Package 'datazoom.amazonia' reference manual

Title:	Simplify Access to Data from the Amazon Region
Description:	Functions to download and treat data regarding the Brazilian Amazon region from a variety of official sources.
Authors:	Igor Rigolon Veiga [aut, cre], DataZoom (PUC-Rio) [fnd], Guilherme Jardim [aut], Daniel AC Barbosa [aut], Bruno Alcantara Duarte [aut], Fredie Didier [aut], Tito Bruni [aut], Luiz Guilherme Lopes Moussatche [aut], Victor Aliende da Matta [aut], Anna Carolina Dutra Saraiva [aut], Arthur Carvalho Brito [aut], Francisco de Lima Cavalcanti [aut], Maria Mittelbach [aut]
Maintainer:	Igor Rigolon Veiga <[email protected]>
License:	MIT + file LICENSE
Version:	1.1.0
Built:	2025-01-22 04:43:12 UTC
Source:	https://github.com/cran/datazoom.amazonia

Decompress a DBC (compressed DBF) file

Description

This function allows you decompress a DBC file into its DBF counterpart. Please note that this is the file format used by the Brazilian Ministry of Health (DATASUS), and it is not related to the FoxPro or CANdb DBC file formats.

Usage

dbc2dbf(input.file, output.file)
dbc2dbf(input.file, output.file)

Arguments

`input.file`	The name of the DBC file (including extension)
`output.file`	The output file name (including extension)

Details

DBC is the extension for compressed DBF files (from the 'XBASE' family of databases). This is a proprietary file format used by the brazilian government to make available public healthcare datasets (by it's agency called DATASUS).

It uses internally the PKWare's Data Compression Library (DCL) "implode" compression algorithm. When decompressed, it becomes a regular DBF file.

Value

Return TRUE if succeded, FALSE otherwise.

Author(s)

Daniela Petruzalek, [email protected]

Source

The internal C code for dbc2dbf is based on blast decompressor and blast-dbf (see References).

References

The PKWare ZIP file format documentation (contains the "implode" algorithm specification) available at https://support.pkware.com, current version https://pkware.cachefly.net/webdocs/casestudies/APPNOTE.TXT.

blast source code in C: https://github.com/madler/zlib/tree/master/contrib/blast

blast-dbf, DBC to DBF command-line decompression tool: https://github.com/eaglebh/blast-dbf

Examples

## Not run: 
# Input file name
in.f <- system.file("files/sids.dbc", package = "read.dbc")

# Output file name
out.f <- tempfile(fileext = ".dbc")

# The call return logi = TRUE on success
if (dbc2dbf(input.file = in.f, output.file = out.f)) {
  print("File decompressed!")
  file.remove(out.f)
}

## End(Not run)

## Not run: 
# Input file name
in.f <- system.file("files/sids.dbc", package = "read.dbc")

# Output file name
out.f <- tempfile(fileext = ".dbc")

# The call return logi = TRUE on success
if (dbc2dbf(input.file = in.f, output.file = out.f)) {
  print("File decompressed!")
  file.remove(out.f)
}

## End(Not run)

ANEEL

Description

National Electric Energy Agency - ANEEL

Usage

load_aneel(dataset, raw_data = FALSE, language = "eng")
load_aneel(dataset, raw_data = FALSE, language = "eng")

Arguments

`dataset`	A dataset name ("energy_development_budget", "energy_generation" or "energy_enterprises_distributed")
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`language`	A `string` that indicates in which language the data will be returned. Portuguese ("pt") and English ("eng") are supported.

Examples

## Not run: 
# download treated data about energy generation
clean_aneel <- load_aneel(
  dataset = "energy_generation",
  raw_data = FALSE
)

## End(Not run)

## Not run: 
# download treated data about energy generation
clean_aneel <- load_aneel(
  dataset = "energy_generation",
  raw_data = FALSE
)

## End(Not run)

BACI - Global international trade

Description

Loads disaggregated data on bilateral trade flows for more than 5000 products and 200 countries.

Usage

load_baci(dataset = "HS92", raw_data = FALSE, time_period, language = "eng")
load_baci(dataset = "HS92", raw_data = FALSE, time_period, language = "eng")

Arguments

`dataset`	A dataset name ("HS92").
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`time_period`	A `numeric` indicating for which years the data will be loaded, in the format YYYY. Can be any vector of numbers, such as 2010:2012.
`language`	A `string` that indicates in which language the data will be returned. Portuguese ("pt") and English ("eng") are supported.

Value

A tibble.

Examples

## Not run: 
# download treated data for 2016 (takes a long time to download)
clean_baci <- load_baci(
  raw_data = FALSE,
  time_period = 2016
)

## End(Not run)

## Not run: 
# download treated data for 2016 (takes a long time to download)
clean_baci <- load_baci(
  raw_data = FALSE,
  time_period = 2016
)

## End(Not run)

Comex - Brazilian external trade

Description

Loads data on all products imported to or exported from Brazil.

Usage

load_br_trade(dataset, raw_data = FALSE, time_period, language = "eng")
load_br_trade(dataset, raw_data = FALSE, time_period, language = "eng")

Arguments

`dataset`	A dataset name ("comex_export_mun", "comex_import_mun", "comex_export_prod" or "comex_import_prod").
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`time_period`	A `numeric` indicating for which years the data will be loaded, in the format YYYY. Can be any vector of numbers, such as 2010:2012.
`language`	A `string` that indicates in which language the data will be returned. Portuguese ("pt") and English ("eng") are supported.

Value

A tibble.

