###### Abstract  
Land use/land cover (LULC) has an important impact on the ecological environment and is crucial for calculating ecosystem service values (ESVs). However, whether and to what extent the EVs vary when calculated by LULC product data at different spatial scales remain unclear. Data from two LULC products were used in this study, and two datasets with different spatial scales were obtained by resampling. Then, the ESVs were calculated by the equivalent factor method. Finally, the impacts of LULC on ESVs at different scales were studied, revealing the following: (1) The ESVs calculated by LULC products and by the same products at different scales are different. (2) The difference in the ESVs calculated by the two LULC datasets is approximately 28%, and the difference tends to decrease with increasing scale. (3) With an increase in the LULC scale, the overall change trend of ESVs also increases, and the increasing trend gradually moderates. In addition, the ESVs and LULC scale conform to a logarithmic relationship, and the coefficient of determination (R\({}^{2}\)) is greater than 0.7. These results have important reference value for obtaining reliable ESVs. ecosystem service values; scale effects; LULC; equivalent factor; resampling +
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technology, increasing amounts of remote sensing data have been applied to the study of ecosystems [7; 8; 9; 10; 11]. Changes in land use/land cover (LULC) have considerable effects on the energy budget of the Earth and the biogeochemical cycle, thereby affecting surface properties and ecosystem services [12; 13]. A variety of studies on biodiversity [14], the soil carbon cycle [15], water regulation [16], soil regulation [17], atmospheric regulation [18], carbon sequestration [19] and entertainment services [20] have reported relationships between LULC and ecosystem service values (ESVs). Furthermore, research has verified that the variations in LULC can be regarded as a proxy for ecosystems, and LULC variations can be used to calculate the trends of EVs and ascertain the safety of ecosystems. Consequently, LULC datasets have been used to calculate the ESVs of different regions. ESVs calculations, which have been deemed the fundamental basis for ecological asset accounting since 1997, facilitate the spatial recognition of ecosystems and manage their sustainability [21]. Currently, two major methods are employed to calculate ESVs: the functional value evaluation method and the equivalent factor method [22]. The functional value evaluation method is based on a series of ecological functions used to evaluate several key service functions and is very complicated [23]. Therefore, this method is more suitable for use at small scales [24]. However, this method is tremendously expensive, and researchers usually lack the background of the research region needed to customize the parameters for these functions, resulting in considerable uncertainty [25]. In contrast, the equivalent factor method establishes the relationships between agricultural products and EVs based on benefit transfer theory and takes LULC as a quantifiable proxy to indirectly obtain ESVs [26; 27]. This method was first proposed by [PERSON], et al. [28] for the global scale and was later regarded as unsuitable in China. More recently, [PERSON], et al. [29] proposed an equivalent factor method for calculating EVs in China based on surveys that places ecosystem and service functions into categories based on LULC datasets. The values of crops per unit area (1 \(\mathrm{hm}^{2}\)) of farmland in China were used as references to obtain the equivalent values based on the meta-analysis method. This method has been proven to be suitable in China [30]. Since the equivalent factor method has been shown to be more capable of calculating ESVs at large scales than the functional value evaluation method, this technique has been applied in many studies, for example, at the global scales [28] and in South Africa [31], Nigeria [32], Ethiopia [33] and the Qinghai-Tibet Plateau (QTP) in China [34].