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高精度的土地覆盖数据是生态系统监测评估与区域可持续发展的重要研究基础，然而目前较少有研究对较高分辨率土地覆盖数据（10m）在城市尺度的区域上进行研究。随着国际湿地城市的建立，也需要高质量高精度的土地覆盖数据为相关研究提供信息。本文以中国首批国际湿地城市为研究区，对三套全球10m土地覆盖数据（Dynamic World、ESA WorldCover、Esri Land Cover）选择2020年和2021年进行空间一致性分析和精度评价，最后基于空间一致性分析结果和精度评价结果进行土地覆盖数据集融合以重建生产一套新数据，提出了基于空间一致性分析与精度评价的融合方法。结果表明：（1）任何两个数据集之间，水体、林地、耕地、建设用地这些类型一致度比较高，而湿地、草地和裸地混淆度比较高。（2）ESRI与DW的空间一致性程度最高，全部一致区域占比最高（60%以上），全部不一致区域占比最低（6%以下）且多分布在沿海沿江，湿地广布的区域，这些区域异质性强，土地覆盖类型复杂。（3）ESA的总体精度最高，DW和ESRI的总体精度较为接近；ESA的湿地类型的精度和分类细节程度相对较高，更适用于城市湿地相关研究。（4）基于空间一致性分析与精度评价的融合方法可以有效融合多源土地覆盖数据，提高具有广泛异质区域数据的精度；本文融合结果的总体精度（80%以上）和Kappa系数比三个原数据都要高，可以为国际湿地城市认证及相关研究提供数据支撑。
High-precision land cover data is an important research basis for ecosystem monitoring and assessment and regional sustainable development. However, there are few studies on high-resolution land cover data (10m) at the urban scale. With the establishment of wetland city, high-quality and high-precision land cover data are also needed to provide information for relevant research. Taking the first wetland cities in China as the study area, this study selected three sets of global 10m Land Cover data (Dynamic World, ESA WorldCover and Esri Land Cover) in 2020 and 2021 for spatial consistency evaluation and precision evaluation. Firstly, the consistency and confusion between each two sets of data were calculated using the spatial superposition method, and a spatial consistency distribution map was drawn to analyze the spatial consistency of the three sets of data. Then the confusion matrix was calculated by constructing verification sample points through visual interpretation to evaluate the accuracy of the three sets of data. Finally, based on the results of spatial consistency analysis and accuracy evaluation, land cover data sets were fused to produce a new set of data, and a fusion method based on spatial consistency analysis and accuracy evaluation was proposed. The results showed that: (1) Among any two data sets, the consistency of water, forest, cropland and urban area was high, while the confusion of wetland, grassland and bare was high. (2) The spatial consistency between ESRI and DW was the highest, with the highest proportion of all consistent areas (more than 60%) and the lowest proportion of all inconsistent areas (less than 6%), which were mainly distributed in areas along the coast and rivers and with extensive wetlands. These areas have strong heterogeneity and complex land cover types. (3) ESA had the highest overall accuracy, while DW and ESRI had similar overall accuracy. ESA wetland types have relatively high precision and classification details, which is more suitable for urban wetland related research. (4) Multi-source land cover data can be effectively integrated and the data accuracy of the widely heterogeneous regions can be improved by using the fusion method based on spatial consistency analysis and accuracy evaluation; The overall accuracy of fusion results (more than 80%) and Kappa coefficient were higher than the three original data. Therefore, the research results of this article can provide data support and auxiliary decision-making support for wetland city certification and related research.