The package allows direct access to data from the BDQueimadas system, including:
-
🔥 Heat spots
-
🌡️ Fire risk index
-
🌧️ Associated meteorological variables
-
🌎 Spatial information (state, municipality, biome)
-
⚡ FRP (Fire Radiative Power)
The data are official and public, provided by the National Institute for Space Research through the Queimadas Program.
🔗 To learn more about INPE's Queimadas Program, visit the portal.
# Install remotes (if necessary)
install.packages("remotes")
# Install the package
remotes::install_github("wtassinari/queimadasR", force = TRUE)install.packages("queimadasR_0.1.0.tar.gz", repos = NULL, type = "source")The general workflow of the package involves:
-
Define the period and filters (state, satellite, etc.)
-
Download the data
-
Perform exploratory analyses or modelling
Simple example:
# -----------------------------------------------------------------------------
# First, source this file to load the function into your R session:
# source("download_fire_spots.R")
# -----------------------------------------------------------------------------
library(queimadasR)
# --- Example 1: All satellites, single month, entire Brazil ------------------
# Downloads every fire spot detected across Brazil during September 2023,
# using all available satellites, with deduplication enabled.
df_brazil <- download_fire_spots(
start_date_str = "01/09/2023",
end_date_str = "30/09/2023",
deduplicate_final = TRUE
)
head(df_brazil)
nrow(df_brazil)
# --- Example 2: Northern region, peak fire season, all satellites ------------
# Covers the 7 states of Brazil's Legal Amazon during the Aug–Sep 2023
# fire season. Deduplication removes records shared across satellite passes.
north_states <- c("ACRE", "AMAPA", "AMAZONAS", "PARA",
"RONDONIA", "RORAIMA", "TOCANTINS")
df_north <- download_fire_spots(
start_date_str = "01/08/2023",
end_date_str = "2/08/2023",
target_states = north_states,
deduplicate_final = TRUE
)
head(df_north)
table(df_north$estado) # fire spots per state
# --- Example 3: Specific satellites, two states, single year -----------------
# Useful when you only want data from GOES-16 (geostationary) and
# AQUA_T (polar orbit) for a targeted area.
df_goes_aqua <- download_fire_spots(
start_date_str = "15/08/2022",
end_date_str = "30/09/2022",
target_states = c("MATO GROSSO", "TOCANTINS"),
target_satellites = c("GOES-16", "AQUA_T"),
deduplicate_final = TRUE
)
table(df_goes_aqua$satelite) # confirm which satellites are present
# --- Example 4: Multi-year download (2020–2022), single state ----------------
# The function automatically loops over each year and combines the results.
# Increase timeout if your connection is slow.
df_multiyear <- download_fire_spots(
start_date_str = "01/07/2020",
end_date_str = "31/10/2022",
target_states = c("MATO GROSSO"),
deduplicate_final = TRUE,
timeout = 600 # 10 minutes per year
)
# Count fire spots per year
table(df_multiyear$ref_year)
