DETER

Overview

DETER (Real-Time Detection System) is a satellite-based monitoring system operated by INPE (National Institute of Space Research) that detects and reports changes in forest cover with near real-time frequency. This system provides:

  • Forest cover change detection: Identifies deforestation and forest degradation events
  • Near real-time monitoring: Updates frequently (typically daily or weekly)
  • Spatial precision: Geolocated detection of disturbances with geographic coordinates
  • Biome coverage: Monitors Legal Amazon and Cerrado biome regions
  • Event-based data: Each detection is a separate record with location and date
  • Historical records: Accumulated database of past detection events

DETER is the primary early-warning system for deforestation in the Amazon, used by Brazilian environmental agencies for enforcement, research institutions for analysis, and internationally for monitoring compliance with forest conservation goals.

Data Source and Methodology

DETER monitoring: - Uses satellite imagery from multiple sources (MODIS, Landsat, Sentinel) - Automated and manual analysis to detect recent disturbances - Generates “alerts” - polyons representing areas of detected change - Updates available regularly (frequency varies by satellite availability) - Operated by INPE’s Remote Sensing Division

For technical details, visit INPE DETER System.

Available Datasets

1. deter_amz (DETER Amazon)

DETER monitoring data for the Legal Amazon biome.

  • Geographic coverage: Legal Amazon region (approximately 5 million km²)
  • Biome: Tropical forest
  • Time period: Historical data spanning multiple years with continuing updates
  • Spatial unit: Polyons/spatial geometries with municipality identification
  • Variables: Detection date, deforestation/degradation type, area, municipality, state
  • Update frequency: Regular updates (typically daily or weekly)
  • Use cases:
    • Monitor recent deforestation hotspots
    • Analyze deforestation trends in specific regions
    • Track enforcement impact on forest cover
    • Early-warning system for forest loss
    • Academic research on deforestation drivers

2. deter_cerrado (DETER Cerrado)

DETER monitoring data for the Cerrado biome.

  • Geographic coverage: Cerrado region (Brazilian tropical savanna)
  • Biome: Tropical savanna/grassland
  • Time period: Historical data with continuing updates
  • Spatial unit: Polygons/spatial geometries with municipality identification
  • Variables: Detection date, vegetation loss type, area, municipality, state
  • Update frequency: Regular updates
  • Use cases:
    • Monitor Cerrado vegetation loss (increasingly threatened biome)
    • Analyze agricultural expansion in Cerrado region
    • Compare forest and savanna degradation patterns
    • Track conservation effectiveness

Important Data Characteristics

Raw Data Structure

The raw DETER data from INPE reports one alert/detection per row, with each row typically associated with a single municipality in the raw data. However, many alerts actually overlap multiple municipalities (typically 2-4 municipalities) that are not all shown in the original records. ### Data Processing

This package provides an important enhancement: spatial intersection with IBGE municipality geometries (2019 version) to identify ALL municipalities that each DETER alert overlaps with. This creates a more complete and accurate geographic picture than the original raw data.

Important note on CRS metadata: The CRS (Coordinate Reference System) information may need verification after loading, as coordinate system metadata can sometimes be unclear in the original INPE data.

Function Parameters

1. dataset

Selects which biome’s DETER data to download.

dataset = "deter_amz"      # Legal Amazon monitoring
dataset = "deter_cerrado"  # Cerrado biome monitoring

2. raw_data

Controls whether to download the original data or the processed/enhanced version.

  • TRUE: Returns raw INPE data with limited municipality information
  • FALSE: Returns treated data with spatial intersection to identify all affected municipalities, standardized English variable names
raw_data = FALSE  # logical

Recommendation: Use raw_data = FALSE to get the enhanced municipality identification from spatial intersection.

3. language

Output language for variable names and documentation.

  • "pt": Portuguese
  • "eng": English
language = "eng"  # character string

Examples

# download treated DETER Amazon data
deter_amz <- load_deter(
  dataset = "deter_amz",
  raw_data = FALSE,
  language = "eng"
)

# download treated DETER Cerrado data
deter_cerrado <- load_deter(
  dataset = "deter_cerrado",
  raw_data = FALSE,
  language = "eng"
)

Data Notes

Raw Data Limitations

  • Original INPE data: Shows one alert per municipality, even when alerts overlap multiple municipalities
  • Enhanced version: Spatial intersection with IBGE 2019 municipality boundaries identifies all affected municipalities
  • Advantage of treated data: More complete geographic picture of deforestation extent

Data Structure

Each alert/row typically contains: - Spatial geometry: Polygon coordinates (SF object) - Detection date: When the alert was issued - Alert type: Deforestation, forest degradation, or other disturbance - Area: Size of detected change in hectares - Municipality: Geographic unit identification - State: Brazilian state - Metadata: Satellite source, confidence level (varies by product)

Important Considerations

  1. Alert types vary: “Deforestation” is permanent forest loss; “degradation” is forest damage but not clear-cut
  2. Near real-time data: Alerts are issued frequently; data is continuously updated
  3. Minimum detection size: Varies by sensor; typically 25 hectares for Amazon, larger for Cerrado
  4. CRS metadata: Verify coordinate system after loading; typically UTM zones for Brazil
  5. Overlapping municipalities: Enhanced version accounts for alerts crossing municipality boundaries
  6. False positives possible: Satellite detection can occasionally misclassify cloud shadows or other features as forest loss