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Hot Spot Analysis Worker

Processes hot spot analysis jobs using Getis-Ord Gi* statistics.

Overview

The hot spot analysis worker identifies statistically significant clusters of high and low values in spatial data using the Getis-Ord Gi* statistic.

Job Type

hotspot_analysis

Input Parameters

{
  "dataset_id": 123,
  "value_field": "population",
  "neighbor_type": "distance",
  "distance": 1000,
  "output_mode": "static"
}

Parameters

dataset_id (required): Source dataset ID
value_field (required): Numeric field to analyze
neighbor_type (optional): "distance" or "knn" (default: "distance")
distance (required if neighbor_type="distance"): Distance threshold in dataset units
k_neighbors (required if neighbor_type="knn"): Number of nearest neighbors
output_mode (optional): "static", "view", or "materialized_view" (default: "static")

Output

Creates a new dataset with hot spot analysis results:

Gi Z-Score*: Standardized z-score indicating hot/cold spots
P-Value: Statistical significance
Hot Spot Class: Categorized classes (99% hot, 95% hot, 90% hot, not significant, 90% cold, 95% cold, 99% cold)

Output Modes

Static Table (default)

Results stored in a permanent table spatial_data_{output_id}. Best for:

Final results that won't change
Maximum query performance
Historical snapshots

View

Results stored as a database view. Best for:

Results that should update when source data changes
Real-time analysis
Reduced storage requirements

Materialized View

Results stored as a materialized view. Best for:

Large datasets requiring periodic refresh
Balance between performance and freshness
Scheduled updates

Algorithm

The worker uses PostGIS functions to:

Calculate spatial weights matrix based on neighbor type
Compute Getis-Ord Gi* statistic for each feature
Calculate z-scores and p-values
Categorize results into hot spot classes
Store results in output table/view

Example

# Enqueue a hot spot analysis job via API
curl -X POST "https://example.com/api/analysis_hotspot_run.php" \
  -H "Content-Type: application/json" \
  -d '{
    "dataset_id": 123,
    "value_field": "population",
    "neighbor_type": "distance",
    "distance": 1000
  }'

# Worker processes the job automatically
# Check status via API
curl "https://example.com/api/job_status.php?job_id=456"

Background Jobs

This analysis runs as a background job. The worker:

Fetches queued hotspot_analysis jobs
Validates input parameters
Executes PostGIS analysis queries
Creates output dataset
Marks job as completed

Performance Considerations

Processing time depends on dataset size and neighbor configuration
Distance-based analysis may be slower for large datasets
KNN-based analysis is generally faster
Consider using materialized views for very large datasets

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