Publication Date:
2019
Description:
Abstract
Clouds and shadows pose a significant barrier for land surface optical and infrared remote sensing image processing and their various applications. The detection and removal of clouds and shadows from satellite images have always been critical preprocessing steps. To date, a variety of methods have been designed to solve this problem. Some require particular channels, while others are heavily dependent on the availability of temporally adjacent images (reference images). Moreover, many methods are too complex to use by common users. For those reasons, in this paper an alternative scheme for detecting clouds and shadows is proposed based on simulated TOA radiance fields. At the same time, a simple approach to remove clouds and shadows is also provided. The results indicate that the new method can properly identify both clouds and shadows in satellite images. Especially, it shows obvious advantage over the MODIS cloud product (MOD35) for shadow detection. Although the proposed cloud removal method is simple, the radiances of a contaminated image can be reasonably reconstructed with RMSE 〈3.0 W/m2 ⋅ sr ⋅ μm and MBE (mean bias) 〈1.0 W/m2 ⋅ sr ⋅ μm for all seven MODIS reflective bands for our case studies. These results prove the effectiveness of the proposed scheme in identifying and removing clouds and shadows from remotely sensed images. Meanwhile, these findings provide some new ideas for the remote sensing community, especially in the fields of cloud detection and image processing.
Print ISSN:
2169-897X
Electronic ISSN:
2169-8996
Topics:
Geosciences
,
Physics
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