Spatial Statistics and Geospatial Data Analysis

We compute counts, averages and other statistics by geographic area, reported as tables and maps.

• Zonal Statistics for Parcels or Areas

  Compare geographic variables by polygon.

  Expected deliverables: Zonal statistics table and attributed polygon layer.

• Zonal Histogram of Raster Categories

  Count pixels of each raster class within each zone.

  Expected deliverables: Zone-class table, counts, resampling settings and QA map.

• Geographic Counts Table by Zone

  Count point observations within each polygon.

  Expected deliverables: Counts CSV, enriched layer and verifiable map.

We map areas where specified records, activities or geographic phenomena are concentrated.

• Point Density or Concentration Map

  Map the spatial distribution of records.

  Expected deliverables: Density raster, PDF map and kernel-parameter sheet.

• Line Density per Unit Area

  Represent route-line length by analysis zone.

  Expected deliverables: Line-density raster/layer, neighborhood definition and units.

We produce estimated-value surfaces from point measurements, documenting methods and limitations.

• Interpolated Surface from Measurements

  Visualize spatial variations in point observations.

  Expected deliverables: Interpolated raster, map and method/validation sheet.

• Methodological Comparison of Two Interpolated Surfaces

  Compare how two methods change the result on the same measurements.

  Expected deliverables: Two rasters, difference map and parameter protocol.

We examine spatial distributions to identify concentrations, clusters and statistical relationships.

• Summary of Territorial Groupings and Clusters

  Detect concentrations using a declared method.

  Expected deliverables: Cluster layer, statistical summary and method settings.

• Exploratory Nearest Neighbor Analysis

  Describe point geometry and spacing patterns.

  Expected deliverables: Distance report and nearest-neighbor statistics with point map.

• Identification of Density Clusters Using Temporal DBSCAN

  Find groups of dated points in space and time.

  Expected deliverables: Cluster-labeled layers, epsilon/minPts settings and sequence map.

We document statistical variables, methods and parameters to support review and repeatability.

• Reproducible Geospatial Statistical Analysis

  Geographic variables need statistical processing.

  Expected deliverables: Spatial-statistics estimation table in GPKG with CSV intervals; reproducible modeling report with an R script and technical HTML or PDF output; statistical-uncertainty map in GeoPackage or GeoTIFF.

• Spatial Summary by Category with Statistical Export

  Produce reproducible tables for grouped observations and areas.

  Expected deliverables: Descriptive class tables and calculation file with formulas and parameters.

We prepare spatial samples and examine the distribution of observations, measurements or records.

• Mean Center and Dispersion of Locations

  Describe the center of weighted or unweighted points.

  Expected deliverables: Central points, parameter table and spatial extent map.

• Documented Random Selection of Records or Points

  Produce a reproducible sample within selected zones.

  Expected deliverables: Sampled records or points in CSV or GPKG, with the random seed, sampling rules and exclusions.