vignettes/articles/available-data.Rmd
available-data.RmdThis document provides documentation for the most important of the available datasets that can be used with MazamaSpatialUtils version 0.8.x.
Spatial datasets that have been converted to sf package objects of class and adhere to the MazamaSpatialUtils standards are considered to be “harmonized”.
For reproducibility, the R code that ingests and harmonizes each spatial dataset is included in the package as a function. Most of the resulting datasets have been been pre-generated and can be downloaded from http://data.mazamascience.com/MazamaSpatialUtils/Spatial_0.8/.
MazamaSpatialUtils has three built-in datasets which are included with the package when it is installed. Each of these is a simplified dataset suitable for quick identification of or .
SimpleCountries – Country outlinesSimpleCountriesEEZ – Country outlines including
Exclusive Economic Zones over waterSimpleTimezones – Time zonesRunning installSpatialData() allows users to install the
following pre-generated datasets, which can then be loaded with
loadSpatialData(<dataset>)
The following list describes datasets that were available in earlier versions of the MazamaSpatialUtils package. Convert scripts for these datasets will be updated and added on an as-needed basis.
The California Air Basins dataset is a simple features data frame representing the 15 California air basins. Air Basins are designated pursuant to California statute and regulation and identify regions of similar meteorological and geographic conditions. Political boundaries are also considered in determining the air basin boundaries.
See the California Health and Safety Code, Section 39606 et seq. and California Code of Regulations, Title 17, Section 60100 et seq.
Use convertCARBAirBasins() to download and convert this
dataset.
https://hub.arcgis.com/datasets/geoplatform::epa-regions
The EPARegions dataset is a simple features data frame representing the boundaries of the ten Regional Offices of the United States Environmental Protection Agency in the United States. Each regional office monitors the environmental regulations within a group of states.
Use convertEPARegions() to download and convert this
dataset.
https://hub.arcgis.com/datasets/nifc::national-gacc-boundaries
The GACC dataset is a simple features data frame representing the
Geographic Area Coordination Center (GACC) boundaries. GACCs are defined
as, “The physical location of an interagency, regional operation center
for the effective coordination, mobilization and demobilization of
emergency management resources.”
A coordination center serves federal, state and local wildland fire
agencies through logistical coordination of resources throughout the
geographic area, and with other geographic areas, as well.
The United States and Alaska are divided into 11 Geographic Areas for the purpose of incident management and mobilization of resources (people, aircraft, ground equipment). Within each Area, an interagency Geographic Area Coordinating Group (GACG), made up of Fire Directors from each of the Federal and State land management agencies from within the Area, is established.
Use convertGACC() to download and convert this
dataset.
The GADM dataset is a simple features data frame representing the administrative divisions of a specific country at a specific administrative level. GADM, the Database of Global Administrative Areas, is a high-resolution database of country administrative areas.
NOTE: This script will generate .rda files named
GADM_<countryCode>_<admLevel>.rda and requires
user input to specify the country and admin level desired. For example,
to generate Admin 1 level boundaries for Belgium, run
convertGADM(countryCode = "BE", admLevel = 1).
This will create GADM_BE_1.rda. Not all countries have the
same number of levels. Many just have two levels while France has
five.
Use convertGADM() to download and convert this
dataset.
The HIFLDFederalLands dataset is a simple features data frame representing the federally owned or administered lands and Indian Reservations of the United States, Puerto Rico, and the US Virgin Islands. Only areas of 640 acres or more are included in this dataset.
Use convertHIFLDFederalLands() to download and convert
this dataset.
The HMSSmoke dataset is a simple features data frame representing the areas of smoke identified for a specific day. This data is derived from analysis of visible satellite imagery obtained during daylight hours.
NOTE: This script will generate .rda files named
HMSSmoke_<datestamp> and requires user input to
specify the date of interest using the datestamp parameter
in the format of datestamp = "YYYYmmdd".
Use convertHMSSmoke() to download and convert this
dataset.
The MTBSBurnAreas dataset is a simple features data frame representing all large wildland fires (includes wildfire, wildland fire use, and prescribed fire) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period of 1984 through 2017. All fires reported as greater than 1,000 acres in the western US and greater than 500 acres in the eastern US are mapped across all ownerships.
