Nonparametric machine learning for mapping forest cover and exploring influential factors
journal contribution
posted on 2020-07-01, 00:00 authored by B Liu, L Gao, B Li, R Marcos-Martinez, Brett BryanBrett BryanNonparametric machine learning for mapping forest cover and exploring influential factors
History
Journal
Landscape EcologyVolume
35Pagination
1683-1699Location
Dordrecht, the NetherlandsISSN
0921-2973eISSN
1572-9761Language
EnglishPublication classification
C Journal article, C1 Refereed article in a scholarly journalCopyright notice
2020, Springer Nature B.V.Issue
7Publisher
SPRINGERUsage metrics
Keywords
Science & TechnologyLife Sciences & BiomedicinePhysical SciencesEcologyGeography, PhysicalGeosciences, MultidisciplinaryEnvironmental Sciences & EcologyPhysical GeographyGeologyMachine learningSupport vector regressionArtificial neural networkRandom forestGradient boosted regression treeForest coverSUPPORT VECTOR REGRESSIONLAND-USESENSITIVITY-ANALYSISLOGISTIC-REGRESSIONCONTINUOUS FIELDSDEEP UNCERTAINTYNEURAL-NETWORKSTREE-COVERDYNAMICSCLASSIFICATIONSchool of Life and Environmental SciencesCentre for Integrative Ecology4102 Ecological applications
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