康熙《皇舆全览图》对长城的绘制及其空间精度量化分析

The Depiction of the Great Wall in Kangxi’s Atlas of the Chinese Empire and Its Quantitative Analysis of Spatial Accuracy

摘要: 康熙年间绘制的《皇舆全览图》是中国首部以经纬度标注的大比例尺全国地图，体现了18世纪初实测制图技术的高峰。本文以山海关至嘉峪关段明长城为研究对象，利用GIS技术比对168个历史—现代对应堡口点，采用空间误差、RMSE、自然分段与线形态分析方法，系统评估地图空间精度。结果表明，地图总体线形与现代长城高度吻合，但区域误差差异显著：京畿地区误差最小(平均4.65 km)，晋陕宁段与河西走廊误差偏大(最高达59.24 km)。RMSE分析表明，经度方向误差显著高于纬度，是主要误差来源。经度98˚E~100˚E与103˚E~104˚E两段出现误差突增，推测与三角测量链断裂或基线误差累积有关；中央经线116.38˚E附近误差显著降低，反映以北京中心的测量控制系统具有更高几何精度。同时，测量人员更替显著影响测图精度，测区变动后出现误差上升与“跳点”现象，疑因实测能力下降或依赖旧图所致。地方协作程度差异也导致测绘方法与数据精度呈现区域分异。

Abstract: The Atlas of the Chinese Empire, compiled during the Kangxi reign, represents China’s first large-scale national map annotated with longitude and latitude, marking the pinnacle of early 18th-century empirical cartography. This study focuses on the Ming Great Wall section from Shanhaiguan to Jiayuguan, employing GIS technology to systematically evaluate its spatial accuracy through comparative analysis of 168 historical-modern corresponding fort points. Analytical methods include spatial error distribution, RMSE (Root Mean Square Error), natural breaks classification, and linear morphology analysis. The results demonstrate that the map’s overall linear morphology aligns closely with the modern Great Wall, yet regional accuracy varies significantly: the capital region exhibits minimal displacement (mean error: 4.65 km), while Shanxi-Shaanxi-Ningxia segments and the Hexi Corridor show larger deviations (maximum: 59.24 km). RMSE analysis reveals that longitudinal errors substantially exceed latitudinal errors, constituting the primary error source. Two abrupt error surges occur at 98˚E~100˚E and 103˚E~104˚E, likely attributable to disrupted triangulation chains or accumulated baseline errors. Notably, precision improves markedly near the central meridian (116.38˚E), reflecting higher geometric accuracy in the Beijing-centered control network. Personnel changes during surveys significantly impacted outcomes, as evidenced by post-rotation error increases and “jump point” anomalies, suggesting compromised field measurement capabilities or reliance on outdated data. Furthermore, regional disparities in local cooperation led to methodological variations and corresponding accuracy differentiation.