Spatially assessing unpleasant places with hard- and soft-GIS methods: a river landscape application

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Röing, S.; Gottwald, S.; Hermes, J.; Schmidt, S.; Albert, C.: Spatially assessing unpleasant places with hard- and soft-GIS methods: a river landscape application. In: Ecosystems and People 17 (2021), Nr. 1, S. 358-369. DOI: https://doi.org/10.1080/26395916.2021.1944912

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/15747

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Sum total of downloads: 36




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Abstract: 
This paper explores the visual, acoustic and olfactory impairments to landscape aesthetic quality in a river landscape case study, using hard- and soft-GIS approaches. The research objectives are (1) to develop a model that localizes the spatial distribution of areas likely perceived as unpleasant and assesses the intensity of visual, acoustic and olfactory impairments in those areas by using a hard-GIS method, and (2) to test the statistical validity of the model based on results gained from a soft GIS method. The case study area is the Lahn river landscape, Germany. Results show a substantial share of the study area affected by modelled impairments, especially areas close to urban environments and along rivers. The area affected by impairments is highest for visual (91%), followed by acoustic (84%) and olfactory factors (54%). However, impairment intensities are greatest for acoustics (30% of study area) and visual (18%). Soft-GIS data tests revealed statistical defensibility of modeled impaired areas. The results highlight the importance of disaggregate analyses of impairments and can provide information on suitable locations for interventions to minimize impairments. Combining hard-GIS with soft-GIS methods may contribute to the credibility, relevance and legitimacy of scientific findings for planning processes and decision-making.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2021
Appears in Collections:Fakultät für Architektur und Landschaft

distribution of downloads over the selected time period:

downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 10 27.78%
2 image of flag of Russian Federation Russian Federation 9 25.00%
3 image of flag of Czech Republic Czech Republic 8 22.22%
4 image of flag of United States United States 4 11.11%
5 image of flag of Japan Japan 1 2.78%
6 image of flag of Indonesia Indonesia 1 2.78%
7 image of flag of France France 1 2.78%
8 image of flag of Europe Europe 1 2.78%
9 image of flag of Australia Australia 1 2.78%

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