This dataset is associated with the study of the robust drivers of urban land surface temperature (ULST) dynamics across diverse landscape characters based on an augmented systematic literature review of 101 peer-reviewed articles. 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.

Atlas.ti, 23

Tableau Desktop, 2023

Visual Studio Code, 1.86

FAST, 2

Microsoft Office Suite, 2021