Examples

## Not run: 
# download treated (raw_data = FALSE) exports data by municipality (dataset = "comex_export_mun")
# from 2020 to 2021 (time_period = 2020:2021)
data <- load_br_trade(
  dataset = "comex_export_mun",
  raw_data = FALSE,
  time_period = 2020:2021
)
# download treated(raw_data = FALSE) imports data by municipality (dataset = "comex_import_mun")
# from 2020 to 2021 (time_period = 2020:2021)
data <- load_br_trade(
  dataset = "comex_import_mun",
  raw_data = FALSE,
  time_period = 2020:2021
)

## End(Not run)

## Not run: 
# download treated (raw_data = FALSE) exports data by municipality (dataset = "comex_export_mun")
# from 2020 to 2021 (time_period = 2020:2021)
data <- load_br_trade(
  dataset = "comex_export_mun",
  raw_data = FALSE,
  time_period = 2020:2021
)
# download treated(raw_data = FALSE) imports data by municipality (dataset = "comex_import_mun")
# from 2020 to 2021 (time_period = 2020:2021)
data <- load_br_trade(
  dataset = "comex_import_mun",
  raw_data = FALSE,
  time_period = 2020:2021
)

## End(Not run)

CEMPRE - Central Register of Companies

Description

Loads information on companies and other organizations and their respective formally constituted local units, registered with the CNPJ - National Register of Legal Entities.

Usage

load_cempre(
  dataset = "cempre",
  raw_data = FALSE,
  geo_level,
  time_period,
  language = "eng",
  sectors = FALSE
)
load_cempre(
  dataset = "cempre",
  raw_data = FALSE,
  geo_level,
  time_period,
  language = "eng",
  sectors = FALSE
)

Arguments

`dataset`	A dataset name ("cempre").
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`geo_level`	A `string` that defines the geographic level of the data. Can be one of "country", "state" or "municipality".
`time_period`	A `numeric` indicating for which years the data will be loaded, in the format YYYY. Can be any vector of numbers, such as 2010:2012.
`language`	A `string` that indicates in which language the data will be returned. Portuguese ("pt") and English ("eng") are supported.
`sectors`	A `boolean` that defines if the data will be return separated by sectors (`TRUE`) or not (`FALSE`).

Value

A tibble.

Examples

## Not run: 
# Download raw data (raw_data = TRUE) at the country level
# from 2008 to 2010 (time_period = 2008:2010).
data <- load_cempre(
  raw_data = TRUE,
  geo_level = "country",
  time_period = 2008:2010
)

# Download treted data (raw_data = FALSE) by state (geo_level = "state")
# from 2008 to 2010 (time_period = 2008:2010) in portuguese (language = "pt").
# In this example, data is split by sector (sectors = TRUE)
data <- load_cempre(
  raw_data = FALSE,
  geo_level = "state",
  time_period = 2008:2010,
  language = "pt",
  sectors = TRUE
)

## End(Not run)

## Not run: 
# Download raw data (raw_data = TRUE) at the country level
# from 2008 to 2010 (time_period = 2008:2010).
data <- load_cempre(
  raw_data = TRUE,
  geo_level = "country",
  time_period = 2008:2010
)

# Download treted data (raw_data = FALSE) by state (geo_level = "state")
# from 2008 to 2010 (time_period = 2008:2010) in portuguese (language = "pt").
# In this example, data is split by sector (sectors = TRUE)
data <- load_cempre(
  raw_data = FALSE,
  geo_level = "state",
  time_period = 2008:2010,
  language = "pt",
  sectors = TRUE
)

## End(Not run)

Censo Agropecuario

Description

Loads information on agricultural establishments and activities

Usage

load_censoagro(
  dataset,
  raw_data = FALSE,
  geo_level,
  time_period,
  language = "eng"
)
load_censoagro(
  dataset,
  raw_data = FALSE,
  geo_level,
  time_period,
  language = "eng"
)

Arguments

`dataset`	A dataset name ("agricultural_land_area", "agricultural_area_use", "agricultural_employees_tractors", "agricultural_producer_condition", "animal_species", "animal_products", "vegetable_production_area", "vegetable_production_permanent", "vegetable_production_temporary", "livestock_production").
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`geo_level`	A `string` that defines the geographic level of the data. Can be of "country" or "state". For dataset "livestock_production", can be one of "country", "state", or "municipality"
`time_period`	A `numeric` indicating for which years the data will be loaded, in the format YYYY. Can be any vector of numbers, such as 2010:2012.
`language`	A `string` that indicates in which language the data will be returned. Portuguese ("pt") and English ("eng") are supported.

Value

A tibble.

Examples

## Not run: 
# Download total land area data at the country level in year 2006
data <- load_censoagro(
  dataset = "agricultural_land_area",
  raw_data = TRUE,
  geo_level = "country",
  time_period = 2006
)

# Download temporary production crops data by state (geo_level = "state") in year 2006
  in portuguese (language = "pt").
data <- load_censoagro(
  dataset = "vegetable_production_temporary",
  raw_data = FALSE,
  geo_level = "state",
  time_period = 1996,
  language = "pt"
)

## End(Not run)


## We should include support for microregion/mesoregion


## Not run: 
# Download total land area data at the country level in year 2006
data <- load_censoagro(
  dataset = "agricultural_land_area",
  raw_data = TRUE,
  geo_level = "country",
  time_period = 2006
)

# Download temporary production crops data by state (geo_level = "state") in year 2006
  in portuguese (language = "pt").
data <- load_censoagro(
  dataset = "vegetable_production_temporary",
  raw_data = FALSE,
  geo_level = "state",
  time_period = 1996,
  language = "pt"
)

## End(Not run)


## We should include support for microregion/mesoregion

TerraClimate - Climate monitoring

Description

Spatial data on climate variables, extracted from Climatology Lab's TerraClimate.

