seaaroundus
Sea Around Us API Wrapper
R wrapper for the Sea Around Us API.
The Sea Around Us data are licensed to the public under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License.
Please read the data use policy described in the DATA_USE file.
This software is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version. See the LICENSE file for a full statement of the License.
A note on usage
When querying the API, please be respectful of the resources required to provide this data. We recommend you retain the results for each request so you can avoid repeated requests for duplicate information.
Prerequisites
Mac via Homebrew
$ brew tap homebrew/versions
$ brew install v8-315 gdalLinux via apt-get
$ sudo apt-get install libgdal1-dev libgdal-dev libgeos-c1 libproj-devInstallation
CRAN version
install.packages("seaaroundus")Dev version
install.packages("devtools")
devtools::install_github("ropensci/seaaroundus")library(seaaroundus)Example usage
list available eezs
head(listregions('eez'))
#> title id
#> 1 Albania 8
#> 2 Algeria 12
#> 3 American Samoa 16
#> 4 Andaman & Nicobar Isl. (India) 357
#> 5 Angola 24
#> 6 Anguilla (UK) 660get species data for Brazil as a data frame
head(catchdata("eez", 76))
#> years brazilian sardinella whitemouth croaker atlantic seabob
#> 1 1950 0 7129.341 0
#> 2 1951 0 6499.208 0
#> 3 1952 0 6608.910 0
#> 4 1953 0 6769.266 0
#> 5 1954 0 6168.482 0
#> 6 1955 0 6976.245 0
#> sea catfishes, coblers herrings, sardines, menhadens argentine croaker
#> 1 2913.719 5857.411 1707.013
#> 2 3280.651 5267.541 1599.238
#> 3 3333.485 5356.747 2002.369
#> 4 3417.538 5486.354 1348.201
#> 5 3664.398 4935.857 1827.590
#> 6 3652.267 5639.058 2131.946
#> king weakfish argentine hake drums, croakers grey mullets others
#> 1 5076.131 0 1544.886 941.349 25156.60
#> 2 4565.233 0 1794.251 846.551 26962.93
#> 3 4642.063 0 1853.677 860.887 28678.96
#> 4 4754.324 0 1844.091 881.717 26989.10
#> 5 4277.566 0 2065.444 793.246 30082.72
#> 6 4900.144 0 2025.746 906.258 32000.83use alternative API environment (available on all functions)
NOTE: alternative API environments may not always be publically accessible or stable
head(catchdata("eez", 76, env="qa"))
#> years brazilian sardinella whitemouth croaker atlantic seabob
#> 1 1950 0 7129.341 0
#> 2 1951 0 6499.208 0
#> 3 1952 0 6608.910 0
#> 4 1953 0 6769.266 0
#> 5 1954 0 6168.482 0
#> 6 1955 0 6976.245 0
#> sea catfishes, coblers herrings, sardines, menhadens argentine croaker
#> 1 2913.719 5857.411 1707.013
#> 2 3280.651 5267.541 1599.238
#> 3 3333.485 5356.747 2002.369
#> 4 3417.538 5486.354 1348.201
#> 5 3664.398 4935.857 1827.590
#> 6 3652.267 5639.058 2131.946
#> king weakfish argentine hake drums, croakers grey mullets others
#> 1 5076.131 0 1544.886 941.349 25156.60
#> 2 4565.233 0 1794.251 846.551 26962.93
#> 3 4642.063 0 1853.677 860.887 28678.96
#> 4 4754.324 0 1844.091 881.717 26989.10
#> 5 4277.566 0 2065.444 793.246 30082.72
#> 6 4900.144 0 2025.746 906.258 32000.83get top 3 species data for Brazil as a data frame
head(catchdata("eez", 76, limit=3))
#> years brazilian sardinella whitemouth croaker atlantic seabob others
#> 1 1950 0 7129.341 0 43197.11
#> 2 1951 0 6499.208 0 44316.40
#> 3 1952 0 6608.910 0 46728.19
