<p>The study examines environmentally friendly strategie’s spatial patterns and influences on rural industrial green digital poverty alleviation from 2014 to 2022. The study uses spatial econometric models to investigate the effects of patterns of land use, pollution levels, the uptake of eco-friendly technology, and access to digital technologies on reducing poverty in rural areas. The dataset combines characteristics related to poverty alleviation, such as average income levels and access to essential services, with measurements of land use, pollution levels, eco-technology adoption rates, rural industrial output/growth rates, and access to digital technologies. Spatial autocorrelation was assessed using the global Moran index, and the findings show significant spatial clustering in areas with comparable ecological strategies as a result of the findings, which demonstrated the existence of spatial autocorrelation, spatial lag, or spatial error factors had to be included in the models. The results show that adopting eco-friendly technology and the availability of digital technologies benefit poverty reduction, whereas higher pollution levels have a negative impact. The study also discovered spatial spillover effects, which indicate that changes in one location can significantly impact. The study makes essential policy recommendations, such as promoting environmentally friendly technologies, improving digital infrastructure, enforcing environmental regulations, and targeting interventions considering spatial factors. The study is constrained by factors like possible biases in the data sources, built-in restrictions in the spatial econometric models, and limitations on generalizability.</p>