Publication:
Classifying dry sclerophyll forest from augmented satellite data : Comparing neural network, decision tree and maximum likelihood

dc.contributor.author Milne, Linda en_US
dc.contributor.author Gedeon, Tom en_US
dc.contributor.author Skidmore, Andrew en_US
dc.date.accessioned 2021-11-25T12:46:39Z
dc.date.available 2021-11-25T12:46:39Z
dc.date.issued 1995 en_US
dc.description.abstract Detailed maps derived from geographical data are becoming increasingly desirable for use in forest management. Many types of data are available for use in generating maps, for example, soil and vegetation maps. We look at a method for giving high level classifications that can be used as additional data for the generation of more detailed maps, and compare the results with other currently used techniques. We use multiple techniques to increase the reliability and accuracy of predictions. We describe a simple method of adjusting the balance of false positive and false negative classifications that are produced by the neural network. This allows better integration with non-neural network techniques. en_US
dc.identifier.uri http://hdl.handle.net/1959.4/37616
dc.language English
dc.language.iso EN en_US
dc.rights CC BY-NC-ND 3.0 en_US
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/3.0/au/ en_US
dc.source Legacy MARC en_US
dc.subject.other maximum likelihood en_US
dc.subject.other neural network en_US
dc.subject.other C4.5 en_US
dc.subject.other threshold outputs en_US
dc.subject.other Image Processing (280203) en_US
dc.subject.other Neural Networks, Genetic Algorithms and Fuzzy Logic (280212) en_US
dc.subject.other Other Artificial Intelligence (280213) en_US
dc.title Classifying dry sclerophyll forest from augmented satellite data : Comparing neural network, decision tree and maximum likelihood en_US
dc.type Conference Paper en
dcterms.accessRights open access
dspace.entity.type Publication en_US
unsw.accessRights.uri https://purl.org/coar/access_right/c_abf2
unsw.identifier.doi https://doi.org/10.26190/unsworks/376
unsw.relation.faculty Engineering
unsw.relation.faculty Science
unsw.relation.ispartofconferenceLocation Sydney, Australia en_US
unsw.relation.ispartofconferenceName ACNN'95 en_US
unsw.relation.ispartofconferenceProceedingsTitle Proc. 6th Australian Conference on Neural Networks, ACNN'95 en_US
unsw.relation.ispartofconferenceYear 1995 en_US
unsw.relation.ispartofpagefrompageto 160-163 en_US
unsw.relation.originalPublicationAffiliation Milne, Linda, Computer Science & Engineering, Faculty of Engineering, UNSW en_US
unsw.relation.originalPublicationAffiliation Gedeon, Tom, Computer Science & Engineering, Faculty of Engineering, UNSW en_US
unsw.relation.originalPublicationAffiliation Skidmore, Andrew, Faculty of Science, UNSW en_US
unsw.relation.school School of Computer Science and Engineering *
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