Abstract
Abstract. Cloud shadow detection is one of the basic step for remote sensing image processing. The threshold method is commonly used currently because of its easy implementation and good accuracy. Aiming at the problems that common threshold settings are difficult to meet the complex surface conditions and the results is two-value, this paper proposes a detection method of cloud shadow pixels based on land cover data support by calculating shadow probabilities using Landsat 8 data as an example. Then, a validation with visual interpretation is used to verify the accuracy. The results show that the method can achieve high cloud shadow detection results.
Highlights
The existence of cloud shadows on remote sensing images can cause wrong expression of the original surface information, which makes the qualitative and quantitative results inaccurate
This paper proposes a detection method of cloud shadow pixels based on land cover data support using spectral characteristic differences between cloud shadow and clear land
Aiming at the problem that traditional threshold method cannot adapt to complex surface conditions, land type data and Cloud Shadow & Clear Land (CSCL) pixel database are added as references in this paper, so that the threshold can be set according to different situations
Summary
The existence of cloud shadows on remote sensing images can cause wrong expression of the original surface information, which makes the qualitative and quantitative results inaccurate. Threshold method of shadow detection is commonly used because of its easy implementation and good accuracy. It is based on the difference between cloud shadow and typical underlying surface spectrum to identify the cloud shadow pixels (Shahtahmassebi et al, 2013). The result of traditional methods is two-value result (cloud shadow or clear land). The support of prior data can better improve the accuracy (Tian et al, 2018) To solve these problems, this paper proposes a detection method of cloud shadow pixels based on land cover data support using spectral characteristic differences between cloud shadow and clear land. The results show that the method can achieve high cloud shadow detection results
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
