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As economic development continues to advance globally, countries are increasingly focused on the green transformation of their economies. This paper employs a data envelopment analysis (DEA) model and entropy weighting methodology to construct and assess an indicator system for economic green transformation, taking into account environmental pollution. The analysis is based on panel data from 215 prefecture-level cities in China between 2015 and 2019. The two-way fixed effects model and moderating effect model are employed to investigate the influence of land finance on economic green transformation and to ascertain the moderating effect mechanism of local government debt. The study's conclusions are as follows: (1) Land finance impedes the transition to a green economy. (2) Local government debt is a major factor that restricts the influence of land finance on the transition to a green economy; as local government debt levels rise, land finance's role in impeding the transition to a green economy rises, and a positive moderating effect occurs. (3) Depending on the urban geographic location, the size of the economy and other factors, the impact of local government debt and land finance on the economic green transition varies. This empirical study demonstrates that the more local government debt there is in an eastern region or city with a bigger economic output scale, the more of an inhibitory influence land finance has on the economic transition to a green economy. In light of this, the paper suggests that the land finance policy be updated at the appropriate time, that the land market be regulated, that the government's reliance on land finance be gradually decreased, that the nature and amount of public debt be actively optimised, that the industrial infrastructure be enhanced to facilitate the transition towards a more environmentally sustainable economy, and that other suggestions be made. [ABSTRACT FROM AUTHOR]