Guides

Areas of Interest (AOIs)

Geographic regions that define where your analysis will be performed

Areas of Interest (AOIs)

Areas of Interest (AOIs) define the geographic regions where your analysis will be performed. They answer the "Where?" question of the three fundamental questions framework.

What are AOIs?

AOIs are polygons drawn on a map that specify geographic boundaries for your analysis:

  • Can be simple bounding boxes or complex geometries
  • Define spatial filtering for input data
  • Enable location-based parallelization
  • Can represent any geographic region from buildings to continents

AOI Characteristics

Flexible Geometries

  • Bounding boxes: Simple rectangular areas
  • Complex polygons: Custom shapes following specific boundaries
  • Multi-polygons: Multiple separate regions in a single AOI
  • Any scale: From individual buildings to entire countries

Geographic Scope

AOIs can represent:

  • Individual retail store locations
  • City blocks or neighborhoods
  • Entire cities or metropolitan areas
  • States, provinces, or countries
  • Custom regions (watersheds, industrial zones, etc.)
  • Multiple non-contiguous areas

AOI Collections

AOIs are organized into AOI Collections for efficient batch processing:

Benefits of Collections

  • Group related locations for comparative analysis
  • Enable batch processing across multiple regions
  • Simplify management of multiple AOIs
  • Support parallelization by processing each AOI independently

Example Collections

  • All store locations for a retail chain
  • Competing facilities in a market
  • Multiple sites in a supply chain
  • Regional markets for comparative analysis

AOI Versions

AOIs support versioning to track changes over time:

  • Version history: Track how boundaries change
  • Temporal consistency: Use the same version across time periods
  • Comparison: Compare results using different boundary definitions

Use Cases

Retail Analysis

Define AOIs around store locations to analyze:

  • Foot traffic patterns
  • Vehicle counts in parking lots
  • Competitor activity nearby
  • Market share in the region

Infrastructure Monitoring

Create AOIs for:

  • Construction sites to track progress
  • Transportation hubs (airports, ports)
  • Power plants or industrial facilities
  • Road segments or rail lines

Environmental Analysis

Define regions for:

  • Deforestation monitoring in specific forests
  • Agricultural field analysis
  • Coastal zone monitoring
  • Wildlife habitat tracking

Urban Planning

Analyze specific areas for:

  • Land use changes
  • Building density
  • Green space assessment
  • Development patterns

Data Filtering

AOIs enable spatial filtering of input data:

1. Platform identifies all data sources
         ↓
2. Filters data to only include points/images within AOI boundaries
         ↓
3. Passes filtered data to algorithm
         ↓
4. Algorithm processes only relevant data

This ensures:

  • Efficient processing (no wasted computation on irrelevant data)
  • Focused results (only the regions you care about)
  • Cost optimization (process only what you need)

Parallelization by Location

Each AOI in a collection can be processed independently, enabling:

  • Horizontal scaling: Multiple AOIs processed simultaneously
  • Faster results: Parallel execution reduces total runtime
  • Resource optimization: Distribute workload across containers

Example: Analyzing 100 store locations can run in parallel, with each location processed by a separate container instance.

Creating AOIs

AOIs can be created through:

Elements Application

  • Draw polygons directly on the map interface
  • Upload GeoJSON or Shapefile formats
  • Import from existing geographic databases

Elements API

  • Create programmatically using the SDK
  • Upload bulk AOI collections
  • Generate AOIs from coordinates or WKT strings

Best Practices

Size Considerations

  • Too large: May exceed processing limits or timeout
  • Too small: May not capture enough context
  • Just right: Balance between scope and performance

Boundary Precision

  • Use precise boundaries for specific analyses
  • Consider buffer zones around features
  • Account for data resolution limitations

Collection Organization

  • Group AOIs logically for comparative analysis
  • Keep collection sizes manageable
  • Use naming conventions for easy identification

Next Steps

  • Understand temporal parameters with TOIs
  • Learn about Algorithms that process AOI data
  • Combine into workflows with Analyses
  • Execute on specific regions through Computations

Updated 5 months ago