgrids/bdod_0-5cm_mean_30s.tif
2 /vsicurl/https://geodata.ucdavis.edu/geodata/soil/soilgrids/bdod_15-30cm_mean_30s.tif
3 /vsicurl/https://geodata.ucdavis.edu/geodata/soil/soilgrids/bdod_30-60cm_mean_30s.tif
4 /vsicurl/https://geodata.ucdavis.edu/geodata/soil/soilgrids/bdod_5-15cm_mean_30s.tif
5 /vsicurl/https://geodata.ucdavis.edu/geodata/soil/soilgrids/cec_0-5cm_mean_30s.tif
6 /vsicurl/https://geodata.ucdavis.edu/geodata/soil/soilgrids/cec_15-30cm_mean_30s.tifThis returns a data.frame with columns url, file, ext, and gdaldsn. The gdaldsn column contains the /vsicurl/ path for files GDAL can read, and NA for files it cannot (.rds, .txt, etc.).
What’s there: a complete inventory
SoilGrids (/geodata/soil/soilgrids/)
Global soil properties at 30 arc-second resolution. 48 TIF files covering 8 properties (bdod, cec, cfvo, clay, nitrogen, ocd, phh2o, sand, silt, soc) at 4 depth intervals, plus pH quantiles. Files range from 83 MB to 546 MB.
soilgrids <- geodata_files("geodata/soil/soilgrids", pattern = "\\.tif$")
nrow(soilgrids)[1] 44Format: Single-band GeoTIFF, LZW compressed, Block=43200x1 (row-striped). No overviews. No internal tiling.
check_block_size(soilgrids$gdaldsn[1])xblock yblock
43200 1
attr(,"full_width")
[1] 43200
attr(,"is_row_striped")
[1] TRUE
attr(,"is_tiled")
[1] FALSEStreamability: Row-striped layout means sub-region reads via /vsicurl/ require decompressing entire rows spanning the full 43200 pixel width. Reading a small bounding box will transfer most of the file. These files are best downloaded locally.
The geodata::soil_world_vsi() function constructs /vsicurl/ paths to these same files — the name suggests streaming is the intended use, but the row-striped layout makes it impractical for anything less than a large regional or global read.
WorldClim 2.1 tiles (/climate/worldclim/2_1/tiles/tile/)
30 arc-second resolution climate data, pre-tiled into 72 spatial tiles. 8 variables (bio, elev, prec, srad, tavg, tmax, tmin, wind). Bio tiles have 19 bands; monthly variables have 12 bands; elevation has 1. File sizes range from ~5 MB (ocean/ice tiles) to ~550 MB (land-dense tiles).
wc_tiles <- geodata_files("climate/worldclim/2_1/tiles/tile", pattern = "\\.tif$")
nrow(wc_tiles) ## expect 576 = 72 tiles × 8 variables[1] 576Format: Multi-band GeoTIFF. Block layout should be checked:
check_block_size(wc_tiles$gdaldsn[1])xblock yblock
3600 1
attr(,"full_width")
[1] 3600
attr(,"is_row_striped")
[1] TRUE
attr(,"is_tiled")
[1] FALSEWorldClim 2.1 global (/climate/worldclim/2_1/base/)
Global grids at 10m, 5m, 2.5m, and 30s resolution. All stored as .zip files containing one or more TIF files per variable.
