AUTOMATED SCALE DEPENDENT VIEWS OF HILLS AND RANGES VIA MORPHOMETRIC ANALYSIS
O. Chaudhry, W. Mackaness
Being part of continuous phenomenon, real world natural features do not have exact or precise spatial extents (in the way that anthropogenic features do). Nevertheless it is common to categorise landscape into different morphological structures such as mountains, hills, valleys for the purpose of analysis or visualisation.
There is a scale dependency to the precision of their boundaries. Current Geographic Information Systems lack data schema to deal with this fuzziness. Their discrete boundaries are objectively defined, loosely connected with our prototypical views on what is meant by ‘a mountain’ or ‘a mountain chain’. This paper presents a quantitative technique that automatically identifies landscape features such as mountains, hills and ranges, and creates the partonomic structure that links membership between these phenomena, and stores these discrete objects.
This paper examines the relationship
between scale and landscape features in the context of their representation in
map form. The research is premised on the idea that large scale features are
comprised and defined by the smaller features that comprise them (that mountain
chains are a collection of clustered yet individually identifiable mountains).
Before we can begin identifying the higher order features, we must first
develop techniques for automatically discerning the smaller features. A
mountain is defined by its prominence (relative height among surrounding
features), extent, and a variety of morphological characteristics. The
algorithm presented here uses derivatives of elevation and the density of
morphological variation in order to automatically identify individual mountain
and hill extents. This database transformation process is viewed as an
essential prerequisite to cartographic portrayal of these features at a range
of scales. The approach was applied to the identification of hills and ranges
in and around