Difference between revisions of "Forest informatics"

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''(This article was taken from Wikipedia)''
'''Forest informatics''' is the combined science of forestry and
 
[[informatics]], with a special emphasis on collection, management,
Forest Informatics is the combined science of [[Forestry]] and
[[Informatics]], with a special emphasis on collection, management,
and processing of data, [[information]], and knowledge, and the
and processing of data, [[information]], and knowledge, and the
incorporation of informatic concepts and theories specific to enrich
incorporation of informatic concepts and theories specific to enrich
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architecture to preemptively generate possible strategic, tactical,
architecture to preemptively generate possible strategic, tactical,
and operational solutions for forest managers.
and operational solutions for forest managers.
== References ==
<references/>


== Contributing Disciplines ==
== Contributing Disciplines ==
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Geographic Information Systems
Geographic Information Systems


== See also ==
==Notes==
 
This article heavily reuses content from [http://en.wikipedia.org/wiki/Forest_informatics the Wikipedia article].
 
== References ==
<references/>


[[Category:Informatics]]
[[Category:Informatics]]

Revision as of 21:13, 24 April 2014

Forest informatics is the combined science of forestry and informatics, with a special emphasis on collection, management, and processing of data, information, and knowledge, and the incorporation of informatic concepts and theories specific to enrich forest management and forest science; it has a similar relationship to library science and information science.

As is Information science or archival science, Forest Informatics is an interdisciplinary science primarily concerned with the collection, classification, manipulation, storage, retrieval and dissemination of information. Information, in this context, includes both human and machine readable documents. Examples of human readable documents include maps, field data sheets, operational schedules, and long term asset management plans with narrative text. Machine readable documents include files for geographic information systems (GIS), Global Positioning Systems (GPS), and other applications like spreadsheets, and relational database management systems.

As in management science, Forest Informatics uses decision support systems, mathematical modeling, statistics, and algorithms from engineering, operations research, computer science, and artificial intelligence to support decision-making activities. Common forestry problems include harvest scheduling, model fitting, optimal sampling, remote sensing, crew assignment, image classification, treatment timing, and log bucking problems, many of which can be formulated as optimization problems (e.g. generalized assignment problem, traveling salesman problem, knapsack problem, job shop scheduling, and vehicle routing problems). The practice includes information processing and the engineering of nformation systems, decision support systems, geographic information systems, and global positioning systems. The research field includes studies the structure, algorithms, behavior, and interactions of natural and artificial systems that store, process, access and communicate information about forested ecosystems.

History

In 1970, J. G. Grevatt wrote an article titled, "Management Information and Computers in Forestry." [1] In the article, the author describes and discusses different dimensions of management information (i.e. operation, expenditure, location, and time) including the nature of management information and decisions, management information in forestry, the management information system itself, the application of computers, the structure of a computer based system, comparisons between clerical and computer systems, and the impact on the field manager. The author concludes that the use of computers to process management data may be justified on grounds of cost and improved information in organizations of a critical size.

At the time of that article, computers, databases, and geographic information systems were still in their infancy and tools like the Global Positioning Systems of today were yet invented. Management database systems for business were more prevalent. Over the next 30 years, computers became more powerful, smaller, and less expensive. Relational database management systems had become commonplace in business, interrogating the computer system had become standardized with languages like SQL, and faster networks for data and information integration have become highly integrated. In that time, geographic information systems that could run on desktop computers and could be customized for various tasks were also developed, but as separate systems.

Within the last 10 years, specialized fields of study at the University level are offered at the several forestry schools where students learn the principles of quantification, modeling, descriptive and predictive analyses of natural resources attributes needed for sound management of forested ecosystems.

Software specifically devoted to analyzing management decisions for forested ecosystems have been developed, and used in several large scale planning projects. For example, the Ecosystem Management Decision Support (EMDS) system is an application framework for knowledge-based decision support of ecological analysis and planning. Open source software solutions have also become more widely accepted as well, as is seen in the expansion of ecological extensions for statistical tools like R. A recent example would be the book written by Andrew Robinson and Jeff D. Hamann about using R for forest analytics[2] .


In 2006, the United Nations declared 2011 to be International Year of Forests.

Forest Informatics, Inc. has developed a PostgreSQL template, a set of software agents, and a collection of reports, maps, and data feeds. The application uses an intelligent agent architecture to preemptively generate possible strategic, tactical, and operational solutions for forest managers.

Contributing Disciplines

Math Artificial intelligence Computer science Information science Information theory Information technology Biodiversity Informatics Ecoinformatics Evolutionary informatics Geoinformatics

Mathematical logic Graph theory Computational geometry Geographic Information Systems

Notes

This article heavily reuses content from the Wikipedia article.

References