Usage

load_climate(
  dataset,
  raw_data = FALSE,
  time_period,
  language = "eng",
  legal_amazon_only = FALSE
)
load_climate(
  dataset,
  raw_data = FALSE,
  time_period,
  language = "eng",
  legal_amazon_only = FALSE
)

Arguments

`dataset`	A dataset name, choosing which variable will be loaded. One of ("max_temperature", "min_temperature", "wind_speed", "vapor_pressure_deficit", "vapor_pressure", "snow_water_equivalent", "shortwave_radiation_flux", "soil_moisture", "runoff", "precipitation", "potential_evaporation", "climatic_water_deficit", "water_evaporation", "palmer_drought_severity_index"). For extra details, try `vignette("TERRACLIMATE")`.
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`time_period`	A `numeric` indicating for which years the data will be loaded, in the format YYYY. Can be any vector of numbers, such as 2010:2012.
`language`	A `string` that indicates in which language the data will be returned. Portuguese ("pt") and English ("eng") are supported.
`legal_amazon_only`	A `boolean` setting the return of Legal Amazon Data (`TRUE`) or Country's Data (`FALSE`). Defaults to `FALSE`

Value

A tibble.

Examples

## Not run: 
# Downloading maximum temperature data from 2000 to 2001
max_temp <- load_climate(dataset = "max_temperature", time_period = 2000:2001)

# Downloading precipitation data only for the legal Amazon in 2010
amz_precipitation <- load_climate(
  dataset = "precipitation",
  time_period = 2010,
  legal_amazon_only = TRUE
)

## End(Not run)

## Not run: 
# Downloading maximum temperature data from 2000 to 2001
max_temp <- load_climate(dataset = "max_temperature", time_period = 2000:2001)

# Downloading precipitation data only for the legal Amazon in 2010
amz_precipitation <- load_climate(
  dataset = "precipitation",
  time_period = 2010,
  legal_amazon_only = TRUE
)

## End(Not run)

DATASUS - Mortality, hospitalizations and hospital beds

Description

Loads DATASUS data on health establishments, mortality, access to health services and several health indicators.

Usage

load_datasus(
  dataset,
  time_period,
  states = "all",
  raw_data = FALSE,
  keep_all = FALSE,
  language = "eng"
)
load_datasus(
  dataset,
  time_period,
  states = "all",
  raw_data = FALSE,
  keep_all = FALSE,
  language = "eng"
)

Arguments

`dataset`	A dataset name, can be one of ("datasus_sim_do", "datasus_sih", "datasus_cnes_lt"), or more. For more details, try `vignette("DATASUS")`.
`time_period`	A `numeric` indicating for which years the data will be loaded, in the format YYYY. Can be any vector of numbers, such as 2010:2012.
`states`	A `string` specifying for which states to download the data. It is "all" by default, but can be a single state such as "AC" or any vector such as c("AC", "AM").
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`keep_all`	A `boolean` choosing whether to aggregate the data by municipality, in turn losing individual-level variables (`FALSE`) or to keep all the original variables. Only applies when raw_data is `TRUE`.
`language`	A `string` that indicates in which language the data will be returned. Portuguese ("pt") and English ("eng") are supported.

Value

A tibble.

Examples

## Not run: 
# download raw data for the year 2010 in the state of AM.
data <- load_datasus(
  dataset = "datasus_sim_do",
  time_period = 2010,
  states = "AM",
  raw_data = TRUE
)

# download treated data with the number of deaths by cause in AM and PA.
data <- load_datasus(
  dataset = "datasus_sim_do",
  time_period = 2010,
  states = c("AM", "PA"),
  raw_data = FALSE
)

# download treated data with the number of deaths by cause in AM and PA
# keeping all individual variables.
data <- load_datasus(
  dataset = "datasus_sim_do",
  time_period = 2010,
  states = c("AM", "PA"),
  raw_data = FALSE,
  keep_all = TRUE
)

## End(Not run)

## Not run: 
# download raw data for the year 2010 in the state of AM.
data <- load_datasus(
  dataset = "datasus_sim_do",
  time_period = 2010,
  states = "AM",
  raw_data = TRUE
)

# download treated data with the number of deaths by cause in AM and PA.
data <- load_datasus(
  dataset = "datasus_sim_do",
  time_period = 2010,
  states = c("AM", "PA"),
  raw_data = FALSE
)

# download treated data with the number of deaths by cause in AM and PA
# keeping all individual variables.
data <- load_datasus(
  dataset = "datasus_sim_do",
  time_period = 2010,
  states = c("AM", "PA"),
  raw_data = FALSE,
  keep_all = TRUE
)

## End(Not run)

Degrad - Forest Degradation in the Brazilian Amazon

Description

Loads information on forest degradation in the Brazilian Amazon, replaced by DETER-B in December 2016.

Usage

load_degrad(
  dataset = "degrad",
  raw_data = FALSE,
  time_period,
  language = "eng"
)
load_degrad(
  dataset = "degrad",
  raw_data = FALSE,
  time_period,
  language = "eng"
)

Arguments

`dataset`	A dataset name ("degrad").
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`time_period`	A `numeric` indicating for which years the data will be loaded, in the format YYYY. Can be any vector of numbers, such as 2010:2012.
`language`	A `string` that indicates in which language the data will be returned. Portuguese ("pt") and English ("eng") are supported.

Value

A list of tibbles (if raw_data = TRUE) or a tibble (if raw_data = FALSE).