| Resolution | Variables | Example size |
|---|---|---|
| 10 minute | bio, elev, prec, srad, tavg, tmax, tmin, vapr, wind | 1.3 MB – 48 MB |
| 5 minute | same | 4.6 MB – 171 MB |
| 2.5 minute | same | 17 MB – 628 MB |
| 30 second | same | 323 MB – 9.7 GB |
GDAL can read inside these zips via /vsizip//vsicurl/:
## example: 10-minute bioclim, first file inside the zip
dsn <- "/vsizip//vsicurl/https://geodata.ucdavis.edu/climate/worldclim/2_1/base/wc2.1_10m_bio.zip"
## list the contents of the zip
vsi_read_dir(dsn) [1] "wc2.1_10m_bio_1.tif" "wc2.1_10m_bio_10.tif" "wc2.1_10m_bio_11.tif"
[4] "wc2.1_10m_bio_12.tif" "wc2.1_10m_bio_13.tif" "wc2.1_10m_bio_14.tif"
[7] "wc2.1_10m_bio_15.tif" "wc2.1_10m_bio_16.tif" "wc2.1_10m_bio_17.tif"
[10] "wc2.1_10m_bio_18.tif" "wc2.1_10m_bio_19.tif" "wc2.1_10m_bio_2.tif"
[13] "wc2.1_10m_bio_3.tif" "wc2.1_10m_bio_4.tif" "wc2.1_10m_bio_5.tif"
[16] "wc2.1_10m_bio_6.tif" "wc2.1_10m_bio_7.tif" "wc2.1_10m_bio_8.tif"
[19] "wc2.1_10m_bio_9.tif" The internal TIF filenames follow the pattern wc2.1_{res}_{var}_{number}.tif.
WorldClim 2.1 country extracts (/climate/worldclim/2_1/tiles/iso/)
30 arc-second data clipped to individual countries, identified by ISO 3166-1 alpha-3 codes.
iso <- geodata_files("climate/worldclim/2_1/tiles/iso")
head(iso) url
1 https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/iso/ABW_wc2.1_30s_bio.tif
2 https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/iso/ABW_wc2.1_30s_elev.tif
3 https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/iso/ABW_wc2.1_30s_prec.tif
4 https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/iso/ABW_wc2.1_30s_srad.tif
5 https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/iso/ABW_wc2.1_30s_tavg.tif
6 https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/iso/ABW_wc2.1_30s_tmax.tif
file ext
1 ABW_wc2.1_30s_bio.tif tif
2 ABW_wc2.1_30s_elev.tif tif
3 ABW_wc2.1_30s_prec.tif tif
4 ABW_wc2.1_30s_srad.tif tif
5 ABW_wc2.1_30s_tavg.tif tif
6 ABW_wc2.1_30s_tmax.tif tif
gdaldsn
1 /vsicurl/https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/iso/ABW_wc2.1_30s_bio.tif
2 /vsicurl/https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/iso/ABW_wc2.1_30s_elev.tif
3 /vsicurl/https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/iso/ABW_wc2.1_30s_prec.tif
4 /vsicurl/https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/iso/ABW_wc2.1_30s_srad.tif
5 /vsicurl/https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/iso/ABW_wc2.1_30s_tavg.tif
6 /vsicurl/https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/iso/ABW_wc2.1_30s_tmax.tifWorldClim 1.4 (/climate/worldclim/1_4/)
Legacy WorldClim version in BIL (Band Interleaved by Line) format inside zip files. Three subdirectories: cur/ (current), fut/ (future projections), pst/ (past / LGM / mid-Holocene).
BIL format is GDAL-readable but, like the row-striped TIFs, does not support efficient random access.
CMIP6 projections (/cmip6/)
Downscaled and bias-corrected CMIP6 future climate data. Organised as:
/cmip6/{resolution}/{model}/{ssp}/Resolutions: 30s, 2.5m, 5m, 10m. 23 GCMs. 4 SSPs (ssp126, ssp245, ssp370, ssp585). 4 time periods (2021-2040, 2041-2060, 2061-2080, 2081-2100). Variables: bioc, prec, tmax, tmin.
At 30s resolution these are bare TIF files, some exceeding 20 GB.
## list models at 2.5 minute resolution
vsi_read_dir("/vsicurl/https://geodata.ucdavis.edu/cmip6/2.5m/") [1] "ACCESS-CM2" "ACCESS-ESM1-5" "AWI-CM-1-1-MR" "BCC-CSM2-MR"
[5] "CMCC-ESM2" "CNRM-CM6-1" "CNRM-CM6-1-HR" "CNRM-ESM2-1"
[9] "CanESM5" "CanESM5-CanOE" "EC-Earth3-Veg" "EC-Earth3-Veg-LR"
[13] "FIO-ESM-2-0" "GFDL-ESM4" "GISS-E2-1-G" "GISS-E2-1-H"
[17] "HadGEM3-GC31-LL" "INM-CM4-8" "INM-CM5-0" "IPSL-CM6A-LR"
[21] "MIROC-ES2L" "MIROC6" "MPI-ESM1-2-HR" "MPI-ESM1-2-LR"
[25] "MRI-ESM2-0" "UKESM1-0-LL" There is also a /cmip6/tiles/ directory with tiled versions.
