Automated detection of impervious surfaces using night-time light and Landsat images based on an iterative classification framework-Reference-Cited by-同舟云学术

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Automated detection of impervious surfaces using night-time light and Landsat images based on an iterative classification framework

Published:2020-02-25 Issue:5 Volume:11 Page:465-474
ISSN:2150-704X
Container-title:Remote Sensing Letters
language:en
Short-container-title:Remote Sensing Letters

Author:

Cheng Xi¹,Luo Rui¹,Shi Guozhong²,Xia Liegang³,Shen Zhanfeng⁴

Affiliation:

1. School of Geophysics, Chengdu University Of Technology, Chengdu, China

2. Key Laboratory of Development and Application of Rural Renewable Energy, Ministry of Agriculture, Chengdu, China

3. School of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China

4. Institute of Remote Sensing and Digital Earth, Chinese Academy of Science, Bejing, China

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,Earth and Planetary Sciences (miscellaneous)

Link

https://www.tandfonline.com/doi/pdf/10.1080/2150704X.2020.1730471

Reference18 articles.

1. Impervious Surface Coverage: The Emergence of a Key Environmental Indicator

2. Chen, Jun, Jin Chen, Anping Liao, Xin Cao, Lijun Chen, Xuehong Chen, and He Chaoying, et al. 2015. “Global Land Cover Mapping at 30 m Resolution: A POK-Based Operational Approach.” ISPRS Journal of Photogrammetry and Remote Sensing 103. International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS): 7–27. doi: 10.1016/j.isprsjprs.2014.09.002.

3. Large-area assessment of impervious surface based on integrated analysis of single-date Landsat-7 images and geospatial vector data

4. Finer resolution observation and monitoring of global land cover: first mapping results with Landsat TM and ETM+ data

5. Improving the normalized difference built-up index to map urban built-up areas using a semiautomatic segmentation approach

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1. A general and simple automated impervious surface mapping approach based on three-dimensional texture features (3DTF) using fine spatial resolution remotely sensed imagery;Science of The Total Environment;2024-05

2. Extraction of Impervious Surface from High-Resolution Remote Sensing Images Based on a Lightweight Convolutional Neural Network;Wireless Communications and Mobile Computing;2022-08-28

3. Using Wavelet Transforms to Fuse Nighttime Light Data and POI Big Data to Extract Urban Built-Up Areas;Remote Sensing;2020-11-27

4. The spatial integration and coordinated industrial development of urban agglomerations in the Yangtze River Economic Belt, China;Cities;2020-09

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