Examples

## Not run: 
# download treated data (raw_data = TRUE) related to forest degradation
# from 2010 to 2012 (time_period = 2010:2012).
data <- load_degrad(
  dataset = "degrad",
  raw_data = FALSE,
  time_period = 2010:2012
)

## End(Not run)

## Not run: 
# download treated data (raw_data = TRUE) related to forest degradation
# from 2010 to 2012 (time_period = 2010:2012).
data <- load_degrad(
  dataset = "degrad",
  raw_data = FALSE,
  time_period = 2010:2012
)

## End(Not run)

DETER - Forest Degradation in the Brazilian Amazon

Description

Loads data on changes in forest cover in the Legal Amazon and the Cerrado biome.

Usage

load_deter(dataset, raw_data = FALSE, language = "eng")
load_deter(dataset, raw_data = FALSE, language = "eng")

Arguments

`dataset`	A dataset name ("deter_amz", "deter_cerrado") with information about the Legal Amazon and Cerrado, respectively
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`language`	A `string` that indicates in which language the data will be returned. Portuguese ("pt") and English ("eng") are supported.

Value

A sf object.

Examples

## Not run: 
# Download treated data (raw_data = FALSE) from Amazonia (dataset = "deter_amz")
deter_amz <- load_deter(
  dataset = "deter_amz",
  raw_data = FALSE
)

## End(Not run)

## Not run: 
# Download treated data (raw_data = FALSE) from Amazonia (dataset = "deter_amz")
deter_amz <- load_deter(
  dataset = "deter_amz",
  raw_data = FALSE
)

## End(Not run)

EPE

Description

Electrical Energy Monthly Consumption per Class

Usage

load_epe(dataset, raw_data = FALSE, geo_level = "state", language = "eng")
load_epe(dataset, raw_data = FALSE, geo_level = "state", language = "eng")

Arguments

`dataset`	A dataset name, ("energy_consumption_per_class") or ("national_energy_balance")
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`geo_level`	A geographical level, ("state") or ("subsystem"), only available for "energy_consumption_per_class"
`language`	A `string` that indicates in which language the data will be returned. Portuguese ("pt") and English ("eng") are supported.

Examples

## Not run: 
# download treated data about energy consumption at the state level
clean_epe <- load_epe(
  dataset = "energy_consumption_per_class",
  geo_level = "state",
  raw_data = FALSE
)

## End(Not run)

## Not run: 
# download treated data about energy consumption at the state level
clean_epe <- load_epe(
  dataset = "energy_consumption_per_class",
  geo_level = "state",
  raw_data = FALSE
)

## End(Not run)

IBAMA - Brazilian Institute for the Environment and Renewable Natural Resources

Description

Loads information on environmental fines in the Amazon region

Usage

load_ibama(dataset, raw_data = FALSE, states = "all", language = "eng")
load_ibama(dataset, raw_data = FALSE, states = "all", language = "eng")

Arguments

`dataset`	A dataset name ("embargoed_areas", "distributed_fines", or "collected_fines")
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`states`	A `string` specifying for which states to download the data. It is "all" by default, but can be a single state such as "AC" or any vector such as c("AC", "AM"). Does not apply to the "embargoed_areas" dataset.
`language`	A `string` that indicates in which language the data will be returned. Currently, only Portuguese ("pt") and English ("eng") are supported.

Value

A tibble.

Examples

## Not run: 
# Download treated embargoes data (raw_data = FALSE) in english (language = "eng")
data <- load_ibama(
  dataset = "embargoed_areas", raw_data = FALSE,
  language = "eng"
)

# Download treated collected fines data from "BA"
data <- load_ibama(
  dataset = "collected_fines", raw_data = FALSE,
  states = "BA", language = "pt"
)

## End(Not run)

## Not run: 
# Download treated embargoes data (raw_data = FALSE) in english (language = "eng")
data <- load_ibama(
  dataset = "embargoed_areas", raw_data = FALSE,
  language = "eng"
)

# Download treated collected fines data from "BA"
data <- load_ibama(
  dataset = "collected_fines", raw_data = FALSE,
  states = "BA", language = "pt"
)

## End(Not run)

IEMA - Institute of Environment and Water Resources

Description

Loads information on electric energy access at the municipality level in the Amazon region

Usage

load_iema(dataset = "iema", raw_data = FALSE, language = "eng")
load_iema(dataset = "iema", raw_data = FALSE, language = "eng")

Arguments

`dataset`	A dataset name ("iema")
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`language`	A `string` that indicates in which language the data will be returned. Portuguese ("pt") and English ("eng") are supported.

Value

A tibble.

Examples

## Not run: 
# Download treated data
data <- load_iema(raw_data = FALSE)

## End(Not run)

## Not run: 
# Download treated data
data <- load_iema(raw_data = FALSE)

## End(Not run)

IMAZON - Deforestation pressure by municipality

Description

Loads data categorizing each municipality by the level of deforestation pressure it faces

Usage

load_imazon(dataset = "imazon_shp", raw_data = FALSE, language = "eng")
load_imazon(dataset = "imazon_shp", raw_data = FALSE, language = "eng")

Arguments

`dataset`	There is one dataset available ("imazon_shp")
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`language`	A `string` that indicates in which language the data will be returned. Portuguese ("pt") and English ("eng") are supported.

Value

A tibble.

Examples

## Not run: 
# Download treated data
data <- load_imazon(raw_data = FALSE)

## End(Not run)

## Not run: 
# Download treated data
data <- load_imazon(raw_data = FALSE)

## End(Not run)

IPS - Amazon Social Progress Index

Description

Loads information on the social and environmental performance of the Legal Amazon.

