Nonparametric machine learning for mapping forest cover and exploring influential factors

Liu, Bao, Gao, Lei, Li, Baoan, Marcos-Martinez, Raymundo and Bryan, Brett A. 2020, Nonparametric machine learning for mapping forest cover and exploring influential factors, Landscape ecology, vol. 25, pp. 1683-1699, doi: 10.1007/s10980-020-01046-0.

Attached Files
Name Description MIMEType Size Downloads

Title Nonparametric machine learning for mapping forest cover and exploring influential factors
Author(s) Liu, Bao
Gao, Lei
Li, Baoan
Marcos-Martinez, Raymundo
Bryan, Brett A.ORCID iD for Bryan, Brett A. orcid.org/0000-0003-4834-5641
Journal name Landscape ecology
Volume number 25
Start page 1683
End page 1699
Total pages 17
Publisher Springer
Place of publication Dordrecht, the Netherlands
Publication date 2020-07
ISSN 0921-2973
1572-9761
Keyword(s) Science & Technology
Life Sciences & Biomedicine
Physical Sciences
Ecology
Geography, Physical
Geosciences, Multidisciplinary
Environmental Sciences & Ecology
Physical Geography
Geology
Machine learning
Support vector regression
Artificial neural network
Random forest
Gradient boosted regression tree
Forest cover
LAND-USE
SENSITIVITY-ANALYSIS
LOGISTIC-REGRESSION
CONTINUOUS FIELDS
DEEP UNCERTAINTY
NEURAL-NETWORKS
TREE-COVER
DYNAMICS
CLASSIFICATION
Language eng
DOI 10.1007/s10980-020-01046-0
Indigenous content off
Field of Research 04 Earth Sciences
05 Environmental Sciences
06 Biological Sciences
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Persistent URL http://hdl.handle.net/10536/DRO/DU:30139565

Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 44 Abstract Views, 1 File Downloads  -  Detailed Statistics
Created: Fri, 03 Jul 2020, 11:19:02 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.