In concert with the rapid process of urbanization, both the spatial extent and intensity of the urban heat island (UHI) effect have been continuously increasing in China. The transformation of landscape patterns is considered to be a direct factor influencing UHI. However, the contributions of various landscape metrics to UHI still require further clarification. City size, landscape composition, and spatial configuration are the three main indicators of landscape patterns. The influences of these three indicators on UHI show a progressive relationship, both from integrity to locality, and from amount to spatiality. Thus, the relationship between landscape patterns and UHI has been divided into three hierarchical aspects. Firstly, the correlations between city size and UHI are typically influenced by the climate. The influence of climatic zonation on the relationship between city size and UHI should be further explored. Secondly, the significant correlations between several landscape composition factors and UHI have been revealed to be under the conditional control of season and day-night cycle. To date, urbanization effects, such as socio-economic influence on UHI, have not received enough attentions. Thirdly, the contributions of spatial configuration factors to UHI are obscure. The key spatial configuration factors significantly influencing UHI and their implications for urban planning and management should be investigated more thoroughly. It is deduced that a tipping point may exist in the nonlinear correlation between landscape patterns and UHI, which corresponds to the inconsistent driving mechanism on both sides of the tipping point. By combining the application of remote sensing, geographical information system, and field observations, the thresholds of landscape pattern contributions could be indicated from the identified tipping points. Specifically, by comparing the spatiotemporal characteristics of the relationship between city size and UHI in different climatic zones, revealing the urbanization effect on the correlations between landscape composition and UHI, and determining the contributions of spatial configuration on UHI while controlling specific factors, the thresholds could be comprehensively identified. The findings will provide insights into three key landscape approaches to relieving UHI.