#> 4 1953 0 6769.266 0 44721.33
#> 5 1954 0 6168.482 0 47646.82
#> 6 1955 0 6976.245 0 51256.25get reporting status data by value for Brazil as a data frame
head(catchdata("eez", 76, measure="value", dimension="reporting-status"))
#> years reported unreported
#> 1 1950 443600.5 194909739
#> 2 1951 498019.1 188595589
#> 3 1952 562198.1 181745220
#> 4 1953 389671.3 160502627
#> 5 1954 802928.4 120388021
#> 6 1955 2531927.4 103156694get species data for Brazil as a chart
catchdata("eez", 76, chart=TRUE)eez vs high seas percent catch data frame
NOTE: data not available until SeaAroundUs global paper is released
head(eezsvshighseas())
#> year eez_percent_catch high_seas_percent_catch
#> 1 1950 99 1
#> 2 1951 99 1
#> 3 1952 99 1
#> 4 1953 99 1
#> 5 1954 99 1
#> 6 1955 99 1eez vs high seas percent catch graph
eezsvshighseas(chart=TRUE)marine trophic index for Brazil as a data frame
head(marinetrophicindex("eez", 76))
#> level year
#> 1 3.51 1950
#> 2 3.53 1951
#> 3 3.53 1952
#> 4 3.52 1953
#> 5 3.54 1954
#> 6 3.54 1955marine trophic index for Brazil as graph
marinetrophicindex("eez", 76, chart=TRUE)get cells for a shape in WKT format
wkt <- "POLYGON((2.37 43.56,13.18 43.56,13.18 35.66,2.37 35.66,2.37 43.56))"
res <- getcells(wkt)
res[1:10]
#> [1] 66605 66606 66607 66608 66609 66610 66611 66612 66613 66614get datagrid of cell data for a given year and list of cells
head(getcelldata(2005, c(89568,90288,89569)))
#> taxon_scientific_name taxon_key commercial_group_id sector_type_id
#> 1 Thunnus albacares 600143 4 1
#> 2 Thunnus albacares 600143 4 1
#> 3 Thunnus albacares 600143 4 1
#> 4 Thunnus obesus 600146 4 1
#> 5 Thunnus obesus 600146 4 1
#> 6 Thunnus obesus 600146 4 1
#> commercial_group_name catch_status_name sector_type_name catch_sum
#> 1 Tuna & billfishes Landings Industrial 0.02261394
#> 2 Tuna & billfishes Landings Industrial 0.02318308
#> 3 Tuna & billfishes Landings Industrial 0.02261394
#> 4 Tuna & billfishes Landings Industrial 0.03267660
#> 5 Tuna & billfishes Landings Industrial 0.03377360
#> 6 Tuna & billfishes Landings Industrial 0.03267660
#> functional_group_name catch_status reporting_status taxon_common_name
#> 1 pelagiclg R R Yellowfin tuna
#> 2 pelagiclg R R Yellowfin tuna
#> 3 pelagiclg R R Yellowfin tuna
#> 4 pelagiclg R R Bigeye tuna
#> 5 pelagiclg R R Bigeye tuna
#> 6 pelagiclg R R Bigeye tuna
#> fishing_entity_name year cell_id reporting_status_name
#> 1 Taiwan 2005 89569 Reported
#> 2 Taiwan 2005 90288 Reported
#> 3 Taiwan 2005 89568 Reported
#> 4 Taiwan 2005 89569 Reported
#> 5 Taiwan 2005 90288 Reported
#> 6 Taiwan 2005 89568 Reported
#> functional_group_id fishing_entity_id
#> 1 3 32
#> 2 3 32
#> 3 3 32
#> 4 3 32
#> 5 3 32
#> 6 3 32Available parameters
Regions:
- eez
- lme
- rfmo
- eez-bordering
- taxon
Measures:
- tonnage
- value
Dimensions:
- taxon (not available for taxon region)
- commercialgroup
- functionalgroup
- country (fishing country)
- sector
- catchtype
- reporting-status
- eez (only available for eez-bordering and taxon regions)
- highseas (only available for taxon region)
Meta
- Please report any issues or bugs.
- License: MIT
- Get citation information for
seaaroundusin R doingcitation(package = 'seaaroundus') - Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.