Projects
The listed projects represent work undertaken across multiple professional contexts, including consulting engagements, employment duties, and independent personal projects. See also Services and Technologies.
The listed projects represent work undertaken across multiple professional contexts, including consulting engagements, employment duties, and independent personal projects. See also Services and Technologies.
Services: GIS Consultancy, GIS Development, Spatial Analysis
Technologies: Python, QGIS
Description: Design and development of a custom GIS tool to map CO2 supply and demand, utilizing a travel distance API and spatial analysis techniques.
Services: GIS Consultancy, GIS Development, Spatial Analysis
Technologies: QGIS, Python
Description: Identification of parcels that are suitable for housing (or other purposes). Retrieval of relevant datasets and utilization of criteria such as proximity to roads, flood zones, land use classification, zoning classification.
Services: GIS Development, GEOINT, Spatial Analysis
Technologies: QGIS, Python
Description: Using a novel approach to identify intense conflict areas and simultaneously attribute them with qualitative information using word clouds. Utilization of ACLED (Armed Conflicts and Location Events' Dataset).
Services: Feature extraction, GIS workflow automation
Technologies: ArcGIS, QGIS, Python, Google Earth
Description: A two-year long project for the production of High Resolution vector layers of European Coastal Zones' Land Use/Land Cover. Extensively involved in production (Feature extraction), quality control and workflow automation. Extraction performed by interpreting SPOT5/SPOT6 imagery. Custom tools built in ArcGIS Model Builder, QGIS Model Designer and Python.
Services: Feature extraction
Technologies: QGIS, Google Earth
Description: Delineation and classification of urban green ground maintenance feature for a municipality. Extraction and interpretation were performed with Ordnance Survey aerial imagery (12.5 cm) and Google Earth as ancillary source.
Services: GIS Development, Spatial Analysis
Technologies: QGIS, Python
Description: This project aims to fill in the gap on automatic implementations of some important LULC operations that are not found on most popular GIS software. Specifically, the core part of the application aims to implement indices of Land Use Mix with commonly found literature methods (mainly Entropy Index and Herfindahl–Hirschman Index).
Services: GIS Development, Spatial Data retrieval, Spatial Analysis
Technologies: QGIS, Python
Description: Green View Index (GVI) is a popular method to map and quantify urban green. Unlike satellite-derived NDVI, it utilizes street-level imagery and is calculated as the ratio of pixels classified as vegetation to the total number of pixels. The plugin is a full implementation of a typical GVI mapping workflow, enabling random point generation, Street View image retrieval, masking of vegetation pixels and calculation of GVI.
Services: GIS Development, Spatial Data retrieval, Spatial Analysis
Technologies: QGIS, Python
Description: Retrieved all administrative regions datasets in Greece, from country level to neighborhood level. Aggregated into one mega-dataset and indexed based on spatial containment.Â
Images copyright: ESRI