Usage

load_ips(
  dataset = "all",
  raw_data = FALSE,
  time_period = c(2014, 2018, 2021, 2023),
  language = "eng"
)
load_ips(
  dataset = "all",
  raw_data = FALSE,
  time_period = c(2014, 2018, 2021, 2023),
  language = "eng"
)

Arguments

`dataset`	A dataset name ("all", "life_quality", "sanit_habit", "violence", "educ", "communic", "mortality", or "deforest")
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`time_period`	Year to download. Can be 2014, 2018, 2021, 2023, or a vector with some combination thereof
`language`	A `string` that indicates in which language the data will be returned. Portuguese ("pt") and English ("eng") are supported.

Value

A tibble.

Examples

## Not run: 
# Download raw data from 2014
data <- load_ips(dataset = "all", raw_data = TRUE, time_period = 2014)

# Download treated deforest data from 2018 in portuguese
data <- load_ips(
  dataset = "deforest", raw_data = FALSE,
  time_period = 2018, language = "pt"
)

## End(Not run)

## Not run: 
# Download raw data from 2014
data <- load_ips(dataset = "all", raw_data = TRUE, time_period = 2014)

# Download treated deforest data from 2018 in portuguese
data <- load_ips(
  dataset = "deforest", raw_data = FALSE,
  time_period = 2018, language = "pt"
)

## End(Not run)

MAPBIOMAS - The Annual Land Cover and Use Mapping Project in Brazil

Description

Loads information about land cover and use

Usage

load_mapbiomas(
  dataset,
  raw_data = FALSE,
  geo_level = "municipality",
  language = "eng"
)
load_mapbiomas(
  dataset,
  raw_data = FALSE,
  geo_level = "municipality",
  language = "eng"
)

Arguments

`dataset`	A dataset name ("mapbiomas_cover", "mapbiomas_transition", "mapbiomas_irrigation", "mapbiomas_deforestation_regeneration", "mapbiomas_mining", "mapbiomas_water" or "mapbiomas_fire")
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`geo_level`	A `string` that defines the geographic level of the data For dataset "mapbiomas_cover", can be "municipality" or "state" (faster download) For dataset "mapbiomas_transition", can be "municipality" or "state" (faster download) For dataset "mapbiomas_deforestation_regeneration", can only be "municipality" For dataset "mapbiomas_mining", can be "indigenous_land" or "municipality" For dataset "mapbiomas_irrigation", can be "state" or "biome" For dataset "mapbiomas_water", can be "municipality", "state" or "biome" For dataset "mapbiomas_fire", can only be "state"
`language`	A `string` that indicates in which language the data will be returned. Portuguese ("pt") and English ("eng") are supported.

Value

A tibble.

Examples

## Not run: 
# download treated Mapbiomas Cover data in English
data <- load_mapbiomas(
  dataset = "mapbiomas_cover",
  raw_data = FALSE,
  geo_level = "municipality",
  language = "eng"
)

# download treated data on mining on indigenous lands
data <- load_mapbiomas("mapbiomas_mining",
  raw_data = FALSE,
  geo_level = "indigenous_land"
)

## End(Not run)

## Not run: 
# download treated Mapbiomas Cover data in English
data <- load_mapbiomas(
  dataset = "mapbiomas_cover",
  raw_data = FALSE,
  geo_level = "municipality",
  language = "eng"
)

# download treated data on mining on indigenous lands
data <- load_mapbiomas("mapbiomas_mining",
  raw_data = FALSE,
  geo_level = "indigenous_land"
)

## End(Not run)

PAM - Municipal Agricultural Production

Description

Loads information on the quantity, value and area of temporary and permanent crops cultivated.

Usage

load_pam(dataset, raw_data = FALSE, geo_level, time_period, language = "eng")
load_pam(dataset, raw_data = FALSE, geo_level, time_period, language = "eng")

Arguments

`dataset`	A dataset name ("all_crops", "permanent_crops", "temporary_crops" or many individual crop possibilities (see `vignette(load_pam)`)). You can also use SIDRA codes (see https://sidra.ibge.gov.br/pesquisa/pam/tabelas)
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`geo_level`	A `string` that defines the geographic level of the data. Can be one of "country", "state" or "municipality".
`time_period`	A `numeric` indicating for which years the data will be loaded, in the format YYYY. Can be any vector of numbers, such as 2010:2012.
`language`	A `string` that indicates in which language the data will be returned. Portuguese ("pt") and English ("eng") are supported.

Value

A tibble consisting of geographic units that present positive values for any of the variables in the dataset.

Examples

## Not run: 
# download treated data at the state level from 2010 to 2011 for all crops
data <- load_pam(
  dataset = "all_crops",
  raw_data = FALSE,
  geo_level = "state",
  time_period = 2010:2011,
  language = "eng"
)

## End(Not run)

## Not run: 
# download treated data at the state level from 2010 to 2011 for all crops
data <- load_pam(
  dataset = "all_crops",
  raw_data = FALSE,
  geo_level = "state",
  time_period = 2010:2011,
  language = "eng"
)

## End(Not run)

PEVS - Forestry Activities

Description

Loads information on the amount and value of the production of the exploitation of native plant resources and planted forest massifs, as well as existing total and harvested areas of forest crops.

Usage

load_pevs(dataset, raw_data = FALSE, geo_level, time_period, language = "eng")
load_pevs(dataset, raw_data = FALSE, geo_level, time_period, language = "eng")

Arguments

`dataset`	A dataset name ("pevs_forest_crops", "pevs_silviculture" or "pevs_silviculture_area"). You can also use SIDRA codes (see https://sidra.ibge.gov.br/pesquisa/pevs/quadros/brasil/2019)
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`geo_level`	A `string` that defines the geographic level of the data. Can be one of "country", "region", "state", or "municipality".
`time_period`	A `numeric` indicating for which years the data will be loaded, in the format YYYY. Can be any vector of numbers, such as 2010:2012.
`language`	A `string` that indicates in which language the data will be returned. Portuguese ("pt") and English ("eng") are supported.

