Wisconsin Statewide Public Lands Classification
An ongoing statewide classification methodology for identifying publicly owned land across approximately 3.5 million Wisconsin parcels.
ONGOING DEVELOPMENT · 2026–PRESENT
Python · ArcGIS Pro · Statewide Parcel Data · Workflow Automation · QA/QC
Overview & Technical Ownership
This ongoing statewide GIS project develops a repeatable parcel-based methodology for identifying and classifying publicly owned lands across approximately 3.5 million Wisconsin parcels. I am responsible for the day-to-day technical development and implementation: exploring attributes, refining methodology, writing processing scripts, automating workflows, investigating edge cases, validating results, and documenting decision rules. Periodic review with State Cartographer’s Office staff strengthens the methodology through professional input and discussion of unusual data conditions.
The Data Challenge
Wisconsin’s statewide parcel data are assembled from county-level parcel and assessment information. Assessor classifications, ownership information, attribute completeness, county conventions, parcel identifiers, and classification-value combinations vary substantially. The core challenge is building a statewide methodology that works consistently without assuming every county represents parcel information in the same way.
Classification Methodology
The developing framework uses multiple parcel attributes—including assessor auxiliary classification, property classification, ownership/name information, and additional patterns or identifiers where useful—to produce tiered outcomes: 1 — Public / Yes; 2 — Uncertain / Requires additional consideration; 3 — Private / No. It is an iterative, documented methodology rather than one simplistic query.
Phase 1
Broad structural classification based on major assessment attributes and their relationship.
Phase 2
Detailed classification logic evaluates auxiliary-class combinations and other parcel characteristics.
Phase 3
Patterns, identifiers, ownership information, validation, and investigation refine uncertain records.
Scripting, Automation & QA/QC
Python and ArcGIS Pro are necessary to process large parcel datasets, implement classification logic, automate repetitive processing, validate results, and maintain reproducible outputs. Results are repeatedly reviewed as unusual combinations and new edge cases surface, with classification reasoning documented and compared across differing county conventions.
REPLACEABLE VISUALS: STATEWIDE CLASSIFICATION MAP · PARCEL VIEW · ARCGIS PRO RESULTS · WORKFLOW DIAGRAM
Ongoing Development · 2026–Present
The classification methodology remains under active development and validation as additional parcel-data inconsistencies, edge cases, and statewide patterns are identified.