Maximilian Lengenfelder

Cleaned, processed, meaningfully structured and spatially analysed raw open data about infrastructure problems from the ZüriWieNeu platform – revealing patterns in maintenance demand across city districts.

Built a Europe-wide wildfire risk indicator using a bivariate environmental index. Combined ecological value and vulnerability to identify high-priority hotspots — demonstrating scalable geocomputation across continental datasets.

What actually happens under the hood of common spatial algorithms? Flickr photo data across German cities and parks is used to implement spatial algorithms from scratch — without libraries — to understand the principles behind them.

Automated extraction of unstructured location data from WHO reports. Built a Python pipeline using pdfplumber and the Gemini API to extract and geocode place names — turning PDF documents into mappable spatial data.

Do wildfire patterns in Bolivia show long-term trends — and where? MODIS satellite data from 2000 to 2024 is analysed via Google Earth Engine to identify spatial distribution and multi-year fire dynamics.

Which areas of Canton Bern are most susceptible to landslides? A hazard map based on the Frequency Ratio method combines slope gradient, geology and land use to calculate a Landslide Susceptibility Index (LSI) — implemented in ArcGIS Pro.

Does map design measurably affect how well people navigate? GPS tracking data and statistical analysis in R were used to empirically test whether different map styles influence orientation efficiency in the field.