GIS

Why is there so little geospatial analysis?

 I am going to veer off the question path on this one. I think there is a proliferation of geospatial analysis going on around the world. But we need to understand what we mean when we say – geospatial analysis.

 

In the book Geospatial Analysis, authors Michael J. Smith, Michael F. Goodchild and Paul A. Longley suggest “geospatial analysis” exists in conceptual terms as “a subset of techniques that are applicable when, as a minimum, data can be referenced on a two-dimensional frame and relate to terrestrial activities.” They reason that the frame is the integral component here, and that “everything is nowhere” without it. They go on to explain that statistics (descriptive, exploratory, and explanatory statistics) should be considered and that strict 2D analysis alone remains too restrictive. Thus, geospatial analysis includes a 3D consideration. Additionally, visualisation is also considered integral to geospatial analysis.

 

If we take 10 geospatial professionals and ask them to define geospatial analysis, I would be willing to bet 10 Euro that we would get at least 5 different answers. It is difficult for many to define.

 

Nevertheless, I think we would find many people trying to explain products or services that can be broadly labelled as 'descriptive, exploratory or explanatory' in nature. These terms would encompass surface modeling just as well as they could include Virtual Earth web maps, GIS buffering, CAD cross section layouts, places Inuit live, land use patterns or the route an oil tanker is taking through the North Sea.

 

Even a quick cursory glance through the Index of Geospatial Analysis will encounter terms like measurement scales, geometric means, resolution, stream networks, variogram, breaklines, ISODATA and percentile, for example. Yet, you will not find the words Google Earth, Virtual Earth or virtual reality (VR) in that index. Is geospatial analysis hard science alone? Is it solely in the domain of geo-computation, mathematics and statistics?

 

We need to ask ourselves, what is the role of traditional science such as geo-computation, mathematics and statistics in modern day geospatial analysis and what is the role of some of the new technologies (often generated from traditional geospatial analysis) like virtual worlds, VR and probably robotics and artificial intelligence (AI) to come soon.

 

When I think about geospatial analysis I see it in terms of a constellation of products like GIS, CAD, hydrological modeling software, lidar point cloud analysis software and even GPS base station software and processing and so on. Hardware, software, media and approach all contribute to description, exploration and explanation.

 

Ultimately, we are faced with the question of quality and re-use when talking about geospatial analysis. And when we start to talk about quality and re-use, then we begin to see that some data cannot be used for geospatial analysis because it is not very good data; either we don't know where it came from, how it was collected, when it was collected or even if it is in the database correctly etc.

 

It is important to recognise that a huge amount of geospatial analysis is going on, particularly due to the positive impacts of virtual worlds, VR, gaming and robotics etc., and that each of these is raising geospatial awareness around the world immensely - importantly raising spatial literacy in the public mind, and eye.

But, we need to nudge our neurons to understand (and explain to others) the distinction between data types, data quality and reuse factors and how these correlate to mathematics, statistics and so on, and that value in a wider landscape of describing our world, exploring it and explaining all the things going on in it – the least of which is a need for high quality data analysis to solve real problems.

 

We must embrace the fact that a real need for quality data and analysis is a critical necessity in resolving basic physical and environmental processes, building critical infrastructure and securing our cities, for example. And that this implies a high quality of spatial analysis is needed. We need to leverage the spatial awareness gained through virtual worlds, VR, games and so on, with the realities of terrestrial processes. This is not an either / or proposition.

Information:

Geospatial Analysis: Web site, PDF and Book

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Read what Matt Ball has to say on this topic here.

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