Sensing Population Distribution from Satellite Imagery Via Deep Learning:Model Selection, Neighboring Effects, and Systematic Biases

Sensing Population Distribution from Satellite Imagery Via Deep Learning:Model Selection, Neighboring Effects, and Systematic Biases

The rapid development of remote sensing techniques provides rich, large-coverage, and high-temporal information of the ground, which can be coupled with the emerging deep learning approaches that enable latent features and hidden geographical patterns to be extracted. This article marks the first at...

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Bibliographic Details
Main Authors: Xiao Huang, Di Zhu, Fan Zhang, Tao Liu, Xiao Li, Lei Zou
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Deep learning
end-to-end architecture
population estimation
satellite imagery
systematic biases
Online Access:https://ieeexplore.ieee.org/document/9419720/

Internet

https://ieeexplore.ieee.org/document/9419720/

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