Value

A tibble consisting of geographic units that present positive values for any of the variables in the dataset.

Examples

## Not run: 
# Download treated (raw_data = FALSE) silviculture data (dataset = 'pevs_silviculture')
# by state (geo_level = 'state') from 2012 (time_period =  2012)
# in portuguese (language = "pt")
data <- load_pevs(
  dataset = "pevs_silviculture",
  raw_data = FALSE,
  geo_level = "state",
  time_period = 2012,
  language = "pt"
)

# Download raw (raw_data = TRUE) forest crops data by region from 2012 to 2013 in english
data <- load_pevs(
  dataset = "pevs_forest_crops",
  raw_data = TRUE,
  geo_level = "region",
  time_period = 2012:2013
)

## End(Not run)

## Not run: 
# Download treated (raw_data = FALSE) silviculture data (dataset = 'pevs_silviculture')
# by state (geo_level = 'state') from 2012 (time_period =  2012)
# in portuguese (language = "pt")
data <- load_pevs(
  dataset = "pevs_silviculture",
  raw_data = FALSE,
  geo_level = "state",
  time_period = 2012,
  language = "pt"
)

# Download raw (raw_data = TRUE) forest crops data by region from 2012 to 2013 in english
data <- load_pevs(
  dataset = "pevs_forest_crops",
  raw_data = TRUE,
  geo_level = "region",
  time_period = 2012:2013
)

## End(Not run)

PIB MUNICIPAL - Municipal GDP

Description

Loads information on gross domestic product at current prices, taxes, net of subsidies, on products at current prices and gross value added at current prices, total and by economic activity, and respective shares.

Usage

load_pibmunic(
  dataset = "pibmunic",
  raw_data = FALSE,
  geo_level,
  time_period,
  language = "eng"
)
load_pibmunic(
  dataset = "pibmunic",
  raw_data = FALSE,
  geo_level,
  time_period,
  language = "eng"
)

Arguments

`dataset`	A dataset name ("pibmunic") with Municipal GDP information. You can also use SIDRA codes (See https://sidra.ibge.gov.br/pesquisa/pib-munic/tabelas)
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`geo_level`	A `string` that defines the geographic level of the data. Can be one of "country", "state" or "municipality".
`time_period`	A `numeric` indicating for which years the data will be loaded, in the format YYYY. Can be any vector of numbers, such as 2010:2012.
`language`	A `string` that indicates in which language the data will be returned. Portuguese ("pt") and English ("eng") are supported.

Value

A tibble.

Examples

## Not run: 
# download treated municipal GDP data at the state level for 2010 to 2012
data <- load_pibmunic(
  raw_data = FALSE,
  geo_level = "state",
  time_period = 2010:2012
)

## End(Not run)
## Not run: 
# download treated municipal GDP data at the state level for 2010 to 2012
data <- load_pibmunic(
  raw_data = FALSE,
  geo_level = "state",
  time_period = 2010:2012
)

## End(Not run)

Population

Description

Loads information on (estimated) population

Usage

load_population(
  dataset = "population",
  raw_data = FALSE,
  geo_level,
  time_period,
  language = "eng"
)
load_population(
  dataset = "population",
  raw_data = FALSE,
  geo_level,
  time_period,
  language = "eng"
)

Arguments

`dataset`	A dataset name ("population").
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`geo_level`	A `string` that defines the geographic level of the data. Can be one of "country", "state" or "municipality".
`time_period`	A `numeric` indicating for which years the data will be loaded, in the format YYYY. Can be any vector of numbers, such as 2010:2012.
`language`	A `string` that indicates in which language the data will be returned. Portuguese ("pt") and English ("eng") are supported.

Value

A tibble.

Examples

## Not run: 
# Download raw data (raw_data = TRUE) at the country level
# from 2008 to 2010 (time_period = 2008:2010).
data <- load_population(
  raw_data = TRUE,
  geo_level = "country",
  time_period = 2008:2010
)

# Download treted data (raw_data = FALSE) by state (geo_level = "state")
# from 2008 to 2010 (time_period = 2008:2010) in portuguese (language = "pt").
data <- load_population(
  raw_data = FALSE,
  geo_level = "state",
  time_period = 2008:2010,
  language = "pt"
)

## End(Not run)

## Not run: 
# Download raw data (raw_data = TRUE) at the country level
# from 2008 to 2010 (time_period = 2008:2010).
data <- load_population(
  raw_data = TRUE,
  geo_level = "country",
  time_period = 2008:2010
)

# Download treted data (raw_data = FALSE) by state (geo_level = "state")
# from 2008 to 2010 (time_period = 2008:2010) in portuguese (language = "pt").
data <- load_population(
  raw_data = FALSE,
  geo_level = "state",
  time_period = 2008:2010,
  language = "pt"
)

## End(Not run)

PPM - Municipal Livestock Production

Description

Loads information on animal farming inventories and livestock products (IBGE).

Usage

load_ppm(dataset, raw_data = FALSE, geo_level, time_period, language = "eng")
load_ppm(dataset, raw_data = FALSE, geo_level, time_period, language = "eng")

Arguments

`dataset`	A dataset name ("ppm_livestock_inventory", "ppm_sheep_farming", "ppm_animal_orig_production", "ppm_cow_farming" or "ppm_aquaculture". You can also use SIDRA codes (see https://sidra.ibge.gov.br/pesquisa/ppm/tabelas/brasil/2021)
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`geo_level`	A `string` that defines the geographic level of the data. Can be one of "country", "state" or "municipality".
`time_period`	A `numeric` indicating for which years the data will be loaded, in the format YYYY. Can be any vector of numbers, such as 2010:2012.
`language`	A `string` that indicates in which language the data will be returned. Portuguese ("pt") and English ("eng") are supported.

