Machine Learning for Ecology and Sustainable Natural Resource Management
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Published By Springer International Publishing

9783319969763, 9783319969787

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

A Perspective on the Future of Machine Learning: Moving Away from ‘Business as Usual’ and Towards a Holistic Approach of Global Conservation

Machine Learning for Ecology and Sustainable Natural Resource Management ◽

10.1007/978-3-319-96978-7_20 ◽

2018 ◽

pp. 411-430

Author(s):

Grant R. W. Humphries ◽

Falk Huettmann

Keyword(s):

Machine Learning ◽

Holistic Approach ◽

Global Conservation ◽

The Future ◽

Business As Usual

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Machine Learning for Macroscale Ecological Niche Modeling - a Multi-Model, Multi-Response Ensemble Technique for Tree Species Management Under Climate Change

Machine Learning for Ecology and Sustainable Natural Resource Management ◽

10.1007/978-3-319-96978-7_6 ◽

2018 ◽

pp. 123-139

Author(s):

Anantha M. Prasad

Keyword(s):

Climate Change ◽

Machine Learning ◽

Tree Species ◽

Ecological Niche ◽

Ecological Niche Modeling ◽

Niche Modeling ◽

Ensemble Technique ◽

Species Management

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Machine Learning in Wildlife Biology: Algorithms, Data Issues and Availability, Workflows, Citizen Science, Code Sharing, Metadata and a Brief Historical Perspective

Machine Learning for Ecology and Sustainable Natural Resource Management ◽

10.1007/978-3-319-96978-7_1 ◽

2018 ◽

pp. 3-26 ◽

Cited By ~ 1

Author(s):

Grant R. W. Humphries ◽

Falk Huettmann

Keyword(s):

Machine Learning ◽

Citizen Science ◽

Historical Perspective ◽

Code Sharing

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Image Recognition in Wildlife Applications

Machine Learning for Ecology and Sustainable Natural Resource Management ◽

10.1007/978-3-319-96978-7_14 ◽

2018 ◽

pp. 285-294

Author(s):

Dawn R. Magness

Keyword(s):

Image Recognition

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Boosting, Bagging and Ensembles in the Real World: An Overview, some Explanations and a Practical Synthesis for Holistic Global Wildlife Conservation Applications Based on Machine Learning with Decision Trees

Machine Learning for Ecology and Sustainable Natural Resource Management ◽

10.1007/978-3-319-96978-7_3 ◽

2018 ◽

pp. 63-83

Author(s):

Falk Huettmann

Keyword(s):

Machine Learning ◽

Decision Trees ◽

Real World ◽

Wildlife Conservation ◽

The Real ◽

Practical Synthesis

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Ensembles of Ensembles: Combining the Predictions from Multiple Machine Learning Methods

Machine Learning for Ecology and Sustainable Natural Resource Management ◽

10.1007/978-3-319-96978-7_5 ◽

2018 ◽

pp. 109-121 ◽

Cited By ~ 1

Author(s):

David J. Lieske ◽

Moritz S. Schmid ◽

Matthew Mahoney

Keyword(s):

Machine Learning ◽

Learning Methods ◽

Machine Learning Methods

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Machine Learning for ‘Strategic Conservation and Planning’: Patterns, Applications, Thoughts and Urgently Needed Global Progress for Sustainability

Machine Learning for Ecology and Sustainable Natural Resource Management ◽

10.1007/978-3-319-96978-7_16 ◽

2018 ◽

pp. 315-333

Author(s):

Falk Huettmann

Keyword(s):

Machine Learning

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Mapping Aboveground Biomass of Trees Using Forest Inventory Data and Public Environmental Variables within the Alaskan Boreal Forest

Machine Learning for Ecology and Sustainable Natural Resource Management ◽

10.1007/978-3-319-96978-7_7 ◽

2018 ◽

pp. 141-160

Author(s):

Brian D. Young ◽

John Yarie ◽

David Verbyla ◽

Falk Huettmann ◽

F. Stuart Chapin

Keyword(s):

Boreal Forest ◽

Aboveground Biomass ◽

Forest Inventory ◽

Environmental Variables ◽

Inventory Data ◽

Forest Inventory Data

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How the Internet Can Know What You Want Before You Do: Web-Based Machine Learning Applications for Wildlife Management

Machine Learning for Ecology and Sustainable Natural Resource Management ◽

10.1007/978-3-319-96978-7_17 ◽

2018 ◽

pp. 335-351 ◽

Cited By ~ 1

Author(s):

Grant R. W. Humphries

Keyword(s):

Machine Learning ◽

Wildlife Management ◽

The Internet ◽

Web Based ◽

Machine Learning Applications

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Use of Machine Learning (ML) for Predicting and Analyzing Ecological and ‘Presence Only’ Data: An Overview of Applications and a Good Outlook

Machine Learning for Ecology and Sustainable Natural Resource Management ◽

10.1007/978-3-319-96978-7_2 ◽

2018 ◽

pp. 27-61 ◽

Cited By ~ 1

Author(s):

Falk Huettmann ◽

Erica H. Craig ◽

Keiko A. Herrick ◽

Andrew P. Baltensperger ◽

Grant R. W. Humphries ◽

...

Keyword(s):

Machine Learning

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Machine Learning for Ecology and Sustainable Natural Resource ManagementLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer International Publishing

A Perspective on the Future of Machine Learning: Moving Away from ‘Business as Usual’ and Towards a Holistic Approach of Global Conservation

Machine Learning for Macroscale Ecological Niche Modeling - a Multi-Model, Multi-Response Ensemble Technique for Tree Species Management Under Climate Change

Machine Learning in Wildlife Biology: Algorithms, Data Issues and Availability, Workflows, Citizen Science, Code Sharing, Metadata and a Brief Historical Perspective

Image Recognition in Wildlife Applications

Boosting, Bagging and Ensembles in the Real World: An Overview, some Explanations and a Practical Synthesis for Holistic Global Wildlife Conservation Applications Based on Machine Learning with Decision Trees

Ensembles of Ensembles: Combining the Predictions from Multiple Machine Learning Methods

Machine Learning for ‘Strategic Conservation and Planning’: Patterns, Applications, Thoughts and Urgently Needed Global Progress for Sustainability

Mapping Aboveground Biomass of Trees Using Forest Inventory Data and Public Environmental Variables within the Alaskan Boreal Forest

How the Internet Can Know What You Want Before You Do: Web-Based Machine Learning Applications for Wildlife Management

Use of Machine Learning (ML) for Predicting and Analyzing Ecological and ‘Presence Only’ Data: An Overview of Applications and a Good Outlook

Machine Learning for Ecology and Sustainable Natural Resource Management
Latest Publications