THB students present innovative residential analysis in Brandenburg

THB students present innovative residential analysis in Brandenburg

Cologne students develop innovative methods for assessing residential areas

An exciting project comes from the Brandenburg University of Technology (THB), where students have designed a new method for the data-based classification of residential areas in Brandenburg an der Havel. Loud Meeting point Brandenburg A variety of specialist data and statistical methods such as cluster analysis, factor analysis and discriminant analysis were used.

The students took into account a wide range of relevant indicators, including proximity to doctors, schools, daycare centers as well as shopping facilities and green areas. The result of their work was clearly presented in interactive maps, making the information accessible to decision-makers and citizens. The final presentation took place in front of employees from the Statistics and Elections Department as well as members of the Rent Index Working Group. The head of the department, Conny Thiele, praised the results, which can serve as a solid scientific basis for future residential location calculations. Professor André Nitze emphasized the practical relevance of the project and emphasized how useful it is for applying the skills the students have learned.

Diverse data and analysis

In addition to developing this method, the residential area maps from 2019 to 2023 were also analyzed, providing various formats such as shapefile, CSV and GML. For this purpose, the comprehensive data is used Govdata referred. The most important publication dates of the residential area maps from the last few years are as follows:

• 2019: Verfügbar seit 21.01.2022
• 2020: Verfügbar seit 21.01.2022
• 2021: Verfügbar seit 21.01.2022
• 2022: Verfügbar seit 11.04.2022
• 2023: Verfügbar seit 27.03.2023

The ability to use this data in different formats is of great value for further analysis. The provision of such data creates the conditions for well-founded decisions in urban planning and the real estate market.

The importance of cluster analysis

A key tool in this project is cluster analysis. How Novustat explains, this is a standard procedure in statistics and data mining that is used to group observations. The goal is to create homogeneous groups in which the units are similar to each other while the groups are significantly different.

Cluster analysis is important not only in urban research, but also in other areas such as psychology, medicine and marketing. The procedure involves several steps, including determining the distance measure, forming groups and interpreting the results. The THB students have used this theoretical knowledge to achieve concrete, practice-relevant results.

Overall, the project demonstrates a successful connection between theory and practice and makes a significant contribution to data-supported residential assessment. It remains exciting to see how these research results are implemented in practice and what further possibilities future urban development opens up in Brandenburg an der Havel.