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tutorial:introduction [2019/08/30 16:43]
argemiro [What will you learn?]
tutorial:introduction [2020/02/18 10:55] (current)
argemiro
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 ===== Introduction ===== ===== Introduction =====
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 +DINAMICA EGO (Environment for Geoprocessing Objects) (www.dinamicaego.com) is a spatially explicit, high performance,​ modeling freeware used by many scholars around the world. Dinamica EGO modeling platform presents outstanding possibilities for the design of spatial models, from analytical to the very complex dynamic ones. These models can ultimately include nested iterations, dynamic feedbacks, multi-region,​ multi-scale and multi-scale approach, manipulation and algebraic combination of data in several formats - such as maps, tables, matrices and constants - decision processes for bifurcating and joining execution pipelines, and a series of complex spatial algorithms for the analysis and simulation of space-time phenomena.
  
-DINAMICA EGO software (www.csr.ufmg.br/​dinamica) is a spatially explicit, high performance,​ modeling freeware used by many scholars around the world. Dinamica EGO modeling platform presents outstanding possibilities for the design of spatial models, from analytical to the very complex dynamic ones. These models can ultimately involve nested iterations, dynamic feedbacks, multi-region and multi-scale approach, manipulation and algebraic combination of data in several formats - such as maps, tables, matrices and constants - decision processes for bifurcating and joining execution pipelines, and a series of complex spatial algorithms for the analysis and simulation of space-time phenomena. +<​note>​ 
- +Dinamica EGO has been applied to numerous environmental studies, including the modeling of deforestation in the Amazon from local to basin-wide scales, urban dynamics, logging and other forestry rents in the Amazon, cattle ranching, forest fires, river regime, biodiversity,​ and agricultural expansion in Brazil. 
-<​note>​Dinamica EGO has been applied to numerous environmental studies, including the modeling of deforestation in the Amazon from local to basin-wide scales, urban dynamics, logging and other forestry rents in the Amazon, cattle ranching, forest fires, river regime, biodiversity ​offsets, and agricultural expansion in Brazil.See list of publication ​at www.csr.ufmg.br/​dinamica/​publications.</​note>​+\\ 
 +See list of publications ​at www.csr.ufmg.br/​dinamica/​publications. 
 +</​note>​
  
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-==== What will you learn? ==== +==== What will you learn? ====  
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-  +  * What is Dinamica EGO? 
- +  * How is this guidebook is structured? 
-  * What Dinamica EGO is +  * Where are the data and models used in the lessons? 
-  * How this guidebook is structured +\\
-  * Where are the data and models used in the lessons +
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-===Welcome to Dinamica Environment for Geoprocessing Objects (Dinamica EGO)!=== +===Welcome to Dinamica EGO!===
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-EGO stands for Environment for Geoprocessing Objects. The previous version of Dinamica was totally reengineered to become a modeling environment,​ now with outstanding possibilities for the design from the very simple static spatial model to very complex dynamic ones, which can ultimately involve nested iterations, dynamic feedbacks, multi-region approach, manipulation and algebraic combination of data in several formats, such as maps, tables, matrices and constants, decision processes for bifurcating and joining execution pipelines, and a series of complex spatial algorithms for the analysis and simulation of space-time phenomena.  +
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 The software environment,​ written in C++ and Java, holds a series of algorithms called functors. Each functor performs an operation. To date, we have implemented the most common spatial analysis algorithms available in commercial GIS (Geographic Information System), plus a series of algorithms especially designed for spatial simulations,​ including transition functions, calibration and validation methods. The software environment,​ written in C++ and Java, holds a series of algorithms called functors. Each functor performs an operation. To date, we have implemented the most common spatial analysis algorithms available in commercial GIS (Geographic Information System), plus a series of algorithms especially designed for spatial simulations,​ including transition functions, calibration and validation methods.
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-These functors are sequenced to establish data flow in the form of graphs. Through the Dinamica EGO graphical interface one can create models by simply dragging and connecting functors via their ports, which represent connectors to types of data, such as maps, tables, matrices, mathematical expressions and constants. Functors can be enveloped by “containers”,​ a special type of functor that is used, for example, to execute iterations or process data from specific regions of a map. Thus models can be designed as a diagram and execution follows a data flow chain. This friendly interface permits the design of simple to very complex spatial models that are saved in a script language in [[:​xml_script|XML format]] or [[:​ego_script|EGO programming language]]. 
