Data quality

Build resilience on reliable data with data quality verification and correction

From location points to polygons, ensure farm plot data integrity. Automate validation, eliminate errors, and meet regulatory standards with confidence.

The Challenge

Ensuring data quality and compliance​ for agricultural supply chains

Accurate and traceable farm plot location data is essential for ensuring supply chain transparency, monitoring sustainability performance, and reducing environmental risks in agriculture. As stakeholder expectations rise, these capabilities have also become a regulatory requirement under frameworks such as the EU Deforestation Regulation (EUDR). Plot data can typically be collected either as polygons—representing precise mapped boundaries—or as points indicating general location coordinates. Picterra’s advanced geoAI technology provides powerful tools to verify the quality of this data, helping you maintain high integrity and meet the highest standards. With Picterra Tracer, you can automate the detection and correction of common data issues, and generate detailed reports and visualizations to support both compliance and ongoing monitoring.

Verification​ & correction

Point and polygon quality verification​ and correction

Point verification​

Our platform automates detecting and correcting common errors, such as misplaced points due to projection issues or manual entry mistakes. 

Incorrectly placed points due to projection errors

Correction of wrong coordinates

Incorrectly placed points due to projection errors

Incorrectly placed points due to projection errors

Points over ocean

Incorrectly placed points due to projection errors

Polygon verification​

Polygon data often presents challenges, such as self-intersecting boundaries, incorrect placements, or missing geographic information. Picterra’s tools simplify the process of detecting and correcting these issues.

Correction of self-intersections and outliers in a dataset of polygons

Correction of self-intersections

Correction of self-intersections and outliers in a dataset of polygons

Verification of unusual size of polygons

Unusual size

Verification of unusual size of polygons

Verification of unusual size of polygons

Unusual size

Verification of unusual size of polygons

Line instead of a polygon

Correction of wrong geometry type

Line instead of a polygon

Verification of unusual size of polygons

Unusual size

Verification of unusual size of polygons

Line instead of a polygon

Correction of wrong geometry type

Line instead of a polygon

Correction by splitting the polygons with holes to multi-polygons

Holes in polygons

Correction by splitting the polygons with holes to multi-polygons

Correction of wrong vertices with inner and/or outer loops

Misconfigured vertices in polygon loops

Correction of wrong vertices with inner and/or outer loops

The solution

Supplier data aggregation, quality verification, and management

Managing supplier data involves collecting, verifying, and unifying data from various formats, which can be complex. Picterra Tracer simplifies this by ensuring data from different suppliers, whether in CSV, KML, or other formats, is readable and GIS-ready.  Our system consolidates files into a unified database, performs rigorous quality checks, and corrects common data errors. This process includes handling typos, inverted data points, mismatched points, and polygons and maintaining high data integrity through automated workflows.

Farm plots data

1. Farm plots data

Data quality verification - +30 stress points

2. Data quality verification - +30 stress points

Geolocation data classification

3. Geolocation data classification

Aggregated & unified supply chain database

4. Aggregated & unified supply chain database

We use AI-powered data extraction to fill gaps when supplier data is incomplete. As a result, we provide a quality-verified, aggregated database of farm plots accessible on the Picterra Tracer. This includes detailed plot maps, visualizations, and statistics per supplier, region, and time, ensuring a single source of truth and aiding in comprehensive compliance and accountability.

 
gif showing the phrases of a data quality assessment

Overall assessment

Picterra comprehensively assesses your dataset’s quality, ensuring all data points and polygons are accurate and complete. Our solution offers detailed reporting on all corrections, enhancing transparency and reliability. Features like automatic detection of duplicate geometries and ensuring projection consistency are part of our holistic approach to data quality.

Driving sustainability and compliance with accurate data

EUDR compliance

Meet the EU Deforestation Regulation requirements with accurate farm plots data.

Source responsibly

See where materials come from and how they impact people and planet.

Detect risks

Reveal hidden threats in land use, supply chains, and operations.

Discover how Picterra ensures data quality across your supply chains

Frequently asked questions

Geospatial data quality refers to the accuracy, completeness and consistency of location and boundary data associated with farms and production plots. Poor-quality data — from incorrect coordinates to invalid or overlapping farm boundaries — can undermine supply chain traceability, sustainability monitoring and compliance assessments. Picterra helps organizations validate and standardize this data before it is used for analysis and reporting.