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datazoom.amazonia

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The datazoom.amazonia package facilitates access to official Brazilian Amazon data, including agriculture, deforestation, production. The package provides functions that download and pre-process selected datasets.

Installation

You can install the released version of datazoom.amazonia from CRAN with:

install.packages("datazoom.amazonia")

And the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("datazoompuc/datazoom.amazonia")

1 - Environmental data

<table> <tr> <td>

| | | |-----------------------|----------------------------------------| | PRODES | Yearly deforestation | | DETER | Alerts on forest cover changes | | DEGRAD | Forest degradation | | Imazon | Deforestation pressure in the Amazon |

</td> <td>

| | | |-----------------------------------|-------------------------------------| | IBAMA | Environmental fines | | MapBiomas | Land cover and land use | | TerraClimate | Climate data | | SEEG | Greenhouse gas emission estimates | | CENSOAGRO | Agriculture activities |

</td> </tr> </table>

2 - Social data

<table> <tr> <td>

| | | |-------------------------------|----------------------------------------------| | IPS | Amazon Social Progress Index | | IEMA | Access to electricity in the Amazon region | | Population | Population |

</td> </tr> </table>

3 - Economic data

<table> <tr> <td>

| | | |-----------------------------|---------------------------------| | COMEX | Brazilian foreign trade | | BACI | Global foreign trade | | PIB-Munic | Municipal GDP | | CEMPRE | Central register of companies | | PAM | Agricultural production |

</td> <td>

| | | |-------------------------|---------------------------| | PEVS | Forestry and extraction | | PPM | Livestock farming | | SIGMINE | Mining | | ANEEL | Energy development | | EPE | Energy consumption |

</td> </tr> </table>

4 - Other tools

<table> <tr> <td>

| | | |-----------------------------------------------------------------|-----------------------------------------------------------------------------| | Legal Amazon Municipalities | Dataset with Brazilian cities and whether they belong to the Legal Amazon | | The ‘googledrive’ package | Troubleshooting and information for downloads from Google Drive |

</table>

Environmental Data

PRODES

The PRODES project uses satellites to monitor deforestation in Brazil’s Legal Amazon. The raw data reports total and incremental (year-by-year) low-cut deforested area at the municipality level, going back to the year 2007.

INPE’s most recent data is now published at TerraBrasilis. We read their full raster data for the Legal Amazon region and extract values onto the map of Brazilian municipalities.

---

Options:

1. dataset: "deforestation", "residual_deforestation", "native_vegetation", "hydrography", "non_forest", or "clouds"

2. raw_data: there are two options:

   • TRUE: if you want the data as it is originally, read as a SpatRaster.
   • FALSE: if you want the treated version of the data, measuring affected areas per municipality.

3. time_period: picks the years for which the data will be downloaded, under the following constraints:

   • For dataset "deforestation", it can be between 2007 and 2023. Deforestation for 2007 includes all cumulative deforestation up to 2007. For other years, deforestation is incremental;
   • For dataset "residual_deforestation", it can be between 2010 and 2023;
   • For all other datasets, only the year 2023 is available.

4. language: you can choose between Portuguese ("pt") and English ("eng")

---

Examples:

# Download treated data (raw_data = FALSE)
# in portuguese (language = 'pt').
data <- load_prodes(
  dataset = "deforestation",
  raw_data = FALSE,
  time_period = 2020:2023,
  language = "pt"
)

DETER

DETER uses satellite surveillance to detect and report changes in forest cover across the Legal Amazon and the Cerrado biome. Each data point consists of a warning, describing which type of change has affected a certain area of forest at a given date. Broadly speaking, it makes a distinction between events of deforestation, degradation and logging. The data extracted here spans from 2016 onward in the Amazon, and from 2018 onward in the Cerrado.

The raw DETER data shows one warning per row, with each row also containing a municipality. However, many warnings actually overlap with 2 or up to 4 municipalities, which are not shown in the original data. Therefore, when the option raw_data = FALSE is selected, the original spatial information is intersected with a municipalities map of Brazil, and each warning can be split into more than one row, with each row corresponding to a municipality.

---

Options:

1. dataset: there are two options:
   • "deter_amz" for data from the Amazon
   • "deter_cerrado" for data from the Cerrado
2. raw_data: there are two options:
   • TRUE: if you want the data as it is originally.
   • FALSE: if you want the treated version of the data.
3. language: you can choose between Portuguese ("pt") and English ("eng")

---

Examples:

# Download treated data (raw_data = FALSE) from Amazonia (dataset = "deter_amz")
deter_amz <- load_deter(
  dataset = "deter_amz",
  raw_data = FALSE
)

DEGRAD

The DEGRAD project uses satellites to monitor degradation of forest areas. Raw data is available as simple features (sf) objects, read from shapefiles. The project was substituted in 2016 by DETER-B. Accordingly, data is available from 2007 up to 2016.

Original documentation for this data is very scarce, users beware. Some things to keep in mind are:

Event data is organized through yearly editions (DEGRAD 2007-2016). Inside a given edition however, there may be data from different years (events that happened in 2015 inside DEGRAD 2016 for example).

This package provides degradation data with municipality identification. It does this by intersecting DEGRAD geometries with IBGE’s municipality geometries from the year 2019. CRS metadata however is missing from the original data source. A best effort approach is used and a CRS is assumed (proj4string: "+proj=longlat +ellps=aust_SA +towgs84=-66.8700,4.3700,-38.5200,0.0,0.0,0.0,0.0 +no_defs").

---

Options: