Abstract: Abstract: Land cover change is one of the most important data sources for global environmental issues, such as the impact assessment of human activities on ecosystems. Since a great number of land cover datasets have been produced at the global and national scale in recent years, it is necessary to scientifically evaluate the reliability of these datasets in specific areas and the consistency between multi-source datasets in the selection of products. There are great changes in land cover, leading to high demand for the land cover data in the Yangtze River Delta, which is one of the most active and open regions in economic development with the strongest innovation capabilities in China. Taking the Yangtze River Delta region as the study area, this study aims to assess the relative accuracy of six land cover datasets (CCI_LC, FROM-GLC, GLC_FCS30, GLCNMO, GlobeLand30, and CGLS_LC) using the accuracy validation and consistency analysis. Five ways were selected to verify the accuracy, including the confusion matrix, overall accuracy, Kappa coefficient, user and producer accuracy. The correlation of land cover types in the study area was analyzed to calculate the proportions of various types in land cover products and the correlation coefficients. Three 30m-resolution land cover products (FROM-GLC, GLC_FCS30, and GlobeLand30) were also compared via the consistency distribution of classification, overall consistency, quantity and allocation disagreement between them. The results show that the overall accuracy of six products in the Yangtze River Delta region were 76.89%, 78.42%, 84.67%, 74.26%, 80.61%, and 85.43%, respectively, indicating that all of land cover products behaved fine accuracies. The correlation coefficients of land cover types were greater than 0.9 in six products. The best correlation was achieved in the GlobeLand30 with the most reliable estimation on the area of land cover types. Three 30m-resolution land cover products had 65.51% similar classified pixels, while, the overall consistencies between the products were 72.23%, 77.99%, and 76.41%, respectively. A fine data support was obtained from three land cover products, although with a little pixel confusion. In addition, the greatest stability was achieved in GLC_FCS30 with high accuracy of land cover types, particularly on the second-level categories for a more detailed description of land cover. High accuracy of classification was obtained in six land cover products for the cropland, woodland, water body, and impervious areas that were widely distributed in most of the research area. Nevertheless, there was a low accuracy of classification for the wetland, bare land, shrub and grassland. There was less influence of topographical fluctuations on the accuracy of classification in topography and geomorphology. Specifically, only a few unstable topographical classifications occurred in the hilly areas of Zhejiang Province. Correspondingly, the economic level dominated the accuracy of classification in urban development. The land cover products also considered the needs of different users. The best performance of CGLS_LC was achieved in cropland, and the similar excellent performance of GLC_FCS30 and CGLS_LC was found in woodland and impervious areas, while FROM-GLC was the most suitable for the water body.