Max Leshne
Pronouns: He/Him/His
Research Mentor(s): Martin Macias Medellin
Research Mentor School/College/Department: Political Science / LSA
Program: UROP
Session: Session 6 (3:40pm – 4:30pm)
Authors: Max Leshne, Martin Macias Medellin
Abstract
Plenty of research has been done examining the relationship between various types of terrain and the warfare and conflict that occurs in them. For example, the strategic importance of mountainous terrain is well known as mountains are easily defendable positions. However, there has been little research done on the effect of different types of urban structures on warfare and conflict. It is commonly assumed in military theory that cities are challenging for conventional armies because of the built up environment, but there has not been a systematic test of this argument. Cities are uniquely structured; no city is exactly the same as another. Perhaps it is for this reason that research has strayed away from considering the effects of urban terrain on urban conflict. The goal of this project is to change this. Through collection of physical characteristics of urban areas (heights of buildings, quality of buildings, types of roads, and the type of area surrounding these buildings), this research team aims to collect data to train a supervised machine learning model to predict the heights and potentially the shapes of buildings. Data of Ukrainian cities was collected using Google Maps and findings were documented in a spreadsheet to later be analyzed. Data of Ukrainian cities was collected specifically because a significant portion of the fighting in the Russo-Ukraine War has taken place in urban areas. Once a machine learning model has been trained to analyze the characteristics of urban areas, more can be learned about the connection (or lack thereof) between urban areas and their effect on conflict and warfare. Right now, this project is still in the data collection stage.
