Improving super-resolution mapping through combining multiple super-resolution land-cover maps-Reference-Cited by-同舟云学术

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Improving super-resolution mapping through combining multiple super-resolution land-cover maps

Published:2016-05-06 Issue:10 Volume:37 Page:2415-2432
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Li Xiaodong,Ling Feng,Foody Giles M.,Du Yun

Funder

Wuhan ChenGuang Youth Sci.&Tech. Project

key project from Institute of Geodesy and Geophysics

Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

http://www.tandfonline.com/doi/pdf/10.1080/01431161.2016.1148288

Reference33 articles.

1. Sub-pixel Target Mapping from Soft-classified, Remotely Sensed Imagery

2. Issues of uncertainty in super-resolution mapping and their implications for the design of an inter-comparison study

3. Multisource remote sensing data classification based on consensus and pruning

4. Multiple classifiers applied to multisource remote sensing data

5. Detection of land-cover transitions by combining multidate classifiers

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2. A Single-Image Noise Estimation Algorithm Based on Pixel-Level Low-Rank Low-Texture Patch and Principal Component Analysis;Sensors;2022-11-17

3. Combining Pixel Swapping and Simulated Annealing for Land Cover Mapping;Sensors;2020-03-09

4. Super-Resolution Land Cover Mapping Based on the Convolutional Neural Network;Remote Sensing;2019-08-02

5. Land-cover classification from multiple classifiers using decision fusion based on the probabilistic graphical model;International Journal of Remote Sensing;2019-01-25

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