Abstract The urban landscape is considered the most complex and heterogeneous landscape among the different land surface features. It rises the land surface temperature (LST) to a large extent compared to the surrounding rural body. This investigation deals with the seasonal variability between LST and normalized difference water index (NDWI) on the different land surfaces in Raipur, India by using sixty-four Landsat images from 1991–92 to 2018–19. The results show that the post-monsoon season indicates the best correlation (0.42) between LST and NDWI, followed by the monsoon (0.34), pre-monsoon (0.25) and winter (0.04). The water bodies reflect a moderate negative correlation of LST-NDWI in all the four seasons (−0.49 in pre-monsoon, −0.33 in monsoon, −0.31 in post-monsoon and −0.45 in winter). On green vegetation, this LST-NDWI correlation is strongly positive in pre-monsoon (0.67) season, moderate positive in monsoon (0.43) and post-monsoon (0.50) seasons, and weak negative in winter (0.25) season. The built-up area and bare lands build a weak positive correlation of LST-NDWI in all the four seasons (0.24 in pre-monsoon, 0.21 in monsoon, 0.27 in post-monsoon and 0.15 in winter). This study can be beneficial for land use planning and management of any city under a similar physical environment.

中文翻译：

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利用 Landsat 卫星数据研究城市环境中 LST 和 NDWI 之间的季节性变化

摘要 城市景观被认为是不同地表特征中最复杂、最异质的景观。与周围的农村体相比，它在很大程度上升高了地表温度（LST）。本调查使用 1991-92 年至 2018-19 年间的 64 幅 Landsat 影像，处理了印度赖布尔不同地表的 LST 和归一化差异水指数 (NDWI) 之间的季节性变化。结果表明，季风后季节表明 LST 和 NDWI 之间的相关性最好（0.42），其次是季风（0.34）、季风前（0.25）和冬季（0.04）。四个季节的水体都反映了LST-NDWI的中度负相关（季风前-0.49，季风-0.33，季风后-0.31和冬季-0.45）。在绿色植被上，这种 LST-NDWI 相关性在季风前 (0.67) 季节呈强正相关，在季风 (0.43) 和季风后 (0.50) 季节呈中度正相关，而在冬季 (0.25) 季节呈弱负相关。建成区和裸地在四个季节都建立了弱的LST-NDWI正相关（季风前为0.24，季风为0.21，季风后为0.27，冬季为0.15）。这项研究对任何城市在类似物理环境下的土地利用规划和管理都有好处。