Title :
A sensor-based scheme for assessing cloud coverage in HJ-1 CCD data
Author :
Dacheng Li ; Ping Tang
Author_Institution :
Inst. of Remote Sensing & Digital Earth, Beijing, China
Abstract :
Currently, most of the effective cloud detection algorithms utilize either temperature properties or reference image(s). Typically, the automatic cloud cover assessment (ACCA) algorithm for Landsat 7 ETM+ images detects cloudy pixels relying on the thermal channel (three times used in two passes). In another study, Fernando flags clouds through analyzing the reflectance distribution between the high resolution cloudy image and a reference cloud-free MODIS image. However, for those sensors whose thermal channels are absent, less achievement has been obtained when no reference image can be acquired. In this paper, we develop a sensor-based cloud detection scheme for HJ-1 CCD data. HJ-1 (A/B) satellite (the environment and disaster monitoring and forecasting small satellites) is an optical satellite which covers a 720 square km area and consists of four visible and near-infrared spectral bands with 30 m resolution, and has been applied in land use and disaster detection.
Keywords :
atmospheric temperature; clouds; disasters; environmental monitoring (geophysics); land use; radiometry; remote sensing; ACCA algorithm; Fernando flag clouds; HJ-1 A-B satellite; HJ-1 CCD data; Landsat 7 ETM+ images; automatic cloud cover assessment algorithm; cloud coverage assessment; cloudy pixel detection; disaster detection; disaster monitoring; effective cloud detection algorithms; environment monitoring; high resolution cloudy image; land use; near-infrared spectral band; optical satellite; reference cloud-free MODIS image; reference image; reflectance distribution; sensor-based cloud detection scheme; sensor-based scheme; small satellite forecasting; temperature properties; thermal channel; visible spectral band; Brightness; Charge coupled devices; Clouds; Earth; Remote sensing; Satellites; Sensors; ACCA algorithm; Cloud detection; HJ-1-A/B; multi-image method; sensor-based;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4799-1114-1
DOI :
10.1109/IGARSS.2013.6721218