Feature(s)
A feature in Ilwis-Objects is anything that can have one or more geometries and has one distinct identity.
A simple view on a feature would be something with one identity and one geometry( maybe of the multi sort). As such this is a workable representation and one that is adopted by many data-models. This representation though is highly redundant in a time when spatial-temporal data or multi scale is much more available. As a feature has (usualy) a whole set of dependent attributes, this whole set needs to be copied for each (e.g) temporal location as there is no implicit link between the features in the temporal direction. There are several solutions for this. In Ilwis-Objects we choose to let each feature have list of one or more geometries where the order of the geometries has significance. The nature of the significane is determined by the context of the data-set. In this way we reduce the redundancy and create a natural relation between the same feature seen in a different dimension.
In the Ilwis-Objects terminology an ice berg tracked over time (assuming it doesn’t split) can be represented as one feature. It may change shape and/or location in time but it is still the same ice berg. The track of geometries is referred to as the ‘index ‘, similar to the same notion in the raster data model.
A feature at a certain index is referred to as feature-node and is similar to a traditional elements of vector maps. Apart from geometries, features also have extensible set of other properties (the attributes) that depend on the nature of the feature and context in which it is used. Features are thus described by
- Per index entry a geometry ( which maybe an empty geometry, but at least one for the whole index)
- Index dependent attributes
- Index independent attributes.
The index maps onto a domain, defining the semantics of the index. Thus an Index may represent a time dimension, a scale dimension or simply a real 3D height or any other domain type.
Features and Feature-nodes are very similar and we will