Cover Image
Read Now

Machine Learning for Ecology and Sustainable Natural Resource Management

Ecologists and natural resource managers are charged with making complex management decisions in the face of a rapidly changing environment resulting from climate change, energy development, urban sprawl, invasive species and globalization. Advances in Geographic Information System (GIS) technology,...

Full description

Bibliographic Details
Other Authors: Humphries, Grant (Editor), Magness, Dawn R. (Editor), Huettmann, Falk (Editor)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2018, 2018
Edition:1st ed. 2018
Subjects:
Computer Appl. In Life Sciences
Computational Biology 
Pattern Recognition
Biostatistics
Data Mining
Bioinformatics 
Data Mining And Knowledge Discovery
Ecology
Ecology 
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • 1: Introduction to Machine Learning A. Data-intensive science B. Data Issues and Availability
  • 2: Data-mining in Ecological and Wildlife Research A. Multiple Methods in the Scientific Process B. Data-mining in Ecological and Wildlife Research C. Applications in Ecological Research a. Predicting Patterns in Space and Time b. Data Exploration and Hypothesis Generation c. Pattern Recognition for Sampling D. Bringing It All Together: Leveraging Multiple Methods to Increase Knowledge for Resource Management
  • 3: Machine Learning and Resource Management A. Web-based Machine Learning Applications for Wildlife Management B. Linking Machine Learning in Management Applications C. Machine Learning and the Cloud for Natural Resource Applications D. The Global View: Hopes and Disappointments E. The Future of Machine Learning

Similar Items