Generating High-Quality and High-Resolution Seamless Satellite Imagery for Large-Scale Urban Regions
Urban geographical maps are important to urban planning, urban construction, land-use studies, disaster control and relief, touring and sightseeing, and so on. Satellite remote sensing images are the most important data source for urban geographical maps. However, for optical satellite remote sensin...
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doaj-299080603c3a4926b6a2128bec745e9d2020-11-25T00:34:40ZengMDPI AGRemote Sensing2072-42922019-12-011218110.3390/rs12010081rs12010081Generating High-Quality and High-Resolution Seamless Satellite Imagery for Large-Scale Urban RegionsXinghua Li0Zhiwei Li1Ruitao Feng2Shuang Luo3Chi Zhang4Menghui Jiang5Huanfeng Shen6School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, ChinaSchool of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, ChinaSchool of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, ChinaSchool of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, ChinaSchool of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, ChinaSchool of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, ChinaSchool of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, ChinaUrban geographical maps are important to urban planning, urban construction, land-use studies, disaster control and relief, touring and sightseeing, and so on. Satellite remote sensing images are the most important data source for urban geographical maps. However, for optical satellite remote sensing images with high spatial resolution, certain inevitable factors, including cloud, haze, and cloud shadow, severely degrade the image quality. Moreover, the geometrical and radiometric differences amongst multiple high-spatial-resolution images are difficult to eliminate. In this study, we propose a robust and efficient procedure for generating high-resolution and high-quality seamless satellite imagery for large-scale urban regions. This procedure consists of image registration, cloud detection, thin/thick cloud removal, pansharpening, and mosaicking processes. Methodologically, a spatially adaptive method considering the variation of atmospheric scattering, and a stepwise replacement method based on local moment matching are proposed for removing thin and thick clouds, respectively. The effectiveness is demonstrated by a successful case of generating a 0.91-m-resolution image of the main city zone in Nanning, Guangxi Zhuang Autonomous Region, China, using images obtained from the Chinese Beijing-2 and Gaofen-2 high-resolution satellites.https://www.mdpi.com/2072-4292/12/1/81cloud detection and removalhigh-quality and high-resolutionmosaickingpansharpeningremote sensing |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xinghua Li Zhiwei Li Ruitao Feng Shuang Luo Chi Zhang Menghui Jiang Huanfeng Shen |
spellingShingle |
Xinghua Li Zhiwei Li Ruitao Feng Shuang Luo Chi Zhang Menghui Jiang Huanfeng Shen Generating High-Quality and High-Resolution Seamless Satellite Imagery for Large-Scale Urban Regions Remote Sensing cloud detection and removal high-quality and high-resolution mosaicking pansharpening remote sensing |
author_facet |
Xinghua Li Zhiwei Li Ruitao Feng Shuang Luo Chi Zhang Menghui Jiang Huanfeng Shen |
author_sort |
Xinghua Li |
title |
Generating High-Quality and High-Resolution Seamless Satellite Imagery for Large-Scale Urban Regions |
title_short |
Generating High-Quality and High-Resolution Seamless Satellite Imagery for Large-Scale Urban Regions |
title_full |
Generating High-Quality and High-Resolution Seamless Satellite Imagery for Large-Scale Urban Regions |
title_fullStr |
Generating High-Quality and High-Resolution Seamless Satellite Imagery for Large-Scale Urban Regions |
title_full_unstemmed |
Generating High-Quality and High-Resolution Seamless Satellite Imagery for Large-Scale Urban Regions |
title_sort |
generating high-quality and high-resolution seamless satellite imagery for large-scale urban regions |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2019-12-01 |
description |
Urban geographical maps are important to urban planning, urban construction, land-use studies, disaster control and relief, touring and sightseeing, and so on. Satellite remote sensing images are the most important data source for urban geographical maps. However, for optical satellite remote sensing images with high spatial resolution, certain inevitable factors, including cloud, haze, and cloud shadow, severely degrade the image quality. Moreover, the geometrical and radiometric differences amongst multiple high-spatial-resolution images are difficult to eliminate. In this study, we propose a robust and efficient procedure for generating high-resolution and high-quality seamless satellite imagery for large-scale urban regions. This procedure consists of image registration, cloud detection, thin/thick cloud removal, pansharpening, and mosaicking processes. Methodologically, a spatially adaptive method considering the variation of atmospheric scattering, and a stepwise replacement method based on local moment matching are proposed for removing thin and thick clouds, respectively. The effectiveness is demonstrated by a successful case of generating a 0.91-m-resolution image of the main city zone in Nanning, Guangxi Zhuang Autonomous Region, China, using images obtained from the Chinese Beijing-2 and Gaofen-2 high-resolution satellites. |
topic |
cloud detection and removal high-quality and high-resolution mosaicking pansharpening remote sensing |
url |
https://www.mdpi.com/2072-4292/12/1/81 |
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