由美国国防气象卫星搭载的可见光成像线性扫描业务系统（DMSP/OLS）和国家极轨卫星搭载的可见光近红外成像辐射仪（NPP/VIIRS）获取的夜间灯光影像是监测人类社会经济活动和自然现象（如林火、油气燃烧等）的主要数据源。然而，现有的夜间灯光数据存在缺乏星上的辐射定标、像元饱和、时间尺度不连续、多源夜间灯光影像辐射不一致等问题。基于此，本文以中巴经济走廊区域为研究区，提出了一种基于线性拟合提取不变目标区域的方法，实现了DMSP/OLS影像间、DMSP/OLS与NPP/VIIRS两种数据间的相互校正。然后对中巴经济走廊的校正结果在不同空间尺度上选用区域灰度总量、标准化差异指数以及标准化差异指数和作为评价指标进行检验。结果表明:两种校正模型的拟合优度均在0.78以上，校正后的DMSP/OLS影像灰度总量与GDP和人口数据的相关性显著提高(GDP: R ²=0.7689;人口: R ²=0.9033)，且标准化差异指数明显降低；NPP/VIIRS影像经过与DMSP/OLS互校正后在辐射亮度、时空分布上与DMSP/OLS更加一致，空间细节信息更加突出，从而增强了多源夜间灯光影像的一致性，更加适合用于长时间序列社会经济要素发展趋势的分析。

The night light images obtained by the visible light imaging linear scanning business system (e.g., DMSP/OLS) and the visible light near infrared imaging radiometer (e.g., NPP/VIIRS) carried by the national polar orbit satellite are the main data sources for monitoring the social and economic activities and natural phenomena (e.g., forest fire, oil, and gas combustion). However, the existing nighttime lighting data lack the radiation of calibration, the pixel saturation, the discontinuous time scale, and the inconsistency of the multisource night light radiance. Thus, this work proposes a method of extracting invariant target area based on linear fitting and performs the mutual correction between two kinds of data between DMSP/OLS and NPP/VIIRS images by taking the Kashi of China and Pakistan Economic Corridor as the research area. Subsequently, the correction results of the economic corridor of China and Pakistan are tested on different spatial scales, including the total amount of regional gray scale, the standard difference index, and the total of standardized difference index. Results show that the goodness of fit of two calibration models is above 0.78. The correlation between the total gray level of the corrected DMSP/OLS image and the GDP and population data significantly increased (GDP: R ²=0.7689; population: R ²=0.9033), and the standard difference index significantly decreased after being calibrated. The calibrated NPP/VIIRS images are more consistent with DMSP/OLS in temporal and spatial distribution, and the spatial details are more prominent. This phenomenon enhances the consistency of multisource nighttime light images and is more suitable for the analysis of long-term development trends in socio-economic factors.