Abstract: Aspects described herein provide a computer-implemented method and system for grouping topographic data based on the context of said data without the operator needing to make any assumptions. For each vector feature, its context, that is, information about the adjacent features, is incorporated in to the associated attribution data. In doing this, the system is able to characterise all of the vector features in a geographical area based on its context, from which patterns emerge. These patterns indicate features that have similar contexts, enabling the system to group the vector features according to their contexts based on their characteristics and attributes. Conversely, features that are anomalous within the region, that is, they do not fit the pattern of the surrounding features, are also identified. This is particularly important for identifying and resolving errors in the underlying topographic data.

Abstract: Aspects described herein provide a computer-implemented method and system for grouping topographic data based on the context of said data without the operator needing to make any assumptions. For each vector feature, its context, that is, information about the adjacent features, is incorporated in to the associated attribution data. In doing this, the system is able to characterise all of the vector features in a geographical area based on its context, from which patterns emerge. These patterns indicate features that have similar contexts, enabling the system to group the vector features according to their contexts based on their characteristics and attributes. Conversely, features that are anomalous within the region, that is, they do not fit the pattern of the surrounding features, are also identified. This is particularly important for identifying and resolving errors in the underlying topographic data.

Abstract: Aspects described herein provide a computer-implemented method and system for grouping topographic data based on the context of said data without the operator needing to make any assumptions. For each vector feature, its context, that is, information about the adjacent features, is incorporated in to the associated attribution data. In doing this, the system is able to characterise all of the vector features in a geographical area based on its context, from which patterns emerge. These patterns indicate features that have similar contexts, enabling the system to group the vector features according to their contexts based on their characteristics and attributes. Conversely, features that are anomalous within the region, that is, they do not fit the pattern of the surrounding features, are also identified. This is particularly important for identifying and resolving errors in the underlying topographic data.

Abstract: Aspects described herein provide a computer-implemented method and system for grouping topographic data based on the context of said data without the operator needing to make any assumptions. For each vector feature, its context, that is, information about the adjacent features, is incorporated in to the associated attribution data. In doing this, the system is able to characterise all of the vector features in a geographical area based on its context, from which patterns emerge. These patterns indicate features that have similar contexts, enabling the system to group the vector features according to their contexts based on their characteristics and attributes. Conversely, features that are anomalous within the region, that is, they do not fit the pattern of the surrounding features, are also identified. This is particularly important for identifying and resolving errors in the underlying topographic data.