Pull one page-set of granules for a date window, as UMM-JSON

Usage

cmr_find_granules(
  short_name,
  t0,
  t1,
  provider = NULL,
  page_size = 2000,
  bounding_box = NULL,
  polygon = NULL
)

Arguments

short_name: CMR collection short name (e.g. "MUR-JPL-L4-GLOB-v4.1")
t0, t1: Date range (inclusive), coercible with format()
provider: Optional CMR provider id, to disambiguate short names that exist under multiple providers
page_size: Max granules per request (CMR hard limit ~2000 for this non-scrolling approach)
bounding_box: Optional spatial filter: a length-4 numeric vector c(west, south, east, north) in decimal degrees. Mutually exclusive with polygon. Useful for subsetting swath products (e.g. MOD021KM) to a region of interest rather than pulling every granule that intersects the temporal window worldwide.
polygon: Optional spatial filter: a numeric vector of lon, lat, lon, lat, ... vertices tracing a ring (at least 3 distinct vertices). If the first and last vertex don't match, the ring is closed automatically (with a message) – CMR requires closed polygons. Mutually exclusive with bounding_box.

Value

A tibble::tibble() with one row per granule, or NULL if no granules matched. See cmr_audit_revisions() for the column dictionary.

Examples

# \donttest{
cmr_find_granules("MUR-JPL-L4-GLOB-v4.1", as.Date("2024-01-01"), as.Date("2024-01-05"))
#> # A tibble: 6 × 11
#>   granule_ur        concept_id n_rev rev_date insert_date update_date production
#>   <chr>             <chr>      <int> <chr>    <chr>       <chr>       <chr>     
#> 1 20240101090000-J… G28292389…    16 2024-01… 2024-01-10… 2024-01-10… 2024-01-1…
#> 2 20240102090000-J… G28292432…    18 2024-01… 2024-01-11… 2024-01-11… 2024-01-1…
#> 3 20240103090000-J… G28297396…    18 2024-01… 2024-01-12… 2024-01-12… 2024-01-1…
#> 4 20240104090000-J… G28302941…    17 2024-01… 2024-01-13… 2024-01-13… 2024-01-1…
#> 5 20240105090000-J… G28311561…    18 2024-01… 2024-01-14… 2024-01-14… 2024-01-1…
#> 6 20240106090000-J… G28314898…    18 2024-01… 2024-01-15… 2024-01-15… 2024-01-1…
#> # ℹ 4 more variables: temporal_start <chr>, data_url <chr>, s3_url <chr>,
#> #   nc_bytes <dbl>

# subset a high-volume swath product to a region of interest
cmr_find_granules("MOD021KM", as.Date("2026-08-01"), as.Date("2026-08-01"),
                   bounding_box = c(140, -45, 155, -35))
#> # A tibble: 8 × 11
#>   granule_ur       concept_id  n_rev rev_date insert_date update_date production
#>   <chr>            <chr>       <int> <chr>    <chr>       <chr>       <chr>     
#> 1 LAADS:9975746428 G426948587…     1 2026-08… 2026-08-04… 2026-08-04… 2026-08-0…
#> 2 LAADS:9980651751 G427337124…     1 2026-08… 2026-08-07… 2026-08-07… 2026-08-0…
#> 3 LAADS:9975763948 G426949649…     1 2026-08… 2026-08-04… 2026-08-04… 2026-08-0…
#> 4 LAADS:9980653369 G427337154…     1 2026-08… 2026-08-07… 2026-08-07… 2026-08-0…
#> 5 LAADS:9975774200 G426950166…     1 2026-08… 2026-08-04… 2026-08-04… 2026-08-0…
#> 6 LAADS:9980668284 G427338216…     1 2026-08… 2026-08-07… 2026-08-07… 2026-08-0…
#> 7 LAADS:9975768761 G426949718…     1 2026-08… 2026-08-04… 2026-08-04… 2026-08-0…
#> 8 LAADS:9980660739 G427337486…     1 2026-08… 2026-08-07… 2026-08-07… 2026-08-0…
#> # ℹ 4 more variables: temporal_start <chr>, data_url <chr>, s3_url <chr>,
#> #   nc_bytes <dbl>
# }

Pull one page-set of granules for a date window, as UMM-JSON

Usage

Arguments

Value

See also

Examples