I work with GIS, UAV data processing, photogrammetry and spatial-data automation, building practical workflows that transform raw geospatial data into structured analytical products and technical deliverables.

My current work includes orthophoto generation, DSM/DTM/nDSM processing, point-cloud analysis, 3D reconstruction, spatial QA and PyQGIS automation using QGIS, WebODM, CloudCompare, PDAL and Python.

In parallel, I develop my Software QA skills through practical testing projects involving requirements analysis, test-case design, defect reporting, regression/retesting, SQL validation, API testing fundamentals and Git/GitHub workflows.

I have 7 years of professional experience in DJI UAV diagnostics, including technical troubleshooting, hardware diagnostics, warranty assessment and systematic fault identification.

I am currently looking for opportunities in GIS, UAV data processing and Software QA, including roles in Wrocław and remote positions.

• GIS and spatial-data analysis
• UAV / drone data processing and photogrammetry
• Python and PyQGIS automation
• LiDAR / point-cloud processing
• DSM / DTM / nDSM analysis
• Spatial databases and SQL
• Software QA and manual testing
• API testing fundamentals
• Building practical GIS/UAV processing applications and automation workflows

An end-to-end UAV photogrammetry and GIS case study based on imagery captured with a DJI Mini 4K.

The project covers the complete workflow from source imagery to validated analytical and 3D outputs:

• 51 UAV images: 31 nadir + 20 oblique;
• automated and manual image QA;
• WebODM photogrammetric processing;
• orthophoto generation;
• DSM / DTM validation and terrain-model refinement;
• 0.25 m nDSM generation and relative-height analysis;
• dense point-cloud inspection in CloudCompare;
• comparison of nadir-only vs nadir + oblique 3D reconstruction;
• final QGIS cartographic products;
• 37-page technical report.

The addition of oblique imagery substantially improved façade reconstruction and overall 3D model completeness compared with the nadir-only dataset.

View the full Sunderland project →

A PyQGIS workflow that extracts roof and ground elevations from UAV-derived DSM / DTM models and generates structured building data for acoustic analysis.

The original GIS Proof of Concept was subsequently used as a real software test object.

The QA case study includes:

• Software Requirements Specification (SRS)
• functional and non-functional requirements
• Test Plan
• 21 designed test cases
• positive and negative testing
• controlled test data preparation
• defect reporting in Jira
• defect lifecycle and retesting
• SQL / SQLite / GeoPackage validation in DBeaver
• independent spatial calculation verification in QGIS
• Git / GitHub version control

The repository represents an application-ready QA portfolio milestone rather than a completed test campaign.

End-to-end UAV photogrammetry workflow covering image QA, WebODM processing, orthophoto generation, terrain-model refinement, nDSM analysis, point-cloud QA and 3D reconstruction.

PyQGIS automation for extracting building elevation information from DSM/DTM data, combined with a structured software QA case study.

QGIS / GeoPackage / PostGIS workflow for transforming inconsistent spatial records into a clean and structured geospatial database.

Point-cloud processing using CloudCompare, CSF and PDAL to classify ground points and generate Digital Terrain Models.

Automated extraction of rooftop slope and aspect statistics from UAV-derived surface models for solar-energy analysis.

PyQGIS workflow for automated terrain slope calculations from elevation datasets.

• QGIS
• PyQGIS
• GeoPackage
• PostGIS
• Rasterio
• GDAL

• WebODM
• CloudCompare
• PDAL
• DSM / DTM / nDSM
• point-cloud processing
• orthomosaic workflows

• Python
• NumPy
• Pandas
• SQL
• SQLite

• Manual testing
• Test case design
• Requirements analysis
• Functional testing
• Negative testing
• Regression / retesting
• Jira
• DBeaver
• SQL validation
• Postman — fundamentals
• DevTools — fundamentals
• Git / GitHub

Before focusing on GIS and software development, I spent approximately 7 years working with DJI UAV systems.

My responsibilities developed from repair work into technical diagnostics and warranty-related assessment. This experience built strong habits around:

• systematic troubleshooting,
• fault isolation,
• technical documentation,
• analysing unexpected system behaviour,
• attention to detail,
• working with complex hardware/software systems.

I now apply the same diagnostic mindset to spatial-data workflows and software QA.

I am currently open to full-time opportunities in:

• GIS / Geospatial Analysis
• UAV / Drone Data Processing
• GIS Automation
• Junior Software QA / Manual Testing
• GIS + QA hybrid roles

I am particularly interested in Wrocław-based opportunities and remote positions where GIS, Python, spatial data, UAV processing or software quality overlap.

Alongside my job search, I continue developing practical UAV/GIS processing workflows and a longer-term application concept for automating drone-data processing and delivery.

Location: Wrocław, Poland
LinkedIn: linkedin.com/in/igor-hajducki
GitHub: github.com/IgorH-GIS

Open to full-time employment, B2B cooperation and selected freelance GIS / UAV data-processing projects.