The deteriorating ecological conditions have attracted widespread attention, spurring the development of quantitative analysis methods for ecological quality, improving the concept of ecological quality, and thus facilitating the formulation of future ecological environmental protection policies. Using satellite remote sensing and ecosystem process model data, we constructed a conceptual framework for ecological quality based on a pixel-level historical baseline of current ecosystem functions and biodiversity habitats through data quality control in forward normalization, correlation analysis, and projection pursuit algorithm based on particle swarm optimization, resulting in dataset of ecological quality indexes of terrestrial ecosystems in China from 2000 to 2018 with a spatial resolution of 1 km. By sharing this dataset, we aim to provide a data foundation for the advancement of ecological assessment theories and methods, as well as the management and decision-making of macro ecosystems.