Whilst working with OGR, I came across the following field used define a geographic dataset:


The spatial dimension (2, 3 or 4 dimensional) of the column.

Whilst I've used 2D and 3D features, are there any examples of datasets in GIS that use the fourth dimension, and do any GIS systems actually handle these?


The 4d with regards to OGR / PostGIS is likely to be used for M-values (M-Aware in ArcGIS) (though I've yet to find this in a tech doc). However the quesion of (real?!) 4d in GIS remains open.


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    This is probably the most psychedelic image in gis.stackexchange.com so far... – amercader Feb 7 '11 at 11:23
  • Does this include principal components analysis of hyperspectral imagery? (Lots of dimensions there.) – Kirk Kuykendall Feb 7 '11 at 17:03
  • @Kirk Good point. But I see that the quotation specifies "spatial" dimension, which presumably means something more than an abstract idea of "space." (On the other hand, any dimension beyond 3 must have some element of abstraction to it.) BTW, you don't need to invoke PCA: hyperspectral images potentially (and probably do, in general) have as many dimensions as there are slices of the spectrum. PCA merely identifies the dimensions in which most of the variation occurs. – whuber Feb 7 '11 at 19:06
  • @whuber It's been a long time since I've done any image analysis, but it seems like if two adjacent pixels are separated by a smaller spectral distance than two pixels that are spatially far apart, then it seems more likely that those two pixels should be classified the same. In other words the boundary between (the concept of) spectral distance and spatial distance is not always sharp. Internally, dealing with spectral dimensions versus spatial dimensions won't be that different will it? – Kirk Kuykendall Feb 7 '11 at 19:17
  • @Kirk There is a formal definition of "dimension" of a set of vector-like objects as being the smallest number of linearly independent elements in that set. This is independent of any applications such as clustering, spectral analysis, or even distance. When "spatial" is used in a GIS context, though, it comes implicitly with understanding that it includes a geometry that is appropriate to describe physical objects and relationships among them. That means we care about things like distance, length, bearing, angle, and area. The latter do make sense for images, but ... – whuber Feb 7 '11 at 19:27

I think the four dimensions used in GIS are x, y, z (height), m (measure). This measure can be time or something else like the projected distance along a reference line, e.g. a pipeline.

  • That would be disappointing..! But likely to be the true 4d value. Is 4d the MAware equivalent in OGR? – geographika Feb 7 '11 at 11:37
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    Measures, although they require a fourth number, would not ordinarily be thought of as an additional "dimension." A dimension would have to be a coordinate that is independent of the other three. Measures are always functions of the two (or three) spatial locations of points in a feature. They act, mathematically, as analogs of grids: a grid is a mechanism to assign an attribute to every location within a polygon (a 2D object) while a measure assigns an attribute to every location within a polyline (a 1D object). – whuber Feb 7 '11 at 14:04

In this case the forth dimension is measure as gissolved mentions, but more commonly the fourth dimension does refer to time. Historically, most GIS systems have been weak at integrating time, but the increase in dynamic modeling over the years has brought time into most current GIS systems. See for example this recent question.

While the software has been slow to formalize concepts of time, there is a good body of GIScience literature which covers the conceptual basis of dealing with time, such as the articles covered in Martin Raubal's 288MR course.


i think 4D used to show time with x,y,z, and time for any feature. we used additional dimension to show time when we are getting x,y, and elevation of any feature at any place.

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