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UrbanMaple
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Jun 25, 2026
| information on physical livability, social cohesion, housing conditions, | ||
| and demographic characteristics. These datasets are complemented by the | ||
| high-resolution LST data, enabling precise mapping of the urban heat | ||
| distribution. Because distance to green is considered as an |
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You could back it up a bit, with a source and/or explaining why.
UrbanMaple
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Jun 25, 2026
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| To ensure a valid comparative analysis between the two distinct urban | ||
| contexts of Rotterdam and Guangzhou, uniform metrics were applied to both | ||
| cities. Because data availability for Rotterdam was bigger than that of |
UrbanMaple
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Jun 25, 2026
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| To operationalise socio-economic vulnerability within the Spatial | ||
| Justice Index (SJI), several demographic and housing indicators were | ||
| selected. These metrics focus on disadvantaged populations, specifically |
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Beware of the weight of the word disadvantaged, consider a synonym that is less prejudiced or explain your wording. population facing stronger challenges to XYZ (urban heat for instance)such as elderly, or population known to have less XYZ such as people that are non-Dutch because it is not clear how migrant would be more vulnerable to urban climate. Also add references to consolidate your choice of metrics.
UrbanMaple
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Jun 25, 2026
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| - Average Distance to Green Spaces (in meters): This metric operationalises | ||
| physical accessibility to urban nature. Proximity to green | ||
| infrastructure is not merely a recreational luxury but a vital public | ||
| health requirement; greater pedestrian distances represent a | ||
| structural barrier to cooling zones, exacerbating the overall | ||
| vulnerability of the local population during extreme thermal events. |
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Is this distance Euclidian or isochrone ? Can you provide a further indication of what is considered a green space? Is there a minimum surface area or feature ?
UrbanMaple
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Jun 25, 2026
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| Because of the sparse data availability for Guangzhou, it is an | ||
| important step of the analysis to simplify the Spatial Justice Index (SJI) for | ||
| Rotterdam as well. The metrics for this index were limited to population | ||
| density, distance to green, percentage of inhabitants older than 65, and | ||
| percentage of inhabitants that are women. By simplifying the Rotterdam | ||
| SJI, results ended up being comparable to Guangzhou. |
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Back up your choice of metrics again here: why women ? Yous tate that by simplifying (how is that simplifying) the Rotterdam SJI, the results ended up being comparable to Guangzhou: How so ?
UrbanMaple
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Jun 25, 2026
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| # Discussion | ||
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| While this study successfully addresses the main research objectives, | ||
| several critical limitations highlight opportunities for methodological | ||
| improvement, largely stemming from discrepancies in data availability | ||
| and type. | ||
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| For the analysis of Rotterdam, the wide availability of | ||
| neighbourhood-level statistics enabled a rich, multidimensional analysis. | ||
| However, equivalent localized socio-economic and physical datasets were | ||
| unavailable for Guangzhou. This data asymmetry is a persistent hurdle in | ||
| transnational compartive urban research, where data collection standards | ||
| and public accessibility vary drastically by jurisdiction. To facilitate | ||
| more robust comparative frameworks in the future, establishing | ||
| standardized reporting metrics for urban demographic and environmental | ||
| datasets across global municipalities remains essential. | ||
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| Further more, the explanatory power of the spatial model could be | ||
| enhanced by integrating more detailed metrics regarding green | ||
| infrastructure quality (such as canopy density or biodiversity indices | ||
| rather than simple proximity) and its direct socio-political | ||
| implications. Incorporating advanced spatial network variables -such as | ||
| transit infrastructure connectivity and pedestrian walking barrier- | ||
| would also provide a more sophisticated understanding of how physical | ||
| networks shape environmental access. | ||
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| Finally, because official urban heat island (UHI) data was not available | ||
| for Guangzhou, the study relied on raw satellite remote sensing to | ||
| derive Land Surface Temperature. This approach introduces logistical | ||
| challenges, particularly in aligning cloud-free satellite overpasses to | ||
| capture comparable peak-summer thermal anomalies for both cities. | ||
| Methodologically, while LST acts as a valuable proxy for localized | ||
| surface heat accumulation, it does not perfectly mirror ambient air | ||
| temperatures or true human thermal comfort. Consequently, relying on | ||
| surface temperature slightly shifted the analytical focus away from the | ||
| atmospheric UHI effects originally intended for evaluation. | ||
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Here is a good place to indicate direction for future research. There are more points to raise than "the Chinese dataset is limited", think more critically about this section for future research, it is a nice way to end a paper. The limitation overall are well argued otherwise.
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| # AI Acknowledgement | ||
| AI tools were used to assist in refining the language and structure of this report. All the content was reviewed and verified afterwards. They were used as an assisting tool for writing code in, for us, new languages, such as R. | ||
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Removed a couple of unnecessary lines
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@Applied-Spatial-Analytics/groupb I recreated this feedback. All changes you have made and will make should appear here so we can comment on them. Please do not merge this PR!