Lenka Hasova is PhD student at University of Bristol.


  • Geography
  • Data Science
  • GIS


  • PhD in Advanced Quantitative Methods, 2024

    University of Bristol

  • Geographic Data Science, 2018

    University of Liverpool

  • GIS, Cartography and Remote Sensing, 2017

    University of Ostrava










Geospatial Analyst & Data Scientist


Apr 2022 – Oct 2022 Bristol
My most recent experience was a placement with Zsah Ltd, a company with an emerging geospatial team. As part of the placement, I've looked at topics such as accessibility modelling for Royal Mail Delivery offices, custom network building with OSM, scalable routing algorithms and naive rush-hour time estimation. The placement helped me understand what kind of problems a third-sector company faces and allowed me to gain some experience with the geospatial data infrastructure.

Bristol Open Data Hackaton project

GIthub source

Nov 2019 – Present Bristol
Winning the Bristol Open Data project pitch, my team works on interactive solar potential map. Combining LIDAR data with geodemographics will help us to measure solar potential on multiple scales, from detailed picture for every roof to overall picture for wards areas.

Geospatial Analyst


Apr 2019 – Sep 2019 Bristol
As part of the Digital Insight team, I have had a chance to collaborate on several Highways projects, providing GIS data management support and data analysis. My major contribution, however, has been as data science support to ‘Predictive Pollution Support’ project for one of the clients. I have developed a model that can identify locations with a higher risk of a pollution incident on sewage, which helped the client to redistribute their resources more effectively. This has been an extremely valuable experience and helped me to understand the real problems that engineering companies face on everyday bases.

CDRC Masters Dissertation poject


Jun 2018 – Sep 2018 Nottingham
Through CDRC, I worked on a Research project for a Boots UK. The study investigates the relationship between GP's and pharmacies through spatial interaction modelling and looks at the possibilities of prediction patients flow.

Recent Posts

Retrieving custom networks from OSM using Pyrosm and translating to Pandana and NetworkX

Here I show you an easy trick to retrieve completely custom networks from OSM, using Pyrosm, without extra packages and unnecessary …

Google Summer of Code 2021

Here I post about the progress, struggle and success of working on project under GSoC 2021

Calculating Walking distance in Python. Networkx vs Pandana.

This post will show you how you can calculate walking distances along OSM road network in matter of miliseconds.

Distribution of Children homes in Czech Republic

Extracting data from XML and geocoding adresses and creating maps

Global Food Hazard Network

An investigation into the identification network of global food hazards.

Recent Publications and research

Quickly discover relevant content by filtering publications.

Proximity and Distance Decay, chapter in GIS&T Body of Knowledge

Distance decay is an essential concept in geography. At its core, distance decay describes how the relationship between two entities …

Modelling Urban Flows, Spatial Effects in Origin-Destination data

This paper is an introduction of preliminary research for Ph.D. thesis ‘Machine Learning methods for Urban Flows, spatial effects …

Form and Function in Spatial Interaction - A New Approach to Spatial Structure

Gravity Spatial Interaction Models have been used consistently to model migration, commuting, and trade. However, classic gravity …