针对目前精度评价尺度单一的问题，提出基于直方变差图的多尺度精度评价方法，分别在像元尺度和亚像元尺度进行土地覆盖数据集精度评价。在像元尺度利用驻点作为采样工具直接评价数据集精度；亚像元尺度上，则利用非严格定义的驻点和驻点直方变差图对不同面积和空间结构的优势类进行精度评价。并以浙江北部典型区域为实验区，Landsat TM/ETM+为参考数据，对UMD、IGBP DISCover、MOD12Q1-2001、GLC2000、GlobCover2009等5种大尺度土地覆盖数据集进行多尺度精度评价实验。结果表明，多尺度精度评价方法能够全面地评价土地覆盖数据集的精度，提供更加丰富的多尺度精度信息。像元尺度精度评价可在一定程度上消除由于参考数据与数据集间的空间匹配造成的误差，评价结果更加客观；亚像元尺度精度评价能有效反映亚像元尺度优势地物面积及空间结构与精度的关系。

Due to the shortage of single-scale accuracy assessment methods, this paper proposes a multi-scale accuracy assessment method based on histo-variograms, which assesses the accuracy of land cover datasets on a pixel and sub-pixel scale. On a pixel scale, a standing-pixel is introduced as the sample tool to accurately assess datasets directly, whereas on a sub-pixel scale, a non-strictly defined standing-pixel and histo-variogram are applied to evaluate the accuracy of the dominant type in a mixed pixel with different areas and spatial structures. Taking as the experimental area a typical region in northern Zhejiang Province, China, and Landsat TM/ETM+ images as the reference data, accuracy assessment experiments of five large-scale land cover datasets, i. e., UMD, IGBP DISCover, MOD12Q1-2001, GLC2000 and GlobCover2009 are carried out. The result shows that the proposed multi-scale accuracy assessment method can provide a comprehensive evaluation of datasets along with abundant multi-scale accuracy information. The accuracy assessment on a pixel scale can eliminate the error caused by spatial disagreement between reference data and datasets, making the result more objective, while the accuracy assessment on a sub-pixel scale can effectively reflect the relationship between the accuracy and feature attributes, which refers to the feature's spatial structure and area.