Value

A tibble consisting of geographic units that present positive values for any of the variables in the dataset.

Examples

## Not run: 
# Download treated data (raw_data = FALSE) about aquaculture (dataset = "ppm_aquaculture")
# from 2013 to 2015 (time_period = 2013:2015) in english
# with the level of aggregation being the country (geo_level = "country").
data <- load_ppm(
  dataset = "ppm_aquaculture",
  raw_data = FALSE,
  geo_level = "country",
  time_period = 2013:2015
)

# Download raw data about sheep farming by state from 1980 to 1995 in portuguese (language = "pt")
data <- load_ppm(
  dataset = "ppm_sheep_farming",
  raw_data = TRUE,
  geo_level = "state",
  time_period = 1980:1995,
  language = "pt"
)

## End(Not run)
## Not run: 
# Download treated data (raw_data = FALSE) about aquaculture (dataset = "ppm_aquaculture")
# from 2013 to 2015 (time_period = 2013:2015) in english
# with the level of aggregation being the country (geo_level = "country").
data <- load_ppm(
  dataset = "ppm_aquaculture",
  raw_data = FALSE,
  geo_level = "country",
  time_period = 2013:2015
)

# Download raw data about sheep farming by state from 1980 to 1995 in portuguese (language = "pt")
data <- load_ppm(
  dataset = "ppm_sheep_farming",
  raw_data = TRUE,
  geo_level = "state",
  time_period = 1980:1995,
  language = "pt"
)

## End(Not run)

PRODES - Deforestation Monitoring Project in the Legal Amazon by Satellite

Description

Loads data on deforestation in the Legal Amazon region.

Usage

load_prodes(dataset, raw_data = FALSE, language = "eng")
load_prodes(dataset, raw_data = FALSE, language = "eng")

Arguments

`dataset`	A dataset name ("deforestation").
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`language`	A `string` that indicates in which language the data will be returned. Portuguese ("pt") and English ("eng") are supported.

Value

A tibble with the selected data.

Examples

## Not run: 
# Download treated data (raw_data = FALSE)
# in portuguese (language = 'pt').
data <- load_prodes(
  raw_data = FALSE,
  language = "pt"
)

## End(Not run)

## Not run: 
# Download treated data (raw_data = FALSE)
# in portuguese (language = 'pt').
data <- load_prodes(
  raw_data = FALSE,
  language = "pt"
)

## End(Not run)

Greenhouse gas emission estimates (SEEG)

Description

Loads data of estimates of emission of greenhouse gases

Usage

load_seeg(dataset, raw_data = FALSE, geo_level, language = "eng")
load_seeg(dataset, raw_data = FALSE, geo_level, language = "eng")

Arguments

`dataset`	A dataset name ("seeg", seeg_farming", "seeg_industry", "seeg_energy", "seeg_land", "seeg_residuals"). On which "seeg" contains all five sectors (only works with raw_data = TRUE) and the others are filtered specifically by a main source of emission.
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`geo_level`	A `string` that defines the geographic level of the data. Can be one of "country", "state" or "municipality".
`language`	A `string` that indicates in which language the data will be returned. Portuguese ("pt") and English ("eng") are supported.

Value

A tibble.

Examples

## Not run: 
# Download raw data (raw_data = TRUE) of greenhouse gases (dataset = "seeg")
# by state (geo_level = "state")
data <- load_seeg(
  dataset = "seeg",
  raw_data = TRUE,
  geo_level = "state"
)

# Download treated data (raw_data = FALSE) of industry greenhouse gases (dataset = "seeg_industry")
data <- load_seeg(
  dataset = "seeg_industry",
  raw_data = FALSE,
  geo_level = "state"
)

## End(Not run)
## Not run: 
# Download raw data (raw_data = TRUE) of greenhouse gases (dataset = "seeg")
# by state (geo_level = "state")
data <- load_seeg(
  dataset = "seeg",
  raw_data = TRUE,
  geo_level = "state"
)

# Download treated data (raw_data = FALSE) of industry greenhouse gases (dataset = "seeg_industry")
data <- load_seeg(
  dataset = "seeg_industry",
  raw_data = FALSE,
  geo_level = "state"
)

## End(Not run)

SIGMINE - Mining Geographic Information System

Description

Loads information the mines being explored legally in Brazil, including their location, status, product being mined and area in square meters.

Usage

load_sigmine(dataset = "sigmine_active", raw_data = FALSE, language = "eng")
load_sigmine(dataset = "sigmine_active", raw_data = FALSE, language = "eng")

Arguments

`dataset`	A dataset name ("sigmine_active")
`raw_data`	A `boolean` setting the return of raw (`TRUE`) or processed (`FALSE`) data.
`language`	A `string` that indicates in which language the data will be returned. Portuguese ("pt") and English ("eng") are supported.

Value

A tibble.

Examples

## Not run: 
# Download treated data (raw_data = FALSE) in portuguese (language = "pt").
data <- load_sigmine(
  dataset = "sigmine_active",
  raw_data = FALSE,
  language = "pt"
)

## End(Not run)
## Not run: 
# Download treated data (raw_data = FALSE) in portuguese (language = "pt").
data <- load_sigmine(
  dataset = "sigmine_active",
  raw_data = FALSE,
  language = "pt"
)

## End(Not run)

IBGE codes and Legal Amazon identification of Brazilian municipalities

Description

A dataset containing each municipality's IBGE code, state, mesoregion, microregion, as well as a binary variable for whether it is part of the Legal Amazon. Mostly for our functions' internal use.

