The current work attempts to understand the spatiotemporal patterns of the urban heat phenomenon (UHP) and its relationship with the transformation of land-use/land-cover in Chandannagar city of India in four different phases, e.g., in pre-monsoon and post-monsoon of 1988 and 2020 based on Landsat satellite data. To investigate the city’s thermal and environmental conditions in a better way, UHP and non-UHP areas are identified separately. Moreover, multiple linear regression (MLR) and simple linear regression (SLR) models are used to envisage the predictability of land surface temperature (LST) by various remote sensing indices and UHP by built-up areas. The results assert that mean LST in both pre-monsoon and post-monsoon from 1988 to 2020 has increased at the rate of 0.11°C and 0.1°C each year, respectively. Built-up areas, UHP areas and mean LST linearly increase in those directions from the city centre where vegetation cover and non-UHP areas decrease rapidly. Moreover, growth of multiple UHP areas, the highest increase in UHP intensity and good applicability of MLR and SLR models are observed in pre-monsoon than post-monsoon. Therefore the information regarding urban thermal environments is expected to be very useful for policymakers and urban planners in adopting suitable mitigation measures against unplanned urbanisation leading to UHP effects.

目前的工作试图了解城市热现象 (UHP) 的时空模式及其与印度钱丹纳加尔市土地利用/土地覆盖转变的四个不同阶段的关系，例如季风前和季风后基于 Landsat 卫星数据的 1988 年和 2020 年季风。为了更好地调查城市的热力和环境状况，分别确定了 UHP 和非 UHP 区域。此外，多元线性回归 (MLR) 和简单线性回归 (SLR) 模型用于设想各种遥感指数对地表温度 (LST) 的可预测性和建成区的 UHP。结果断言，从 1988 年到 2020 年，季风前和季风后的平均地表温度分别以每年 0.11°C 和 0.1°C 的速度增加。建成区，UHP 区域和平均 LST 从市中心方向线性增加，植被覆盖和非 UHP 区域迅速减少。此外，多个超高压区域的增长、超高压强度的最高增加以及 MLR 和 SLR 模型的良好适用性在季风前比季风后观察到。因此，有关城市热环境的信息有望对政策制定者和城市规划者采取适当的缓解措施以应对导致超高压效应的无计划城市化非常有用。