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 +These functors are sequenced to establish data flow in the form of graphs. Through the graphical interface one can create models by simply dragging and connecting functors via their ports, which represent connectors to types of data, such as maps, tables, matrices, mathematical expressions and constants. Functors can be enveloped by “containers”,​ a special type of functor that is used, for example, to execute iterations or process data from specific regions of a map. Thus models can be designed as a diagram and their executions follow a data flow chain. This friendly interface enables designing from simple to very complex spatial models that are saved in a script language in [[:​xml_script|XML format]] or [[:​ego_script|EGO programming language]].
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-In sum, Dinamica EGO software favors simplicity, flexibility and good performance,​ optimizing speed and computer resources, such as memory and parallel processing. Most of its algorithms are designed to take advantage of multicore processor architecture. In additionDinamica EGO handles large raster format using disk paging. On the other hand, if memory ​is available, it can load all the input maps at the beginning ​of a model execution and keep them in memory only while they are needed. In this waythe software only accesses the disk at the end of an execution to write the final outputs orif a user specifiesat the end of an iteration to save the output maps from each time step     +In sum, Dinamica EGO software favors simplicity, flexibility and top performance,​ optimizing speed and computer resources, such as memory and parallel processing. Most of the algorithms are designed to take advantage of the multicore processor architecture, ​from version 5 onwards ​the software architecture ​is fully parallel. The parallel execution system uses a fixed number of execution threads (called workers) with task stealing to provide ​load balancing and increase ​the flexibility ​of how parallel tasks can be designed. In theoryall model components can run in parallelincluding independent functorsindependent loop steps, and pieces ​of map. Dinamica EGO handles large raster maps that are manipulated in parallel even when they are too big to fit in memoryIn addition, ​Dinamica EGO provides online coupling with R and Python
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-<note tip>​**This document is the original user guide of the described ​Dinamica EGO**The aim of this guidebook is to introduce the user to the vast possibilities of Dinamica EGO for the design of space-time models that can fully represent the complexity of various geographic phenomena</​note>  ​ +
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 ===Modular Guidebook Structure=== ===Modular Guidebook Structure===
-This Guidebook ​are modular in structure ​([[:​guidebook_start|Modeling Environmental Dynamics with Dinamica EGO]]). Each module is divided into lessons and is assigned a particular level in a progressive series:+\\ 
 +This guidebook introduces the user to the vast possibilities of Dinamica EGO for the design of space-time models that can fully represent the complexity of various geographic phenomena. ​This Guidebook ​is modular in structure. Each module is divided into lessons ​or examples ​and is assigned ​to a particular level in a progressive series ​of steps:
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-**MODULE II:** Working with maps on Dinamica EGO+**MODULE II:** Working with maps
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-**MODULE III:** Working with tables ​on Dinamica EGO+**MODULE III:** Working with tables
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-**MODULE IV:** Creating and using Submodels ​on Dinamica EGO+**MODULE IV:** Creating and using Submodels
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-**MODULE V:** Incorporating control structures into a model on Dinamica EGO+**MODULE V:** Incorporating control structures into a model
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-**MODULE VI:** Advanced spatial analyses ​on Dinamica EGO+**MODULE VI:** Advanced spatial analyses
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-**MODULE VII:​** ​Other Features ​of Dinamica EGO+**MODULE VII:​** ​Additional ​Features
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-**MODULE VIII:​** ​Other Applications ​of Dinamica EGO+**MODULE VIII:​** ​Additional ​Applications
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 ===Links in this Document=== ===Links in this Document===
-This document contains internal links. Clicking on an internal link opens an Dinamica ​Website. Links are shown in blue and are handled by the system browser. +This document contains internal links. Clicking on an internal link opens Website. Links are in blue.
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-===Download - Models and Inputs== +<​note>​We hope you can learn how to use software and apply it to countless environmental applications.</​note>​ 
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----- +☞[[:​lesson_1|Next Lesson]] 
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-<​note ​tip>We hope you can learn about the software and use it for countless environmental applications. ​**GOOD LUCK!**</​note>​+\\ 
 +☞[[:​guidebook_start| Back to Guidebook Start]]