Dataset Associated with the Study of Robust Drivers of Urban Land Surface Temperature (ULST) Dynamics Across Diverse Landscape Characters

Some generic landscape drivers such as climate, parent material, topography, presence/proximity to urban thermal sinks were analysed as well as their impact on ULST. The study offers a novel perspective in understanding ULST dynamics, promoting interdisciplinary, participatory and democratic research approaches necessary for citizen and open science applications.

The dataset includes: 1) Atlas.ti Files - A collection of 1,508 codes generated using Atlas.ti, relevant extracts in .csv and .xlsx formats, and coded articles; 2) Python Scripts - for deduplication of literature data, and dummy regression analysis of the relationship between ULST and landscape character elements; 3) Tableau Resources - Dataset used to develop the interactive dashboards developed to summarize and communicate the findings of our research; and 4) Supplementary Files - Comprising of a composite of all initial articles considered in the study, the deduplicated article list, results of the final screened/reviewed articles and other data that were utilized in the study, e.g. coded data from Atlas.ti, data used in the dummy regression analysis, amongst others.