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 本研究利用1988至2019年的118景陆地卫星（Landsat）影像，评估了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差分植被指数（Normalized Difference Vegetation Index, NDVI）之间的关联。研究结果显示，平均LST存在显著月际波动：最高平均LST出现在4月（38.79℃），其次为5月（36.64℃）、6月（34.56℃）与3月（32.11℃）；最低平均LST观测于1月（23.01℃），紧随其后的是12月（23.76℃）与11月（25.83℃）；9月（27.18℃）、10月（27.22℃）及2月（27.88℃）的平均LST处于中等区间。本研究采用皮尔逊线性相关分析法探究LST与NDVI的相关性，结果表明：10月（-0.62）、9月（-0.55）与4月（-0.51）的LST-NDVI相关性呈强负相关；3月（-0.40）、5月（-0.44）、6月（-0.47）与11月（-0.39）呈现中等强度负相关；12月（-0.21）、1月（-0.24）与2月（-0.29）则表现为弱负相关。气象要素变化与地表特征差异是造成平均LST月际波动及LST-NDVI相关性变化的核心原因。本研究可为城乡规划者开展未来土地转换评估提供有效参考依据。