## 5 Conclusions and Recommendations  
This study mapped LCZ and used remotely sensed land surface properties to determine the major drivers of LST variations between and within LCZ in Harare. The study established that the RF algorithm is effective for LCZ classification, as it mapped a complex city with high accuracy. LST varied between LCZs with increased warming as a consequence of the decrease in vegetation proportion, decrease in surface wetness, and increase in built-up extent. The densely built-up LCZ and LCZ3 were the warmest, while dense forest and water LCZs were the coolest due to cooling by latent heat transfer. Therefore, urbanization extent, surface wetness and distribution, and health of vegetation were the major determinants of variations in LST between LCZs. Intra-LCZ analysis showed that factors such as increased bareness and elevation made low but significant contributions to LST spatial structure. The effect of these contributing factors was not uniform in strength and direction (warming or cooling) in affecting LST across all LCZs. In the densely built-up LCZ and LCZ3, the increase in wetness, bareness, and vegetation density led to a reduction in LST, while changes in terms of built-up extent had no effect, given that the area is almost homogenous and densely built. In other built up LCZs, the increase in built-up extent and urbanization extent were the major causes of warming, while vegetation and surface wetness caused significant cooling. The expansion of buildings into dense vegetation areas caused the most warming than any other transitions in the city. Based on the Contribution Index, we concluded that the heat mitigation value of vegetation and water areas in a city is reduced by their relatively small and diminishing coverage compared to surfaces with warming effects. Additionally, a conclusion was drawn that a reduction in the health of vegetation in areas, as well as the quality of water, reduces their heat mitigation value. The influence of surface characteristics on LST varied at the inter-LCZ scale compared to patterns observed at the intra-LCZ scale. Based on these findings, this study recommends that surface heat mitigation approaches must differ from one LCZ to another, with a consideration of how LSTs respond to surface characteristics. Future studies should consider high resolution datasets (>10 m) to understand the effect of elevation and aspect, as 30 m resolution may be insufficient for this highly dynamic aspect. Conceptualization, T.D.M., O.M. and J.O. ; methodology, T.D.M. ; software, T.D.M. ; validation, T.D.M., O.M. and J.O. ; formal analysis, T.D.M. ; investigation, T.D.M., O.M. and J.O. ; resources, T.D.M., O.M. and J.O. ; data curation, T.D.M., O.M. and J.O. ; writing--original draft preparation, T.D.M. ; writing--review and editing, T.D.M., O.M. and J.O. ; visualization, T.D.M. ; supervision, O.M. and J.O. ; project administration, O.M. and J.O. ; funding acquisition, T.D.M., O.M. and J.O. All authors have read and agreed to the published version of the manuscript. **Funding:** We acknowledge the National Research Foundation (NRF) of South Africa and the Germany DAAD climapAfrica for funding the research. This work was funded by the National Research Foundation of South Africa (NRF) Research Chair in Land Use Planning and Management (Grant Number: 84157). The research of this article was supported by DAAD within the framework of the climapAfrica programme with funds of the Federal Ministry of Education and Research. The publisher is fully responsible for the content. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** Remotely sensed data used in this study can be freely downloaded from United States Geological Survey (USGS) Earth Explorer website (www.earthexplorer.usgs.gov (accessed on 14 September 2022)).