The roles of textural images in improving land-cover classification in the Brazilian Amazon-Reference-Cited by-同舟云学术

The roles of textural images in improving land-cover classification in the Brazilian Amazon

Published:2014-12-04 Issue:24 Volume:35 Page:8188-8207
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Lu Dengsheng¹²,Li Guiying²,Moran Emilio²,Dutra Luciano³,Batistella Mateus⁴

Affiliation:

1. Zhejiang Provincial Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration, School of Environmental & Resource Sciences, Zhejiang A&F University, Hangzhou, Zhejiang Province 311300, China

2. Center for Global Change and Earth Observations, Michigan State University, East Lansing, MI 48864, USA

3. National Institute for Space Research, São Jose dos Campos 12245-010, SP, Brazil

4. Embrapa Satellite Monitoring, Campinas 13088-300, SP, Brazil

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2014.980920

Reference41 articles.

1. Using texture analysis to improve per-pixel classification of very high resolution images for mapping plastic greenhouses

2. A review of vegetation indices

3. Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors

4. Examining the effect of spatial resolution and texture window size on classification accuracy: an urban environment case

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