## 1 Introduction  
Land use/land cover change (LUCC) is closely related to climate change, terrestrial ecosystem, geophysical and chemical cycles, human life, _etc._[1; 2; 3; 4; 5; 6]. Nevertheless, it has always been a difficult problem to derive such a parameter, especially at national, continental and even global scales, since the emergence of remote sensing. Remote sensing technology has the ability to produce land cover products at different spatial resolutions, especially at a global scale. Global land cover (GLC) mapping has been given much attention by the international scientific community since the 1990s. Consequently, some scholars have paid more attention to assessing and validating the consistency, accuracy and suitability among different GLC products [7; 8; 9; 10; 11; 12]. Meanwhile, GLC products have been distributed to the scientific community, non-governmental organizations, individuals and governments. Therefore, it is of great significance to evaluate and validate the quality and consistency of these GLC products [13]. At present, several GLC products have been produced, including the International Geosphere-Biosphere Programme Data and Information System (IGBP-DIS) DISCover of the US Geological Survey [14], University of Maryland Land Cover Product (UMD LC) [15], CORINE of the European Commission [16; 17], Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5.1 Land Cover Type (thereafter referred to as MCD12Q1) of Boston University [18], GLC2000 of the European Commission's Joint Research Centre [19], GlobCover of the European Space Agency [20, 21], ECOCLIMAP of the French Meteorological Research Center [22] and GlobeLand30 dataset of China National Basic Geographic Information Center [23]. However, most of the developed GLC data have coarse resolutions, ranging from 300 m to 1 km, and users generally consider it far from satisfactory due to the lack of spatial details, low classification accuracy, and inconsistency with different products. In 2010, China launched a GLC mapping project, and finally produced a 30 m GLC data product (GlobeLand30) with 10 classes for years 2000 and 2010, within a four-year period. As shown in Table 1, in comparison to other GLC products, the MODIS MCD12Q1 has an annual updating cycle that has been updated to be more timely. Therefore, this product has an immeasurable significance in Earth surface research and has been widely used for different applications [24; 25; 26; 27; 28]. The MCD12Q1 contains five data layers, corresponding to five different classification schemes with the spatial resolution of 500 m. Consistency analysis of MCD12Q1 has been performed in some studies [29; 30; 31; 32]. Nevertheless, finer resolution GLC products have never been used to evaluate the product. In this study, the GlobeLand30 and MCD12Q1 are compared by analyzing the consistency of MCD12Q1 in Anhui Province, China by normalizing the land cover classification types between two products based on the knowledge rule (KR) and the C4.5 decision tree (DT) classification algorithm. In addition, the whole study area is divided into three sub-regions that have different dominant land cover types. Four evaluation indicators of area consistency, spatial consistency, classification accuracy, and landscape diversity indices are selected to evaluate the consistency of five land cover classification schemes of MCD12Q1 in the three sub-regions. The novelty of this study is depicted as the following:  
(1) The harmonization of land cover classification between both the GLC products is performed based on the KR and C4.5 DT classification algorithm. A total of five land cover types are categorized from the two datasets to evaluate the consistency of five classification schemes of MCD12Q1, specifically including \"woodland\", \"grassland\", \"cropland\", \"wetland\" and \"artificial surfaces\". (2) Three sub-regions of the study area with different spatial heterogeneities are used to evaluate the consistency of five classification schemes of MCD12Q1 at a regional scale.