Cloud Detection for DSCOVR EPIC Data

Abstract

The cloud covers most of the Earth's space and plays an important role in the Earth's energy balance. Moreover, the cloud is one of the most vital and active factors in the weather and climate. In addition, the cloud usually covers ground information, which causes many problems and difficulties in the processing of image registration and fusion. So cloud detection is very significant and necessary. DSCOVR (deep space climate observatory) satellite was launched in 2015. The new EPIC (earth polychromatic imaging camera) data from it has some special characteristics, such as the hemisphere scale and the wide range of band spectrum (from ultraviolet bands, visible bands to infrared bands). Hence, we propose a new cloud detection method for EPIC data in the way of normalized difference cloud index (NDCI). In our method, first, we analyze the different reflection characteristics of different bands, especially the new ultraviolet bands, and select appropriate bands to detect clouds. Combined with the applications of EPIC data bands, 340nm, 388nm, 680nm and 780nm are identified as the main research bands. Secondly, we analyze the reflection characteristics of clouds including thin clouds and residual clouds. Based on the above two aspects, we define the cloud index (CI) to detect clouds, which effectively reduces the influence of underlying surface on the cloud detection results. In order to verify the effectiveness of the proposed cloud detection method, other three cloud detection methods are compared, including the visible light cloud detection method, SVM cloud detection method and traditional NDCI cloud detection method. The experimental results show that our proposed method effectively detects thin clouds and residual clouds that are not detected by other methods, even in winter and in summer.