CMIP5 projections (/climate/cmip5/)
Legacy CMIP5 data at 30s, 2.5m, 5m, 10m resolutions. Separate directories for lgm/ (Last Glacial Maximum) and mid/ (mid-Holocene).
Elevation
TODO: locate and document. The geodata package provides elevation_3s(), elevation_30s(), and elevation_global() — the URLs for these need to be traced from the source code.
Landcover (/geodata/landcover/)
Two subdirectories:
/geodata/landcover/30s/— 30 arc-second aggregated landcover fractions/geodata/landcover/3deg_cogs/— ESA WorldCover 10m data as 3-degree tiles, labelled as COGs in the directory name
lc_cogs <- geodata_files("geodata/landcover/3deg_cogs", pattern = "\\.tif$")
nrow(lc_cogs)[1] 2651The 3deg_cogs files follow the naming convention ESA_WorldCover_10m_2020_v100_{lat}{lon}_Map.tif. If these are genuine COGs (internally tiled with overviews), they would be efficiently streamable via /vsicurl/.
## check whether these are really COGs
check_block_size(lc_cogs$gdaldsn[1])xblock yblock
1024 1024
attr(,"full_width")
[1] 36000
attr(,"is_row_striped")
[1] FALSE
attr(,"is_tiled")
[1] TRUECrops (/geodata/crops/)
Subdirectories for SPAM and Monfreda crop data, plus cropland density and crop calendars. File formats and structure need to be enumerated.
GADM administrative boundaries (/gadm/gadm4.1/)
Per-country boundaries in multiple formats:
| Subdirectory | Format | GDAL-readable | Notes |
|---|---|---|---|
gpkg/ |
GeoPackage | Yes | SQLite-based, supports HTTP range requests |
shp/ |
Shapefile (zipped) | Yes, via /vsizip/ | Multiple component files |
json/ |
GeoJSON | Yes | |
pck/ |
RDS (R serialization) | No | Used by geodata::gadm() |
kmz/ |
KMZ (zipped KML) | Yes, via /vsizip/ |
Whole-dataset archives:
gadm_410-gpkg.zip— 1.4 GB, all countries in one GeoPackagegadm_410-gdb.zip— 913 MB, FileGDB formatgadm_410-levels.zip— 2.5 GB, separated by admin levelgadm_410-raw.gpkg— 2.6 GB, bare GeoPackage on HTTP
The gadm_410-raw.gpkg is directly streamable:
## open GADM as a single GeoPackage over HTTP
dsn <- "/vsicurl/https://geodata.ucdavis.edu/gadm/gadm4.1/gadm_410-raw.gpkg"
## list layers
gdalraster::ogr_ds_layer_names(dsn)[1] "gadm41_raw"Per-country GeoPackage files are also streamable:
dsn <- "/vsicurl/https://geodata.ucdavis.edu/gadm/gadm4.1/gpkg/gadm41_AUS.gpkg"
gdalraster::ogr_ds_layer_names(dsn)[1] "ADM_ADM_0" "ADM_ADM_1" "ADM_ADM_2"Other datasets
| Path | Contents | geodata function |
|---|---|---|
/geodata/travel/ |
Travel time rasters | travel_time() |
/geodata/osm/ |
OpenStreetMap extracts (highways, places) | osm() |
/geodata/buildings/ |
Building footprint data | — |
These need further enumeration.
