Nonparametric machine learning for mapping forest cover and exploring influential factors
Version 2 2025-11-13, 01:51
Version 1 2020-07-01, 00:00
journal contribution
posted on 2025-11-13, 01:51 authored by B Liu, L Gao, B Li, R Marcos-Martinez, Brett BryanBrett BryanNonparametric machine learning for mapping forest cover and exploring influential factors
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Location
Dordrecht, the NetherlandsOpen access
- Yes
Language
engPublication classification
C Journal article, C1 Refereed article in a scholarly journalCopyright notice
2020, Springer Nature B.V.Journal
Landscape EcologyVolume
35Pagination
1683-1699ISSN
0921-2973eISSN
1572-9761Issue
7Publisher
Springer NatureUsage 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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