Abstract: Land Use and Land Cover (LULC) is the direct result and concentrated reflection of the interaction between human activities and natural geographical environment, which affects global climate change, material cycle and dynamic balance of water and heat. High-precision LULC information is critical to address current environmental challenges. With the rapid increase in remote sensing observation platforms, the free disclosure of high-resolution satellite remote sensing data and the advancement of LULC mapping technology, freely available medium and high-resolution land cover products are booming, and more and more open source medium and high resolution LULC datasets have been constructed worldwide. However, there are different degrees of uncertainty in multi-source data. How to select suitable land cover products at the regional scale has become a difficult problem in various fields. Therefore, it is very important to evaluate the accuracy of the current commonly used land cover data at the regional scale. This study focuses on the Erhai Lake Basin, utilizing the Third National Land Survey data alongside kilometer grid sampling, field surveys, and high-resolution image interpretation to collect 2,947 validation samples. We evaluated seven commonly used heterogeneous LULC data products in terms of area, spatial consistency, confusion levels, and accuracy, The influence of LULC product mapping accuracy was quantitatively analyzed from four aspects: shrub forest proportion, landscape pattern index, elevation standard deviation and average patch area, and the advantages, disadvantages and applicability of each dataset were discussed. The findings reveal that among the eight land cover datasets, high consistency areas, moderate consistency areas, and low consistency areas represent 64.13%, 34.00%, and 1.87% of the Erhai Lake Basin's total area, respectively. Notable confusion and misclassification occurred in shrub land and grassland, highlighting significant differences in the ability of various products to represent different regions and land cover types. The overall accuracy of the LULC products ranges from 69.5% to 81.1%. Notably, ESA_WC stands out as offering the best data quality and spatial detail, especially for identifying cultivated land in fragmented landscapes. Additionally, the Shannon Diversity Index (SHDI) was found to have the most considerable impact on spatial consistency of land cover in the Erhai Basin, followed by the proportion of shrub land. In contrast, factors such as elevation standard deviation, patch size, and cloud cover frequency had a lesser effect. For studies of all land cover features in the Erhai Basin, 10 m resolution data should prioritize the highest overall accuracy provided by ESA_WC, CRLC data is a better choice if shrubland and grassland are not subdivided. While for 30 m resolution data, CLCD demonstrates relatively high accuracy, it significantly underestimates impermeable surface area compared to other products, making it unsuitable for urban expansion research. This study serves as a valuable reference for assessing the classification accuracy and strengths and weaknesses of the seven LULC products, facilitating targeted data selection for specific applications. The research results can directly evaluate the accuracy of LULC products, provide effective suggestions for the applicability and adaptation of these data in plateau mountainous areas, and provide scientific basis for ecological environment protection, rational utilization of resources and sustainable development in plateau mountainous areas.