Datasets not on this server
Some geodata functions fetch data from external APIs rather than geodata.ucdavis.edu:
sp_occurrence()— queries the GBIF APIbio_oracle()— queries the Bio-Oracle server atbio-oracle.org
Block layout and streamability
The central question for remote access is whether a file’s internal layout supports efficient HTTP range requests. GDAL’s /vsicurl/ handler issues byte-range requests to read specific portions of a file. This works well when the file is internally tiled (e.g., COG format with Block=256x256) but poorly when the file is row-striped (Block=width×1).
For a row-striped file, reading a small spatial window requires decompressing one or more full rows, each spanning the entire raster width. For a 43200-pixel-wide global grid, every row is a complete scan line from -180° to +180°. A single HTTP range request per row, times the number of rows in the window, with full LZW decompression of each row. For a small bounding box this is extremely wasteful.
What we know
| Collection | Block layout | Streamable? |
|---|---|---|
| SoilGrids TIFs | 43200×1 (row-striped) | No — download |
| WorldClim 2.1 tiles | TODO: check | Probably row-striped |
| WorldClim 2.1 global zips | N/A (zip) | Via /vsizip/, but still row-striped inside |
| CMIP6 30s TIFs | TODO: check | Unknown |
| Landcover 3deg COGs | TODO: check | Likely yes (name says COGs) |
| Landcover 30s | TODO: check | Unknown |
| GADM GeoPackage | N/A (vector) | Yes — SQLite random access works over HTTP |
| GADM raw GeoPackage | N/A (vector) | Yes |
How to check
## for any TIF on the server
bs <- check_block_size("/vsicurl/https://geodata.ucdavis.edu/path/to/file.tif")
bs
## if is_row_striped is TRUE: download, don't stream
## if is_tiled is TRUE: streaming is efficientGenerating file tables
For any collection, generate a complete table of URLs and GDAL dataset names:
## SoilGrids: all TIFs
sg <- geodata_files("geodata/soil/soilgrids", pattern = "\\.tif$")
head(sg[, c("url", "gdaldsn")]) url
1 https://geodata.ucdavis.edu/geodata/soil/soilgrids/bdod_0-5cm_mean_30s.tif
2 https://geodata.ucdavis.edu/geodata/soil/soilgrids/bdod_15-30cm_mean_30s.tif
3 https://geodata.ucdavis.edu/geodata/soil/soilgrids/bdod_30-60cm_mean_30s.tif
4 https://geodata.ucdavis.edu/geodata/soil/soilgrids/bdod_5-15cm_mean_30s.tif
5 https://geodata.ucdavis.edu/geodata/soil/soilgrids/cec_0-5cm_mean_30s.tif
6 https://geodata.ucdavis.edu/geodata/soil/soilgrids/cec_15-30cm_mean_30s.tif
gdaldsn
1 /vsicurl/https://geodata.ucdavis.edu/geodata/soil/soilgrids/bdod_0-5cm_mean_30s.tif
2 /vsicurl/https://geodata.ucdavis.edu/geodata/soil/soilgrids/bdod_15-30cm_mean_30s.tif
3 /vsicurl/https://geodata.ucdavis.edu/geodata/soil/soilgrids/bdod_30-60cm_mean_30s.tif
4 /vsicurl/https://geodata.ucdavis.edu/geodata/soil/soilgrids/bdod_5-15cm_mean_30s.tif
5 /vsicurl/https://geodata.ucdavis.edu/geodata/soil/soilgrids/cec_0-5cm_mean_30s.tif
6 /vsicurl/https://geodata.ucdavis.edu/geodata/soil/soilgrids/cec_15-30cm_mean_30s.tif## WorldClim tiles: all TIFs
wc <- geodata_files("climate/worldclim/2_1/tiles/tile", pattern = "\\.tif$")
head(wc[, c("url", "gdaldsn")]) url
