Forest Biometry, Modelling and Information Sciences
FBMIS is a peer reviewed internet journal which provides free access to original research and review articles in the following areas:
|Forest Biometry, which includes (i) Data collection methods including Measurement & Mensuration, Remote Sensing, Experiments, Sampling and Inventory for the collection of tree or forest data, or data relating to processes and populations that occur within forests or trees, and (ii) Use of Statistical methods to analyze, summarize and interpret forest data.|
|Forest Modelling, which includes use of Mathematical, Statistical, Stochastic and Computer Software models to represent the structure and processes occurring in the forest, or in trees, and the use of statistical methods for fitting such models to forest or tree data. Forest Growth and Yield Models are a major application area.|
|Forest Information Sciences, which includes techniques for the storage, warehousing and archiving of data, metadata and information, and its management for the purposes Analysis, Modelling, Knowledge extraction and the building of Forest Management Information and Decision Support Systems.|
Researchers in any of these areas are invited to submit articles to the journal. See FBMIS Coverage for more details.
FBMIS is electronic in form, being published primarily over the Internet. It is published by The FBMIS Group, University of Greenwich, ( ISSN 1740-5955). See the copyright form for details on The FBMIS Group.
The pdf form of presentation been adopted, allowing articles to be seen in the electronic or printed form in exactly the same format as they would be seen in a traditional hardcopy journal. Hence articles will have page numbers, and be collected into Volumes comprising about ten articles. Periodically, Volumes of FBMIS will be printed in a hardcopy form and be deposited in the major archival libraries with ISBN numbers so as to facilitate academic referencing. An additional hardcopy print run may be produced, depending on demand.
In order to enable the use of advanced web techniques, and interactive simulations, published articles will be cross-referenced to the author's own URL address if the author so desires.
Authors of articles reporting research and development of new models are encouraged to deposit their models, code, fitting algorithms, and sample data to the Forest Model Archive, (FMA), so as to assist in the long term preservation of these models, and world wide accessibility to them.
FBMIS is expected to be mirrored at a number of other sites in due course.
Disclaimer: The opinions and views expressed in the articles published in FBMIS are those of the authors, and are not necessarily shared by the The Editor and the Editorial board of FBMIS. While the editorial and review processes followed try to ensure the validity and correctness of the reported work in the articles published in FBMIS, the Editor and Editorial Board disclaim responsibility for any damages that may be incurred from the use of the information published in FBMIS, or the models published in the associated FMA.