A study of a Gaussian mixture model for urban land-cover mapping based on VHR remote sensing imagery-Reference-Cited by-同舟云学术

A study of a Gaussian mixture model for urban land-cover mapping based on VHR remote sensing imagery

Published:2015-12-08 Issue:1 Volume:37 Page:1-13
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Tao Jianbin¹²,Shu Ning³,Wang Yu²,Hu Qingwu³,Zhang Yanbing²

Affiliation:

1. Key Laboratory for Geographical Process Analysis & Simulation of Hubei Province, Central China Normal University, Wuhan, PR China

2. School of Urban and Environmental Sciences, Central China Normal University, Wuhan, PR China

3. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, PR China

Funder

Major cultivating project of CCNU, the Geographic Processes and Ecological Response in the middle reach of the Yangtze River

Faculties’ start-up fund for scientific research Central China Normal University (Theories and Methodologies of CO2 Estimates Using Remote Sensing Data in Urban Area)

Key Laboratory of Geographic Conditions Monitoring, National Administration of Surveying, Mapping and Geoinformation, P.R.China

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/2150704X.2015.1101502

Reference25 articles.

1. A new look at the statistical model identification

2. Support vector machines using GMM supervectors for speaker verification

3. Detecting Features in Spatial Point Processes with Clutter via Model-Based Clustering

4. Gaussian Mixture Models for Supervised Classification of Remote Sensing Multispectral Images

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