Assessment of positional accuracy in spatial data using techniques of spatial statistics: proposal of a method and an example using the Brazilian standard

This paper presents the importance of simple spatial statistics techniques applied in positional quality control of spatial data. To this end, Analysis methods of point data spatial distribution pattern are presented, as well as bias analysis in the positional discrepancies samples. To evaluate the points spatial distribution Nearest Neighbor and Ripley's K function methods were used. As for bias analysis, the average directional vectors of discrepancies and the circular variance were used. A methodology for positional quality control of spatial data is proposed, in which includes sampling planning and its spatial distribution pattern evaluation, analyzing the data normality through the application of bias tests, and positional accuracy classification according to a standard. For the practical experiment, an orthoimage generated from a PRISM scene of the ALOS satellite was evaluated. Results showed that the orthoimage is accurate on a scale of 1:25,000, being classified as Class A according to the Brazilian standard positional accuracy, not showing bias at the coordinates. The main contribution of this work is the incorporation of spatial statistics techniques in cartographic quality control.本文阐述了简易空间统计技术在空间数据位置质量管控中的应用价值。为此，本文介绍了点数据空间分布格局的分析方法，以及针对位置偏差样本的偏差分析方法。为评估点要素的空间分布特征，本文采用了最近邻分析（Nearest Neighbor）与里普利K函数（Ripley's K function）两种方法。在偏差分析方面，本文采用了偏差平均方向向量与圆形方差作为分析指标。本文提出了一套空间数据位置质量管控方法，该方法涵盖采样规划及其空间分布格局评估、通过偏差检验开展数据正态性分析，以及依据标准进行位置精度分级。本次实证实验以ALOS卫星PRISM场景生成的正射影像为评估对象。实验结果表明，该正射影像在1:25000比例尺下精度达标，依据巴西位置精度标准被划分为A级，且坐标不存在偏差。本研究的主要贡献在于将空间统计技术纳入地图制图质量管控体系。