IMG2HEIGHT: height estimation from single remote sensing image using a deep convolutional encoder-decoder network-Reference-Cited by-同舟云学术

IMG2HEIGHT: height estimation from single remote sensing image using a deep convolutional encoder-decoder network

Published:2023-09-11 Issue:18 Volume:44 Page:5686-5712
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Du Shouhang¹²,Xing Jianghe¹,Du Shihong³,Cui Ximin¹,Xiao Xiongwu⁴^ORCID,Li Wei¹,Wang Shaoyu¹

Affiliation:

1. College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing, China

2. Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities, MNR, Shanghai Surveying and Mapping Institute, Shanghai, China

3. Institute of Remote Sensing and GIS, Peking University, Beijing, China

4. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China

Funder

the National Natural Science Foundation of China

the China Postdoctoral Science Foundation

the Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2023.2251185

Reference42 articles.

1. 2D Image-To-3D Model: Knowledge-Based 3D Building Reconstruction (3DBR) Using Single Aerial Images and Convolutional Neural Networks (CNNs)

2. Height estimation from single aerial images using a deep convolutional encoder-decoder network

3. Spatio-temporal analysis of the relationship between 2D/3D urban site characteristics and land surface temperature

4. DSM-to-LoD2: Spaceborne Stereo Digital Surface Model Refinement

5. Large-scale parameterization of 3D building morphology in complex urban landscapes using aerial LiDAR and city administrative data

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