A model is a representation of some part of the real world and hence has certain characteristics common with the real world. It therefore possible to study and operate on the model instead of the real world under various conditions. This is a very effective method to answer 'what if' questions. The procedure can be repeated by changing the data or altering the parameters of the model.
A map is a miniature representation of some part of the real world is a model while databases are also models. Maps and databases are usually static models.
Modelling and GIS are inseperable as GIS is a tool for modelling the real world.
Models can be static if the input and output both correspond to the same point in time, or dynamic, if the output represents a later point in time than the input. Static models often take the form of indicators combining various inputs to create a useful output. On the other hand, dynamic models represent a process that modifies or transforms some aspect of the Earth's surface through time.
In the context of GIS, modeling is defined as the operations of GIS that emulate processes of the real world at an instant or over a period of time. GIS models can be used to evaluate or predict future landscapes.
Analog GIS model is a representation of the real-world system in which every part of the real world appears in miniature in the model. In an analog model, all aspects of the system must be scaled by
the same ratio for the model to be valid.
In a digital model, all operations are conducted using a computer. Data is assembled in a data model and relevant aspects of the real world and coded to patterns of 0s and 1s. Digital models do not have a representative fraction. The level of geographic detail is captured in the spatial resolution.
Discrete models imitate processes that operate between discrete entities. Continuous models are formed on variables that are continuous functions of location. The discrete-object view and the continuous field-view are widely accepted distinctions between the conceptualizations of geographic space and geographic variation.
Geographic space is empty except where it is occupied by point, line or area objects that may overlap, do not exhaust all available space and are countable. For example, the discrete-object view is best to describe and represent biological organisms or man-made features like buildings, vehicles or fire hydrants.
In the continuous field view, there are no gaps in coverage and there is exactly one variable at each location.Continuous field models express knowledge of the operation of the physical system in terms of partial differential equations which relate the values, rate of change through time, spatial gradients and spatial curvatures of the continuously varying quantities.
Individual and aggregate models- It is possible to model any system using a set of rules about the mechanical behavior of the system’s basic objects (individual model). However, if the number of basic objects is far too large for this approach to be practical, the problem is solved by replacing individual objects with continuously varying estimates of abstracted properties such as density. Another approach is to aggregate (aggregate model) individual objects into larger wholes and to model the system through the
behavior of these aggregates.
Cellular Automata: In a cellular automaton, spatial variation is represented as a raster of fixed resolution, each cell is assigned to one of a number of defined states. Such models have been used widely to study processes of urban growth, in which case the possible states are limited. At each time step, the next state of each cell is determined by a number of rules based on the properties of the cell and its neighbors and on the states of the cell and its neighbors. The concepts of cellular automata were first explored by John Conway.
AGENT-BASED modeling is a computer based simulation in which a program is written to simulate the real-world situation. An agent-based model consists of an environment or framework that defines the scope and rules of actions, along with a number of agents representing one or more actors whose parameters and behaviors are defined. When the model is run, the characteristics of each agent are tracked through time and space. Agent-based modeling has found many interesting applications to geographic phenomena. Several efforts have been made to apply agent-based modeling to the emergence of land-use and land-cover patterns, with particular emphasis on the processes that lead to
greater fragmentation of land cover as a result of development and thus to problems for species that require specialized natural habitat.
A map is a miniature representation of some part of the real world is a model while databases are also models. Maps and databases are usually static models.
Modelling and GIS are inseperable as GIS is a tool for modelling the real world.
Models can be static if the input and output both correspond to the same point in time, or dynamic, if the output represents a later point in time than the input. Static models often take the form of indicators combining various inputs to create a useful output. On the other hand, dynamic models represent a process that modifies or transforms some aspect of the Earth's surface through time.
In the context of GIS, modeling is defined as the operations of GIS that emulate processes of the real world at an instant or over a period of time. GIS models can be used to evaluate or predict future landscapes.
Analog GIS model is a representation of the real-world system in which every part of the real world appears in miniature in the model. In an analog model, all aspects of the system must be scaled by
the same ratio for the model to be valid.
In a digital model, all operations are conducted using a computer. Data is assembled in a data model and relevant aspects of the real world and coded to patterns of 0s and 1s. Digital models do not have a representative fraction. The level of geographic detail is captured in the spatial resolution.
Discrete models imitate processes that operate between discrete entities. Continuous models are formed on variables that are continuous functions of location. The discrete-object view and the continuous field-view are widely accepted distinctions between the conceptualizations of geographic space and geographic variation.
Geographic space is empty except where it is occupied by point, line or area objects that may overlap, do not exhaust all available space and are countable. For example, the discrete-object view is best to describe and represent biological organisms or man-made features like buildings, vehicles or fire hydrants.
In the continuous field view, there are no gaps in coverage and there is exactly one variable at each location.Continuous field models express knowledge of the operation of the physical system in terms of partial differential equations which relate the values, rate of change through time, spatial gradients and spatial curvatures of the continuously varying quantities.
Individual and aggregate models- It is possible to model any system using a set of rules about the mechanical behavior of the system’s basic objects (individual model). However, if the number of basic objects is far too large for this approach to be practical, the problem is solved by replacing individual objects with continuously varying estimates of abstracted properties such as density. Another approach is to aggregate (aggregate model) individual objects into larger wholes and to model the system through the
behavior of these aggregates.
Cellular Automata: In a cellular automaton, spatial variation is represented as a raster of fixed resolution, each cell is assigned to one of a number of defined states. Such models have been used widely to study processes of urban growth, in which case the possible states are limited. At each time step, the next state of each cell is determined by a number of rules based on the properties of the cell and its neighbors and on the states of the cell and its neighbors. The concepts of cellular automata were first explored by John Conway.
AGENT-BASED modeling is a computer based simulation in which a program is written to simulate the real-world situation. An agent-based model consists of an environment or framework that defines the scope and rules of actions, along with a number of agents representing one or more actors whose parameters and behaviors are defined. When the model is run, the characteristics of each agent are tracked through time and space. Agent-based modeling has found many interesting applications to geographic phenomena. Several efforts have been made to apply agent-based modeling to the emergence of land-use and land-cover patterns, with particular emphasis on the processes that lead to
greater fragmentation of land cover as a result of development and thus to problems for species that require specialized natural habitat.
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