Data underlying the MSc research project: Human-nature connectedness of the Teplica stream of Senica

DOI:10.4121/874e9667-a19b-4e1b-83d9-ec324c93df52.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/874e9667-a19b-4e1b-83d9-ec324c93df52

Datacite citation style

Rajmane, Shreya; Letsios, Vasileios; Lee, Youjin (2025): Data underlying the MSc research project: Human-nature connectedness of the Teplica stream of Senica. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/874e9667-a19b-4e1b-83d9-ec324c93df52.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

This dataset contains quantitative data on urban stream restoration of the Teplica River in Senica, Slovakia, as part of the research project Human-Nature Connectedness of the Teplica Stream in Senica.

In this research, a combined approach across three themes —Biodiversity, Quality of Life, and Climate Adaptation—was used to assess the current condition of the Teplica stream.

For this case study:

  • The river was divided into stream segments at 200-meter intervals.
  • In each segment, different criteria were measured to determine the current situation, using buffer zones of varying radii around the stream, depending on the specific criteria measured.

Two data-driven methods were applied:

  1. Spatial Multi-Criteria Decision Analysis (S-MCDA). S-MCDA was used to weigh and compare the different measured criteria within the objectives of biodiversity, climate adaptation, and quality of life. This method supports decision-making by evaluating and ranking the criteria to identify priority areas for intervention.
  2. Typology Construction. Typology construction, using the k-clustering means, was used to group criteria into homogenous clusters based on similarities, allowing the identification of patterns within the dataset. These clusters help to understand which types of interventions would be most impactful within specific segments of the Teplica stream.

In this dataset both the units of measure and the criteria measured can be found.

History

  • 2025-06-30 first online, published, posted

Publisher

4TU.ResearchData

Format

.gkpg

Organizations

TU Delft, Faculty of Architecture and the Built Environment

DATA

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