Climate change adaptation indicators in major coastal cities
Description
This dataset was compiled to support research on climate change adaptation indicators and how they have changed in major coastal cities. The database was established based on elements available in an existing monitoring indicator database (Goonesekera & Olazabal, 2021[dataset]: https://doi.org/10.5281/zenodo.5705687). This dataset was updated with newly available indicators and a coding scheme established for the purposes of the research conducted by authors. The dataset contains monitoring indicators extracted from climate-motivated planning documents of Athens, Auckland, Barcelona, Glasgow, Lima, Montreal, Nagoya, New York City, Vancouver, and Tokyo. The data set covers two time periods: 2015-2019 and 2020-2024. It contains details extracted from public sources and codes assigned according to the protocols and codebook established during the research, ‘Tracking urban climate change adaptation over time: Evidence from indicator-based monitoring systems of major coastal cities.’ For details, consult the corresponding research article and supplementary materials.
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Steps to reproduce
The database was established as part of the research ‘Tracking urban climate change adaptation over time: Evidence from indicator-based monitoring systems of major coastal cities’ during which an existing monitoring indicator database (Goonesekera & Olazabal, 2021[dataset]: https://doi.org/10.5281/zenodo.5705687) was updated and modified for the purposes of the corresponding research. 1.1 Quality criteria The protocol was established to apply quality criteria for the use of secondary data in research. The criteria applied when verifying and updating the indicator database were Authenticity, Credibility, Representativeness and Meaning (Largan & Morris, 2019; Scott 1990). 1.2 Database verification The steps were taken to verify the content of the indicator database established by Goonesekera & Olazabal (2021). The original source documents were obtained by using an internet search, and compiled and translated accordingly. The database content was reviewed in relation to the indicator definition set in the research and in relation to the available source documents. 1.3 Updating the database The indicator database was updated with newly available indicators of the sample cities. The search for newly established adaptation in climate-motivated planning documents was conducted between July 2024 and October 2024. The priority was to find the most recent adaptation-focused plan; if no such plan was available, a climate change plan or other climate-motivated plan was searched. The database was updated with new indicators and relevant details extracted from these new planning documents. 1.4 Coding process. Step 1: Adaptation relevance. Indicators in the database were reviewed, marked for their relevance to adaptation, and coded accordingly. Step 2: Adaptation benefit pathways. All adaptation-relevant indicators were coded deductively based on the inferred and most explicit adaptation benefits pathway they relate to, as per an established codebook. Step 3: Adaptation benefitting unit and hazards. The associated benefitting unit or system(s) and hazards were inferred and coded in relation to the benefit pathways. Step 4: Other supporting codes. Other supporting codes such as sectoral domain, process or outcome orientation were specified. The full process of establishing this dataset is described in the corresponding manuscript/research article and supplementary material.
Institutions
- University of HelsinkiUusimaa, Helsinki