Modeling Error in Overlaid Categorical Maps

显示指定给分类的区域或面的叠加地图 类是地理信息处理中一个最基本、最频繁的过程 系统（GIS）。 在重叠的基础上作出的决定或推论 地图所包含的信息并不比 组件映射和通过组合和 置换输入映射。 我们掌握的统计技术很少， 分析分类地图中固有的错误，甚至更少 用于提醒使用GIS地图的人员注意固有错误的技术 在他们看到的图像中。 在发展中取得的进展 用于处理连续分布的工具尚未与 对分类地图上离散分类的理解。 克里斯曼教授的研究将加强地图理论 错误，并生成新的统计程序来描述 覆盖的分类地图。 克里斯曼的工作将使我们有可能 地图须附有关于可能出现的错误的资料。 用户将 然后能够将这种不精确因素纳入决策， 他们根据叠加产生的地图进行推断， 程序. 作为制订这种指数过程的一部分， 克里斯曼将探索一个新的空间类的发展 统计学与分类地图之外的应用。 他的工作将是 这是朝着全面发展的重要一步， 制图数据和制图误差的公认模式 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.