# --- Example 5: No deduplication, custom dedup keys, inspect satellites ------
# Download without deduplication so you can inspect the raw data first,
# then manually deduplicate using only lat/lon/datetime.
df_raw <- download_fire_spots(
start_date_str = "01/09/2024",
end_date_str = "30/09/2024",
target_states = c("PARA", "MARANHAO"),
deduplicate_final = FALSE,
show_satellites_when_empty = TRUE
)
# Check which satellites are present before deciding how to deduplicate
sort(table(df_raw$satelite), decreasing = TRUE)
# Manually deduplicate using only coordinates + datetime
df_deduped <- df_raw[!duplicated(df_raw[, c("latitude", "longitude", "data_pas")]), ]
nrow(df_raw) - nrow(df_deduped) # how many duplicates were removed
# --- Example 6: Save results to CSV ------------------------------------------
df_to_save <- download_fire_spots(
start_date_str = "01/08/2023",
end_date_str = "31/08/2023",
target_states = c("AMAZONAS", "PARA"),
deduplicate_final = TRUE
)
write.csv(df_to_save, "fire_spots_AM_PA_aug2023.csv", row.names = FALSE)
cat("File saved:", nrow(df_to_save), "records\n")
The download_focos() function returns a dataframe with the following variables:
| Variable | Type | Description |
|---|---|---|
latitude |
num | Geographic latitude coordinate of the heat spot (in decimal degrees) |
longitude |
num | Geographic longitude coordinate of the heat spot (in decimal degrees) |
data_pas |
POSIXct | Date and time of the satellite pass (format: YYYY-MM-DD HH:MM:SS) |
satelite |
chr | Satellite that performed the detection (e.g.: AQUA_M-T, NOAA-20, NOAA-21, TERRA, etc.) |
pais |
chr | Country where the spot was detected |
estado |
chr | Federative unit (state) where the spot was detected |
municipio |
chr | Name of the municipality where the spot was detected |
bioma |
chr | Brazilian biome where the spot occurred (Amazon, Cerrado, Atlantic Forest, Caatinga, Pampa, Pantanal) |
numero_dias_sem_chuva |
num | Number of consecutive days without precipitation in the region |
precipitacao |
num | Accumulated precipitation in the period (in mm) |
risco_fogo |
num | Fire risk index calculated by INPE (scale 0–1) |
id_area_industrial |
int | Industrial area identifier (0 = non-industrial, 1 = industrial) |
frp |
num | Fire Radiative Power (in MW) |
ano_ref |
int | Reference year of the detection |
Geographic coordinates (latitude, longitude)
- Precision: approximately 1 km (resolution of the reference satellites)
- Format: decimal degrees (e.g.: -9.30, -68.30)
Satellites (satelite)
- AQUA_M-T: Aqua satellite (Morning-Afternoon Mission) — primary reference
- TERRA_M-T: Terra satellite (Morning-Afternoon Mission)
- NOAA-20/21: NOAA series satellites (National Oceanic and Atmospheric Administration)
- NPP-375: Suomi NPP satellite
Brazilian biomes (bioma)
- Amazon
- Cerrado
- Atlantic Forest
- Caatinga
- Pampa
- Pantanal
FRP (Fire Radiative Power)
- Measures the intensity of the fire
- Higher values indicate more intense spots
- Unit: Megawatts (MW)
- Useful for estimating gas and particulate matter emissions
Fire risk (risco_fogo)
- Index calculated by INPE based on:
- Meteorological conditions
- Soil moisture
- Vegetation type
- Fire history
- Scale: 0 (low risk) to 1 (high risk)
Satellites Examples included in the dataset:
- AQUA_M-T
- TERRA_M-T
- NOAA-20 / NOAA-21
- NPP-375
The package can be used for:
- Environmental and ecological studies
- Seasonal fire monitoring
- Spatio-temporal modelling
- Studies on the health impacts of wildfires
- Integration with epidemiological databases
The development of this package would not have been possible without the open data freely provided by INPE's Queimadas Program and the work of the entire team involved in environmental monitoring in Brazil.
Special thanks to the National Institute for Space Research (INPE) for making the data available and for their essential work in monitoring wildfires and forest fires across Brazilian territory.
We recommend that users also cite the official data source in their scientific publications.
We ask users to cite the package whenever it is used in research or publications, acknowledging the work of all authors involved.
TASSINARI, Wagner S.; PACIFICO, Roni dos Santos Jorge; FERREIRA, Manuela dos Santos; OLIVEIRA, Liliane de Fátima Antônio; HOKERBERG, Yara Hahr Marques; SANTOS, Heloísa Ferreira Pinto and SAUCHA, Camylla Veloso Valença; OLIVEIRA, Raquel de Vasconcellos Carvalhaes.
. queimadasR: Pacote para download e análise de dados de queimadas do INPE. Versão 0.1.0. 2024. Disponível em: https://github.com/wtassinari/queimadasR
@software{queimadasR2026,
title = {queimadasR: Pacote para download e análise de dados de queimadas do INPE},
author = {TASSINARI, Wagner S. and PACIFICO, Roni dos Santos Jorge and FERREIRA, Manuela dos Santos and OLIVEIRA, Liliane de Fátima Antônio and HOKERBERG, Yara Hahr Marques and SANTOS, Heloísa Ferreira Pinto and SAUCHA, Camylla Veloso Valença and OLIVEIRA, Raquel de Vasconcellos Carvalhaes},
organization = {Universidade Federal Rural do Rio de Janeiro e Instituto Nacional de Infectologia/FIOCRUZ},
year = {2026},
version = {0.2.0},
doi = {10.5281/zenodo.18879882},
url = {https://doi.org/10.5281/zenodo.18879882}
}