Analysis

Aurora provides spatial and statistical analysis tools directly within the Map Builder.

All analysis is initiated from a map and operates on the map?s active layers and current spatial context.

Analysis results can be visualized immediately in the map and used in dashboards and datasets.

Overview

Analysis in Aurora is map-driven.

Users select an analysis category and tool from the Map Builder, then configure parameters using the map?s datasets and spatial extent.

Analysis can:

• Generate new layers

• Produce summary statistics

• Highlight spatial patterns

• Create derived datasets

• Feed dashboards and charts

Analysis Categories

Aurora provides several analysis categories within Maps.

Proximity & Distance

Tools for distance-based spatial relationships.

Includes:

• Buffer ? create distance zones around features

• Nearest ? find nearest features

• Proximity ? analyze distance relationships

• Center & Dispersion ? spatial central tendency

• Outliers ? distance-based outlier detection

Overlay & Join (Vector)

Vector overlay and spatial relationship tools.

Includes:

• Intersect ? geometric intersection of layers

• Overlay Layers ? combine spatial layers

• Join ? spatial attribute join

• Join Features (Aggregated) ? aggregated spatial join

• Summarize Within ? summarize features inside areas

• Summarize Nearby ? summarize nearby features

• Erase ? remove overlapping geometry

Spatial Pattern Analysis

Pattern detection and density visualization tools.

Includes:

• Clustering ? group spatial clusters

• Heatmap ? density surface visualization

• Hot Spots ? statistically significant clusters

• Outliers ? spatial anomaly detection

Routing

Network-based spatial analysis.

Routing tools operate on network datasets to compute paths and connectivity.

Raster Analysis

Analysis of raster datasets.

Raster tools compute statistics and spatial relationships based on raster cell values within the map extent or selected areas.

Feature Tools

Geometry and feature-level operations applied to map layers.

These tools modify or derive features directly within the map context.

Time Analysis

Temporal analysis tools for time-enabled datasets.

Includes:

• Time Cube ? spatiotemporal aggregation

• Forecast / Rolling Average ? temporal trend analysis

Map-Driven Execution

All analysis operates within the current map context.

This means analysis uses:

• Active layers

• Visible features

• Map extent

• Spatial selection

• Radius / proximity settings

• Time slider (if enabled)

This ensures analysis reflects what the user is viewing.

Results

Analysis results may:

• Create new map layers

• Highlight features

• Generate statistics

• Produce derived datasets

• Feed dashboard widgets

Results appear immediately in the map.

Relationship to Maps

Analysis is a core capability of the Maps module.

Maps provide:

• Spatial context

• Layer selection

• Interaction tools

• Visualization

• Filtering

• Time controls

Analysis extends map exploration into spatial computation.

Relationship to Dashboards

Analysis outputs can be used in dashboards.

Examples:

• Hotspot layers in maps

• Outlier summaries in widgets

• Proximity results in charts

• Raster statistics in analysis panels

Dashboards visualize results produced in maps.

Typical Uses

Aurora map analysis supports:

• Proximity studies

• Coverage analysis

• Spatial clustering

• Density mapping

• Overlay comparisons

• Network routing

• Temporal trends

• Raster statistics

• Spatial aggregation

Examples:

• Schools within 1 km of hospitals

• Crime hotspots

• Population density

• Service coverage

• Nearest facilities

• Time-series trends

• Raster suitability