Standardize, normalize, and validate spatial data — deterministically.
Geospatial Schema is a reference resource for GIS data managers, government technology teams, and Python ETL engineers building production pipelines against INSPIRE, FGDC, OGC, ISO 19115, and local government schemas. Each guide pairs declarative configuration patterns with executable examples so transformations stay idempotent and auditable.
Explore attribute mapping rules, CRS normalization workflows, validation gates, batch sync strategies, CI gating, and compliance reporting — organized into three core subject areas below.
Start here
Practical, production-tested guides that get straight to executable code and measurable thresholds.
EPSG Code Normalization for Mixed Datasets
Step-by-step: parse EPSG codes from shapefiles, GeoPackages, and PostGIS tables, canonicalize to WKT2, and cache lookups for high-throughput batch jobs.
Batch-Transforming 10k Shapefiles Without Memory Leaks
Iterator-based streaming pipeline in Python that processes tens of thousands of shapefiles with a bounded memory footprint and deterministic error handling.
Exponential Backoff in Schema Mapping Jobs
Resilient retry logic for transient failures in ETL pipelines: configurable backoff, jitter, circuit-breaker integration, and structured error telemetry.
Mapping INSPIRE Annex III to PostgreSQL Schemas
Declarative field mappings, mandatory code list enumerations, and automated validation queries for conforming local PostgreSQL databases to INSPIRE Annex III.
Tolerance Thresholds for Automated Coordinate Snapping
Derive snapping tolerances from CRS axis metadata, apply dynamic unit conversion, and enforce them in validation gates without hardcoded magic numbers.
Converting FGDC CSDGM to ISO 19115 Automatically
XSLT-driven conversion pipeline that maps all mandatory CSDGM elements to their ISO 19115-1 counterparts with validation against the official XSD schemas.
What you’ll find here
Every guide is engineered for production use: declarative schema configurations, strict tolerance thresholds, deterministic CRS handling, and auditable CI gating. Browse by topic or follow the cross-links between guides to assemble an end-to-end pipeline.
Schema Architecture & Standards
FGDC Metadata Mapping: Implementation Patterns for Automated Schema Transformation
In production geospatial pipelines, FGDC Metadata Mapping operates as a deterministic transformation stage rather than a manual documentation exercise. This…
Local Government Data Dictionaries
Enforce municipal data dictionaries as a deterministic ETL pipeline stage. Covers version-controlled YAML field manifests with mandatory/optional tables, alias normalization, a validation engine with domain/pattern/datetime guards and CRS sync, failure-mode routing, audit-trail output, and CI gating for cross-agency GIS exports.
Cross-Platform Schema Translation
Translate geospatial schemas deterministically across Esri, PostGIS, GeoPackage, and GeoParquet. Covers YAML mapping manifests, pydantic/pyproj execution engines, failure-mode routing, lineage logging, and CI gating for ETL pipelines.
INSPIRE Directive Schema Compliance: Automated Annex II/III Conformance
Build a deterministic INSPIRE Directive compliance stage: a declarative Annex II/III manifest, ETRS89/LAEA CRS synchronization, attribute validation with fallback routing, auditable compliance reports, and a CI gate that blocks non-conformant geospatial data.
CRS Normalization & Sync
Projection Normalization Workflows
Build a deterministic projection normalization stage for geospatial ETL pipelines. Covers YAML CRS mapping manifests, pyproj resolution with CRSError/ProjError handling, pre-transform validity gating, tolerance enforcement, audit-trail output, failure-mode routing, and CI gating.
Unit Conversion & Tolerance Thresholds
Implement deterministic unit conversion and tolerance thresholds in Python geospatial ETL pipelines. Covers YAML configuration, vectorized scaling, snap/round/drift gating, failure-mode routing, ISO 19115 compliance logging, and CI integration.
Multi-CRS Dataset Harmonization
Harmonize datasets arriving in mixed coordinate reference systems into one authoritative target CRS. Covers YAML routing manifests, per-source datum transforms with pyproj, tolerance and topology gates, quarantine routing, lineage logging, and CI gating for geospatial ETL.
Datum Transformation Fallback Chains
Implement deterministic datum transformation fallback chains in Python ETL pipelines. Covers YAML configuration, pyproj TransformerGroup routing, failure-mode tables, compliance logging, and CI gating for geospatial schema normalization.
Attribute Transformation & ETL
Error Handling & Retry Logic for Geospatial Schema Mapping Pipelines
Engineer deterministic error handling and retry logic for geospatial ETL: config-as-code retry policies, exponential backoff, dead-letter routing, idempotent writes, audit-grade rejection logs, and CI gating for government and enterprise GIS workflows.
Nested JSON/GeoJSON Flattening for Geospatial ETL Pipelines
Flatten deeply nested JSON and GeoJSON payloads deterministically: dot-notation mapping manifests, RFC 7946-safe geometry preservation, mandatory/optional field routing, streaming execution, compliance logging, and CI gating for government and enterprise GIS workflows.
Batch Schema Processing Pipelines for Geospatial Standardization
Implement deterministic batch schema processing pipelines for geospatial ETL: configuration-as-code manifests, streaming execution, failure routing, compliance reporting, and CI integration for government and enterprise GIS workflows.
Field Renaming & Type Coercion Rules for Geospatial ETL Pipelines
Engineer deterministic field renaming and type coercion for geospatial ETL: declarative YAML contracts, pyarrow precision guards, null and tolerance enforcement, failure routing, compliance audit output, and CI gating for government and enterprise GIS data.