A Method for Fully Automatic Building Footprint Extraction From Remote Sensing Images-Reference-Cited by-同舟云学术

A Method for Fully Automatic Building Footprint Extraction From Remote Sensing Images

Published:2022-07-04 Issue:4 Volume:48 Page:520-533
ISSN:0703-8992
Container-title:Canadian Journal of Remote Sensing
language:en
Short-container-title:Canadian Journal of Remote Sensing

Author:

Xiong John¹,Chen Ting²,Wang Minjie¹,He Jianjun²,Wang Lanying¹,Wang Zhiyong²

Affiliation:

1. 21AT North America R&D Ltd, Markham, ON, L3R 9T8, Canada

2. Twenty First Century Aerospace Technology Co., Ltd, Beijing, 100096, China

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/07038992.2022.2103397

Reference27 articles.

1. A Framework for Automatic Building Detection from Low-Contrast Satellite Images

2. Aravinth, R., Prakasam, C., and Sanjeevi Prasad, S. 2017. “Building footprint extraction from high resolution remote sensing data- a case study On Ayyappankovil, Elappara and Upputhara Villages (Idukki District, Kerala)”. https://a-a-r-s.org › proceeding › ACRS2017.

3. Bachofer, F., and Hochschild, V. 2015. “A SVM-based approach to extract building footprints from pléiades satellite imagery”. International conference on “geospatial technologies for sustainable urban and rural development,” Kigali, Rwanda, November 2015.

4. Building Footprint Extraction From VHR Remote Sensing Images Combined With Normalized DSMs Using Fused Fully Convolutional Networks

5. EXTRACTION OF BUILT-UP AREAS USING CONVOLUTIONAL NEURAL NETWORKS AND TRANSFER LEARNING FROM SENTINEL-2 SATELLITE IMAGES

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