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GIS paper needs clarifications

Posted on 2016-05-18
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Below is an extract taking from a paper available at: http://www.geog.ucsb.edu/~good/papers/414.pdf

I need to understand it please very well. It is all clear until he starts the second paragraph.
The second paragraph mentioned an indicator I am not sure I understand the whole second paragraph.  Please help to clarify I am starting to study these models and their integration with GIS. Thanks

A model is a computer program that takes a digital representation of one or more aspects of the real world and transforms them to create a new representation. Models can be static, if the input and the output both correspond to the same point in time, or dynamic, if the output represents a later point in time than the input.

The common element in all of these models is the operation of the GIS in multiple stages, whether they be used to create complex indicators from input layers or to represent time steps in the operation of a dynamic process. Static models often take the form of indicators, combining various inputs to create a useful output. For example, the Universal Soil Loss Equation (USLE) combines layers of mapped information about slope, soil quality, agricultural practices, and other properties to estimate the amount of soil that will be lost to erosion from a unit area in a unit time (Wischmeier and Smith 1978). The DRASTIC model (fig. 1) estimates geographic variation in the vulnerability of groundwater to pollution, again based on a number of mapped properties (Aller et al. 1987). Dynamic models, on the other hand, represent a process that modifies or transforms some aspect of the Earth’s surface through time. Contemporary weather forecasts are based on dynamic models of the atmosphere; dynamic models of stream flow are used to predict flooding from storms; and dynamic models of human behavior are used to predict traffic congestion
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Question by:JRawabi
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by:slubek
ID: 41608562
I don't know that models, but it seems that USLE model is static because it can be used to predict one number - amount of soil eroded from (for example) one square mile during time unit (for example one month). Based on input values (slope, sole quality etc.), it gives us, for example, 10 tones per month per square mile.

Indicator (in that meaning) is a function combining input values into output. Linear indicator is someting like:

errosion = a * time * surface              (bigger surface means bigger errosion and so with longer time)

where

a = a1 * slope + a2 * soil_quality + a3 * quality_of_agricultural_practices + a4 * ... etc.

To create model (indicator) you have to calculate values of a1, a2, a3, ... an, based on known inputs. But there are a lot of methods to do it - statistical regression like least squares, neural networks etc. Each method gives us different coefficient values. And each method has different accuracy.
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