Accessibility calculation data, along with pre- and post-carbon emission calculations and driving force analysis.

This study developed an "Entrance-to-Accessibility and Emission Reduction" (E2A) model, designed to assess how the land-saving strategy of increasing entrance density balances accessibility and traffic emission reduction. The E2A model first optimizes entrance locations, quantifies changes in accessibility and the resulting traffic emissions, and then uses interpretable machine learning methods to identify key morphological driving factors. The dataset includes the process and results of this study, specifically: 1. accessibility calculation data; 2. comparison of accessibility before and after the addition of new entrances; and 3. carbon emission calculations and driving force analysis data.