Landsat 7 Automatic Cloud Cover Assessment.pdfVIP

Landsat 7 Automatic Cloud Cover Assessment Richard R. Irish• Science Systems and Applications, Inc. NASA’s Goddard Space Flight Center, Greenbelt, Maryland ABSTRACT An automatic cloud cover assessment algorithm was developed for the Landsat 7 ground system. A scene dependent approach that employs two passes through ETM+ data was developed. In pass one, the reflective and thermal properties of scene features are used to establish the presence or absence of clouds in a scene. If present, a scene-specific thermal profile for clouds is established. In pass two, a unique thermal signature for clouds is developed and used to identify the remaining clouds in a scene. The algorithm appears to be a good cloud discriminator for most areas of the Earth. Some difficulty has appeared in imagery over Antarctica, and snow at high illumination angles is occasionally mistaken for cloud. Keywords: Landsat, ETM+, clouds, classification, ACCA, algorithm 1. INTRODUCTION A primary goal of the Landsat 7 mission is to provide a global seasonal archive of cloud-free imagery over the Earth’s landmasses. To achieve this goal, 250 images or scenes are acquired each day by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and archived. Mission success is determined by the cloud-free nature of each scene acquired. An automatic cloud cover assessment (ACCA) algorithm was deployed for ascertaining the cloud component of each ETM+ image prior to archiving. The resulting cloud cover assessment scores are subsequently used by mission planners to reschedule failed acquisitions, and by users to filter cloudy scenes from database queries. Discerning clouds from underlying terrain seems intuitively straightforward.