Use convertMTBSBurnArea() to download and convert this
dataset.
The NWSFireZones dataset is a simple features data frame representing weather forecast zones. These areas are used to delineate the Fire Weather Zones that are used by National Weather Service (NWS) in the fire weather forecast program.
Use convertNWSFireZones() to download and convert this
data set.
The PHDs dataset is a simple features data frame representing Public Health Districts for Washington, Oregon, Idaho, and California. This is Mazama internal data obtained from USFS AirFire.
Use convertPHDs() to download and convert this data
set.
The SimpleCountries dataset is a simple features data frame representing country borders. It is a greatly simplified version of the NaturalEarthAdm0 shapefile and is especially suited for spatial searches. Users may wish to use a higher resolution dataset when plotting.
Use convertSimpleCountries() to download and convert
this data set.
The SimpleCountriesEEZ dataset is a simple features data frame
representing simple world divisions which match those in the
EEZCountries layer. Polygons for coastal countries include a 200 mile
buffer, corresponding to their Exclusive Economic Zones, so this layer
is especially suited for spatial searches. This is the default dataset
used in getCountry() and getCountryCode().
Use convertSimpleCountriesEEZ() to download and convert
this data set.
The SimpleTimeZones dataset is a simple features data frame representing timezones of the world.
Use convertSimpleTimezones() to download and convert
this data set.
This creates a simple features data frame for US State Legislative
Districts.
User input is required to specify the stateCode (2-digit
ISO 3166) and which house (Upper or Lower chamber) the data
should represent. For example, to obtain data on the Washington State
Senate Legislative Districts, run
convertStateLegislativeDistricts(stateCode = "WA", house = "Upper").
This will generate a file named
WA_upperHouseLegislativeDistricts.rda
Use convertStateLegislativeDistricts() to download and
convert this data set.
http://thematicmapping.org/downloads/world_borders.php
Country level boundaries compatible with ISO 3166-1 country codes.
Use convertTMWorldBorders() to download and convert this
data set.
https://www2.census.gov/geo/tiger/TIGER2021/CBSA/
The USCensusCBSA dataset is a simple features data frame which represents Core Based Statistical Areas (CBSAs) as defined by the Office of Management and Budget (OMB). CBSAs consist of the county or counties or equivalent entities associated with at least one core (urbanized area or urban cluster) of at least 10,000 population, plus adjacent counties having a high degree of social and economic integration with the core as measured through commuting ties with the counties associated with the core.
Use convertUSCensusCBSA() to download and convert this
data set.
The USCensusUrbanAreas dataset is a simple features data frame which represent the urban areas delineated by the US Census that represent densely developed territory. There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people.
Use convertUSCensusUrbanAreas() to download and convert
this data set.
The USFSRangerDistricts dataset is a simple features data frame representing US Forest Service ranger district administrative boundaries. Ranger districts are sub units of National Forests intended to identify the specific organizational units that administer areas.
Use convertUSFSRangerDistricts() to download and convert
this data set.
Each WBDHU# dataset contains a simple features data frame polygons delineating watersheds from the USGS Watershed Boundary Dataset (WBD) at different Hydrologic Unit levels. This is a seamless, national dataset which each polygon represents the area of the landscape that drains to a portion of the stream network.
User input is required to specify the level of data to
generate. The level must be one of the following: [2, 4, 6,
8, 10, 12 or 14]. To generate a Level 8 data set, run
convertWBDHUC(level = 8) which will generate a file named
WBDHU8.rda.
Use convertWBDHUC() to download and convert this data
set.
This creates a simple features data frame that represents public zone weather forecast areas. The NWS issues forecasts, and some watches and warnings, for public zones which are usually the same as counties but in many cases are subsets of counties. Counties are subset into smaller zones to allow for more accurate forecasts because of differences in weather within a county due to such things as elevation, or proximity to large bodies of water.
Use convertWeatherZones() to download and convert this
data set.
This creates a simple features data frame that represents World Exclusive Economic Zones Boundaries. An exclusive economic zone is a sea zone prescribed by the 1982 United Nations Convention on the Law of the Sea over which a state has special rights regarding the exploration and use of marine resources, including energy production from water and wind.
Use convertWorldEEZ() to download and convert this data
set.