| Abstract | There are many reasons to want to know the true surface area of the landscape, especially
in landscape analysis and studies of wildlife habitat. Surface area provides a better estimate
of the land area available to an animal than planimetric area, and the ratio of this
surface area to planimetric area provides a useful measure of topographic roughness of
the landscape. This paper describes a straightforward method of calculating surface-area
grids directly from digital elevation models (DEMs), by generating 8 3-dimensional triangles
connecting each cell centerpoint with the centerpoints of the 8 surrounding cells,
then calculating and summing the area of the portions of each triangle that lay within the
cell boundary. This method tended to be slightly less accurate than using Triangulated
Irregular Networks (TINs) to generate surface-area statistics, especially when trying to
analyze areas enclosed by vector-based polygons (i.e., management units or study areas)
when there were few cells within the polygon. Accuracy and precision increased rapidly
with increasing cell counts, however, and the calculated surface-area value was consistently
close to the TIN-based area value at cell counts above 250. Raster-based analyses
offer several advantages that are difficult or impossible to achieve with TINs, including
neighborhood analysis, faster processing speed, and more consistent output. Useful
derivative products such as surface-ratio grids are simple to calculate from surface-area
grids. Finally, raster-formatted digital elevation data are widely and often freely available,
whereas TINs must generally be generated by the user
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