1 https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/tile/tile_10_wc2.1_30s_bio.tif
2 https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/tile/tile_10_wc2.1_30s_elev.tif
3 https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/tile/tile_10_wc2.1_30s_prec.tif
4 https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/tile/tile_10_wc2.1_30s_srad.tif
5 https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/tile/tile_10_wc2.1_30s_tavg.tif
6 https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/tile/tile_10_wc2.1_30s_tmax.tif
gdaldsn
1 /vsicurl/https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/tile/tile_10_wc2.1_30s_bio.tif
2 /vsicurl/https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/tile/tile_10_wc2.1_30s_elev.tif
3 /vsicurl/https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/tile/tile_10_wc2.1_30s_prec.tif
4 /vsicurl/https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/tile/tile_10_wc2.1_30s_srad.tif
5 /vsicurl/https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/tile/tile_10_wc2.1_30s_tavg.tif
6 /vsicurl/https://geodata.ucdavis.edu/climate/worldclim/2_1/tiles/tile/tile_10_wc2.1_30s_tmax.tif## GADM 4.1 GeoPackages
gadm <- geodata_files("gadm/gadm4.1/gpkg", pattern = "\\.gpkg$")
head(gadm[, c("url", "gdaldsn")]) url
1 https://geodata.ucdavis.edu/gadm/gadm4.1/gpkg/gadm41_ABW.gpkg
2 https://geodata.ucdavis.edu/gadm/gadm4.1/gpkg/gadm41_AFG.gpkg
3 https://geodata.ucdavis.edu/gadm/gadm4.1/gpkg/gadm41_AGO.gpkg
4 https://geodata.ucdavis.edu/gadm/gadm4.1/gpkg/gadm41_AIA.gpkg
5 https://geodata.ucdavis.edu/gadm/gadm4.1/gpkg/gadm41_ALA.gpkg
6 https://geodata.ucdavis.edu/gadm/gadm4.1/gpkg/gadm41_ALB.gpkg
gdaldsn
1 /vsicurl/https://geodata.ucdavis.edu/gadm/gadm4.1/gpkg/gadm41_ABW.gpkg
2 /vsicurl/https://geodata.ucdavis.edu/gadm/gadm4.1/gpkg/gadm41_AFG.gpkg
3 /vsicurl/https://geodata.ucdavis.edu/gadm/gadm4.1/gpkg/gadm41_AGO.gpkg
4 /vsicurl/https://geodata.ucdavis.edu/gadm/gadm4.1/gpkg/gadm41_AIA.gpkg
5 /vsicurl/https://geodata.ucdavis.edu/gadm/gadm4.1/gpkg/gadm41_ALA.gpkg
6 /vsicurl/https://geodata.ucdavis.edu/gadm/gadm4.1/gpkg/gadm41_ALB.gpkg## CMIP6 models at 2.5 minute resolution
## first list the model directories, then enumerate within each
models <- vsi_read_dir("/vsicurl/https://geodata.ucdavis.edu/cmip6/2.5m/")
models [1] "ACCESS-CM2" "ACCESS-ESM1-5" "AWI-CM-1-1-MR" "BCC-CSM2-MR"
[5] "CMCC-ESM2" "CNRM-CM6-1" "CNRM-CM6-1-HR" "CNRM-ESM2-1"
[9] "CanESM5" "CanESM5-CanOE" "EC-Earth3-Veg" "EC-Earth3-Veg-LR"
[13] "FIO-ESM-2-0" "GFDL-ESM4" "GISS-E2-1-G" "GISS-E2-1-H"
[17] "HadGEM3-GC31-LL" "INM-CM4-8" "INM-CM5-0" "IPSL-CM6A-LR"
[21] "MIROC-ES2L" "MIROC6" "MPI-ESM1-2-HR" "MPI-ESM1-2-LR"
[25] "MRI-ESM2-0" "UKESM1-0-LL" Still to document
Several areas need further investigation:
- Elevation data paths (
elevation_3s,elevation_30s,elevation_global) - Exact contents of
/geodata/crops/,/geodata/travel/,/geodata/osm/,/geodata/buildings/ - Block layout of WorldClim tiles, CMIP6 30s TIFs, and landcover COGs
- Contents of
/geodata/landcover/30s/ - Contents of
/geodata/soil/soilgrids/agg/,fill/, andraw/subdirectories - The
/cmip6/tiles/tiled variant structure