Modelling terrains: how far do you need to go?

MSIAC kindly send me their online Journal. The current issue has an interesting article on the simulation of terrain, which shows the extent to which modelling is taken and the (self-defeating?) complexity that is developing.

The article, TERRAIN SURFACE CODES FOR AN ALL-SEASON, OFF-RIDE MOTION SIMULATOR, by Paul W. Richmond, Alexander A. Reid, Sally A. Shoop and George L. Mason, describs the syst4matic modelling of different terrains. This is to provide data for vehicle/ trrain interaction algorithms used in US Army tank simulators.

The abstract says: “The attributes important for predicting the distribution of all-season terrain parameters soil type, drainage, slope, aspect, canopy, and elevation. Bullock… developed methodology to infer soil strength values from soil type, wetness index, geographic location and a seasonal parameter (dry, average, wet, wet-wet). Following this methodology and adding capability to spatially distribute snow and thawing/frozen ground, a more distinct value of climate impact (e.g.,monthly, weekly or even hourly) is indexed to a set of principal terrain mechanics parameters. Microclimate considerations suggest that soil type; wetness or drainage index, slope, aspect, and canopy should provide a unique set of indices which, when combined with climatologic and geographic information will allow estimates of the required terrain mechanics properties…”

The paper refers to soil/ terrain classification codes developed by the
Unified Soil Classification System (USCS),
CCTT, the Close Combat Tactical Trainer produced by the US Army in 1998
– the Simnet Mobility Index – 15 soil types
– the CCTT codes – 30 codes
– the UAMBL (Unit of Action Manoeuvre Battle Lab) – 28 codes. (And a contender for the worst official website of 2006)

and theres the added problem of translating between different databases.

Im impressed and amazed firstly by the amount of detail people go into, but also by the bureaucracy and wasted effort involved in translating one classification into another and in arguing the finer details. With $388 bn to play for, Parkinsons law may start to exert some influence. However, with main battle tanks costing $4.3m each, I suppose the cost of several of them bogging down is much higher than this research. Not to mention losing lives, and battles.

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