Modeling Error in Overlaid Categorical Maps

在地理信息系统（GIS）中，对区域或多边形进行复盖是一个常见的基本过程。在叠加映射的基础上做出的决定或推断不会比包含在组件映射和通过组合和排列输入映射派生的映射上的信息更可靠或更有效。我们几乎没有统计技术来分析分类地图中固有的错误，更没有技术来提醒那些使用GIS地图的人注意他们所看到的图像中固有的错误。在开发处理连续分布的工具方面取得的进展与对分类图上显示的离散类别的理解并不匹配。克里斯曼教授的研究将加强地图误差理论，并产生新的统计程序来描述重叠分类地图上的误差。克里斯曼的工作将使地图附有可能出现的错误的信息成为可能。然后，用户将能够在基于叠加程序生成的地图的基础上，将这种不精确因素考虑到决策和推断中。作为开发这类指数过程的一部分，克里斯曼将探索一种新型空间统计的发展，其应用将超越分类地图。他的工作将是一个重要的一步，以发展一个普遍和普遍接受的模型误差在地图数据和地图显示。

Overlaying maps showing zones or polygons assigned to categorical classes is a frequent and basic process in geographical information systems (GIS). Decisions or inferences made on the basis of overlaid maps can be no more sound or valid than the information contained on component maps and on the maps that are derived by combining and permuting input maps. We possess few statistical techniques for analyzing the error inherent in categorical maps and even fewer techniques for alerting those who use GIS maps to the errors inherent in the images they see. The progress that has been made in developing tools for treating continuous distributions has not been matched with understandings of the discrete categories shown on categorical maps. Professor Chrisman's research will strengthen the theory of map error and generate new statistical procedures to describe error on overlaid categorical maps. Chrisman's work will make it possible for maps to be accompanied by information on probable error. Users will then be able to factor such imprecision into the decisions and inferences they make on the basis of maps produced by overlay procedures. As part of the process of developing such indices, Chrisman will explore the development of a new class of spatial statistics with applications beyond categorical maps. His work will be an important step toward development of a general and generally- accepted model of error in cartographic data and in cartographic display.