Aligning with UN Sustainable Development Goals (SDGs) 1 and 10, the ‘growth-poverty-inequality’ (GPI) nexus has become widely discussed in economic development research. It remains an important discourse regarding sustainable development. To monitor spatiotemporal economic development and analyse the GPI trilemma, especially in developing and undeveloped regions, a novel framework based on long-term, consistent night-time light (NTL) remote sensing (RS) data (2000–2020) was proposed and applied to the Nile River Basin. An optimized, multitemporal estimation strategy was developed for gross domestic product (GDP) estimation and spatialization. Then, the poverty map and inequality indices for the entire basin and each country were prepared. Combining GDP growth, the poverty map, inequality index, and other relevant economic statistics, the GPI nexus for the Nile River Basin was modelled. Findings suggest that the proposed framework can not only effectively map GPI dynamics but also accurately model the GPI nexus. We found that the economic development of countries in the Nile River Basin is characterised by widespread poverty and inequality and restricted spatial distribution. The spatiotemporal evolution patterns of GPI vary with upstream and downstream geographic locations. Regarding their interaction, study findings revealed that economic growth relieves poverty, whereas high inequality levels aggravate poverty. Moreover, high inequality dampens the positive effect of economic growth on poverty reduction. This study offers new insight into GPI trilemma modeling and analyses using NTL data, an economically viable alternative to mass field surveys that is especially relevant for developing and underdeveloped regions.

根据联合国可持续发展目标 (SDG) 1 和 10，“增长-贫困-不平等”(GPI) 关系已在经济发展研究中得到广泛讨论。它仍然是关于可持续发展的重要论述。为了监测时空经济发展和分析 GPI 三难困境，特别是在发展中和欠发达地区，提出并应用了一个基于长期、一致的夜间光 (NTL) 遥感 (RS) 数据 (2000-2020) 的新框架到尼罗河流域。为国内生产总值 (GDP) 估计和空间化开发了优化的多时间估计策略。然后，准备了整个流域和每个国家的贫困地图和不平等指数。结合 GDP 增长、贫困地图、不平等指数和其他相关经济统计数据，对尼罗河流域的 GPI 关系进行了建模。研究结果表明，所提出的框架不仅可以有效地映射 GPI 动态，还可以准确地模拟 GPI 关系。我们发现，尼罗河流域国家经济发展的特点是普遍存在贫困和不平等，空间分布受限。GPI的时空演化模式随上下游地理位置而变化。关于它们的相互作用，研究结果表明，经济增长减轻了贫困，而高度的不平等加剧了贫困。此外，高度不平等削弱了经济增长对减贫的积极影响。这项研究为使用 NTL 数据的 GPI 三难困境建模和分析提供了新的见解，