Evaluating Usability of Python Tools for Spatial Distance Calculations : A Case Study on Vegetation Risk Assessment in Power Line Corridors

The identification of hazardous vegetation encroachment in power line corridors has shifted from manual inspections to automated remote sensing. While prior research has improved monitoring efficiency and accuracy, little attention has been paid to the quality assessment from a Geographic Information System (GIS) development perspective. To address this research gap, this thesis aims to enhance a computational solution based on Python for vegetation risk assessments in power line corridors, with a focus on improving the usability of distance calculations between power lines and risk trees. The thesis followed two main approaches: 1) implement an alternative PostGIS-based solution, and 2) evaluate and compare its usability against the existing Esri's File Geodatabase (FGDB) and ArcPy approach through a feature analysis case study guided by the DESMET framework. The feature analysis indicates that the PostGIS solution outperforms the ArcPy/FGDB approach, particularly in terms of shorter execution times for distance calculations. When interpreted through the ISO/IEC 25010 usability criteria, which encompass effectiveness, efficiency, and satisfaction, PostGIS matches ArcPy in task completion and outperforms it in terms of time efficiency, cost-effectiveness, and overall user satisfaction. Consequently, these findings support recommending PostGIS to enhance usability in vegetation risk assessment workflows. However, as DESMET evaluations are context-dependent, PostGIS may not be optimal in all scenarios. In conclusion, this thesis presents a replicable and adaptable evaluation framework to guide future usability evaluations of geospatial tools and workflows, highlighting the importance of aligning tool selection and workflow optimisation with user needs, organisational goals, and context-specific requirements.