A long-term monthly assessment of land surface temperature and normalized difference vegetation index using Landsat data

Abstract The present study assesses the monthly variation of land surface temperature (LST) and the relationship between LST and normalized difference vegetation index (NDVI) in Raipur City of India using one hundred and eighteen Landsat images from 1988 to 2019. The results show that a monthly variation is observed in the mean LST. The highest mean LST is found in April (38.79oC), followed by May (36.64oC), June (34.56oC), and March (32.11oC).The lowest mean LST is observed in January (23.01oC), followed by December (23.76oC), and November (25.83oC). A moderate range of mean LST is noticed in September (27.18oC), October (27.22oC), and February (27.88oC). Pearson's linear correlation method is used to correlate LST with NDVI. The LST-NDVI correlation is strong negative in October (-0.62), September (-0.55), and April (-0.51). The moderate negative correlation is developed in March (-0.40), May (-0.44), June (-0.47), and November (-0.39). A weak negative correlation is observed in December (-0.21), January (-0.24), and February (-0.29). The change in weather elements and variation in land surface characteristics contribute to the monthly fluctuation of mean LST and LST-NDVI correlation. The study will be an effective one for the town and country planners for their future estimation of land conversion.

摘要 本研究基于1988年至2019年间的118景陆地卫星（Landsat）影像，针对印度赖布尔市的地表温度（Land Surface Temperature，LST）月际变化特征，以及地表温度与归一化植被指数（Normalized Difference Vegetation Index，NDVI）之间的关联展开评估。研究结果表明，平均地表温度存在明显月际波动：最高平均地表温度出现在4月（38.79℃），依次为5月（36.64℃）、6月（34.56℃）与3月（32.11℃）；最低平均地表温度出现在1月（23.01℃），随后是12月（23.76℃）与11月（25.83℃）；9月（27.18℃）、10月（27.22℃）与2月（27.88℃）的平均地表温度处于中等区间。本研究采用皮尔逊线性相关分析法探究地表温度与归一化植被指数的相关性：10月（-0.62）、9月（-0.55）与4月（-0.51）的地表温度与归一化植被指数呈强负相关；3月（-0.40）、5月（-0.44）、6月（-0.47）与11月（-0.39）呈中等程度负相关；12月（-0.21）、1月（-0.24）与2月（-0.29）则呈弱负相关。气象要素变化与地表特征差异是造成平均地表温度月际波动，以及地表温度与归一化植被指数相关性变化的主要成因。本研究可为城乡规划人员开展未来土地转化评估提供有效参考依据。