Indirect Assessment of Watershed SDG7 Development Process Using Nighttime Light Data—An Example of the Aral Sea Watershed

The accurate calculation of sustainable development indicators is essential for the assessment Sustainable Development Goals. This study develops a methodology that combines nighttime light indices, population distribution data, and statistics in order to examine changes key drivers SDG7 Aral Sea Basin from 2000–2020. In this study, best-performing combination four indices five simulation methods (two linear regression three machine learning methods) was selected simulate spatial GDP Basin. results showed that: (1) prediction using XGBoost model with TNL had better performance than other models. (2) From 2000 2020, shows an uneven pattern while growing rapidly (+101.73 billion, +585.5%), lower Amu Darya River gradually concentrating middle Syr basins, respectively. At same time, strong negative correlation area water bodies. (3) Although there small increase score (+6.57) ranking (+9) it difficult achieve 2030. Deepening inter-basin energy cooperation, enhancing investment renewable energy, increasing intensity achieving SDG7.