Abstract
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.
Highlights
The generation of a high-quality seamless urban geographical map is significant for urban land-use mapping and urban land planning [1,2,3,4]
On the basis of the above analysis, we propose a luminance-based atmospheric light estimation strategy, entitles the non-uniform atmospheric light model
In the registration proposed procedure, a series of that steps are utilized to achieve in image and is of critical importance for multi-temporal thick cloud and shadow removal, as well as image quality and spatial resolution
Summary
The generation of a high-quality seamless urban geographical map is significant for urban land-use mapping and urban land planning [1,2,3,4]. High-spatial-resolution images (HRIs) from satellite remote sensing platforms are required for precise urban mapping. Small satellites can be further netted as distributed constellations which facilitate the acquisition of high-spatial-resolution remote sensing images with a high imaging quality and short revisit cycle. Several issues must be considered during urban image generation with small satellite HRIs, such as Beijing-2, as Remote Sens. 2020, 12, 81; doi:10.3390/rs12010081 www.mdpi.com/journal/remotesensing quality seamless urban image a challenging task. The swath width of images is usually reduced with an increase in spatial resolution
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