Weighted multiscale region-level sparse representation for classification of high-spatial resolution remote sensing images-Reference-Cited by-同舟云学术

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Weighted multiscale region-level sparse representation for classification of high-spatial resolution remote sensing images

Published:2018-10-13 Issue:04 Volume:12 Page:1
ISSN:1931-3195
Container-title:Journal of Applied Remote Sensing
language:
Short-container-title:J. Appl. Rem. Sens.

Author:

Chu Sensen¹,Hong Liang²,Cheng Liang¹,Du Peijun¹,Zong Wenwen¹

Affiliation:

1. Nanjing University, Jiangsu Provincial Key Laboratory of Geographic Information Science and Technolo

2. Yunnan Normal University, College of Tourism and Geography Science, Kunming

Publisher

SPIE-Intl Soc Optical Eng

Subject

General Earth and Planetary Sciences

Reference49 articles.

1. Mapping ephemeral stream networks in desert environments using very-high-spatial-resolution multispectral remote sensing

2. Measuring Detailed Urban Vegetation with Multisource High-Resolution Remote Sensing Imagery for Environmental Design and Planning

3. Object-oriented mapping of landslides using Random Forests

4. Automatic system for operational traffic monitoring using very-high-resolution satellite imagery

5. Intercomparison of UAV, Aircraft and Satellite Remote Sensing Platforms for Precision Viticulture

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