Usage

municipalities
municipalities

Format

A data frame with 5570 rows and 12 variables:

code_muni: IBGE 7-digit municipality code
name_muni: municipality name
code_state: 2-digit state code
abbrev_state: state abbreviations (e.g. "AM")
name_state: full name of the states
code_region: 1-digit regional code
name_region: name of the region
legal_amazon: takes value 1 for municipalities in the legal amazon, 0 otherwise
municipality_mapbiomas: municipality name in MAPBIOMAS data
code_micro: 5-digit microregion code
name_micro: name of the microregion
code_meso: 4-digit mesoregion code
name_meso: name of the mesoregion

Source

Package geobr and https://www.ibge.gov.br/geociencias/cartas-e-mapas/mapas-regionais/15819-amazonia-legal.html?=&t=acesso-ao-produto

IBGE codes and MAPBIOMAS id of Brazilian municipalities and biomes

Description

A dataset containing each municipality-biome's IBGE code, state, biome, name and MAPBIOMAS ID. Mostly for our functions' internal use.

Usage

municipalities_biomes
municipalities_biomes

Format

A data frame with 6537 rows and 4 variables:

feature_id: MAPBIOMAS biome-municipality ID
code_muni: IBGE 7-digit municipality code
abbrev_state: state abbreviations (e.g. "AM")
municipality_mapbiomas: municipality name in MAPBIOMAS data
biome: biome

Source

Package geobr and https://mapbiomas.org/

Read Data Stored in DBC (Compressed DBF) Files

Description

This function allows you to read a DBC (compressed DBF) file into a data frame. Please note that this is the file format used by the Brazilian Ministry of Health (DATASUS), and it is not related to the FoxPro or CANdb DBC file formats.

Usage

read.dbc(file, ...)
read.dbc(file, ...)

Arguments

`file`	The name of the DBC file (including extension)
`...`	Further arguments to be passed to `read.dbf`

Details

After decompressing, it reads the temporary DBF file into a data.frame using read.dbf from the foreign package.

Value

A data.frame of the data from the DBC file.

Note

DATASUS is the name of the Department of Informatics of the Brazilian Health System and is responsible for publishing public healthcare data. Besides the DATASUS, the Brazilian National Agency for Supplementary Health (ANS) also uses this file format for its public data.

This function was tested using files from both DATASUS and ANS to ensure compliance with the format, and hence ensure its usability by researchers.

As a final note, neither this project, nor its author, has any association with the brazilian government.

Author(s)

Daniela Petruzalek, [email protected]

Examples

## Not run: 
# The 'sids.dbc' file is the compressed version of 'sids.dbf' from the "foreign" package.
x <- read.dbc(system.file("files/sids.dbc", package = "read.dbc"))
str(x)
summary(x)

# This is a small subset of U.S. NOAA storm database.
storm <- read.dbc(system.file("files/storm.dbc", package = "read.dbc"))
head(x)
str(x)

## Don't run!
## The following code will download data from the "Declarations of Death" database for
## the Brazilian state of Parana, year 2013. Source: DATASUS / Brazilian Ministry of Health
url <- "ftp://ftp.datasus.gov.br/dissemin/publicos/SIM/CID10/DORES/DOPR2013.dbc"
download.file(url, destfile = "DOPR2013.dbc")
dopr <- read.dbc("DOPR2013.dbc")
head(dopr)
str(dopr)

## End(Not run)
## Not run: 
# The 'sids.dbc' file is the compressed version of 'sids.dbf' from the "foreign" package.
x <- read.dbc(system.file("files/sids.dbc", package = "read.dbc"))
str(x)
summary(x)

# This is a small subset of U.S. NOAA storm database.
storm <- read.dbc(system.file("files/storm.dbc", package = "read.dbc"))
head(x)
str(x)

## Don't run!
## The following code will download data from the "Declarations of Death" database for
## the Brazilian state of Parana, year 2013. Source: DATASUS / Brazilian Ministry of Health
url <- "ftp://ftp.datasus.gov.br/dissemin/publicos/SIM/CID10/DORES/DOPR2013.dbc"
download.file(url, destfile = "DOPR2013.dbc")
dopr <- read.dbc("DOPR2013.dbc")
head(dopr)
str(dopr)

## End(Not run)

Package 'datazoom.amazonia'

Help Index

Decompress a DBC (compressed DBF) file

Description

Usage

Arguments

Details

Value

Author(s)

Source

References

See Also

Examples

ANEEL

Description

Usage

Arguments

Examples

BACI - Global international trade

Description

Usage

Arguments

Value

Examples

Comex - Brazilian external trade

Description

Usage

Arguments

Value

Examples

CEMPRE - Central Register of Companies

Description

Usage

Arguments

Value

Examples

Censo Agropecuario

Description

Usage

Arguments

Value

Examples

TerraClimate - Climate monitoring

Description

Usage

Arguments

Value

Examples

DATASUS - Mortality, hospitalizations and hospital beds

Description

Usage

Arguments

Value

Examples

Degrad - Forest Degradation in the Brazilian Amazon

Description

Usage

Arguments

Value

Examples

DETER - Forest Degradation in the Brazilian Amazon

Description

Usage

Arguments

Value

Examples

EPE

Description

Usage

Arguments

Examples

IBAMA - Brazilian Institute for the Environment and Renewable Natural Resources

Description

Usage

Arguments

Value

Examples

IEMA - Institute of Environment and Water Resources

Description

Usage