Machine learning approaches for forest classification and change analysis using multi-temporal Landsat TM images over Huntington Wildlife Forest-Reference-Cited by-同舟云学术

Machine learning approaches for forest classification and change analysis using multi-temporal Landsat TM images over Huntington Wildlife Forest

Published:2013-08 Issue:4 Volume:50 Page:361-384
ISSN:1548-1603
Container-title:GIScience & Remote Sensing
language:en
Short-container-title:GIScience & Remote Sensing

Author:

Li Manqi¹,Im Jungho¹,Beier Colin²

Affiliation:

1. a School of Urban and Environmental Engineering , Ulsan National Institute of Science and Technology (UNIST) , Ulsan , 689-798 , South Korea

2. b Department of Forest and Natural Resources Management , College of Environmental Science and Forestry, State University of New York , Syracuse , NY , 13210 , USA

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/15481603.2013.819161

Reference67 articles.

1. Forest Cover Mapping in North-Central Mexico: A Comparison of Digital Image Processing Methods

2. Mapping a specific class for priority habitats monitoring from satellite sensor data

3. Revised landsat-5 tm radiometric calibration procedures and postcalibration dynamic ranges

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