Acquisition probability differences in cloud coverage of the available Landsat observations over mainland Southeast Asia from 1986 to 2015

• Published in: International journal of digital earth 2018-05, Vol.11 (5), p.437-450
• Main Authors: Li, Peng, Feng, Zhiming, Xiao, Chiwei
• Format: Article
• Language: English
• Subjects: acquisition probability (AP); Cloud cover; cloud coverage (CC); Clouds; Dry season; Geological surveys; Image acquisition; Image enhancement; Image quality; Imagery; Land cover; land cover and land use changes; Landsat; Landsat satellites; mainland Southeast Asia; Probability; Probability theory; Rainy season; Remote sensing; Satellite imagery; Satellite observation; Seasons; Statistical methods; Surveying; Temporal distribution; Thresholds; Tropical environments; Wet season
• ISSN: 1753-8947; 1753-8955
• DOI: 10.1080/17538947.2017.1327619

Landsat data are the longest available records that consistently document global change. However, the extent and degree of cloud coverage typically determine its usability, especially in the tropics. In this study, scene-based metadata from the U.S. Geological Survey Landsat inventories, ten-day, monthly, seasonal, and annual acquisition probabilities (AP) of targeted images at various cloud coverage thresholds (10% to 100%) were statistically analyzed using available Landsat TM, ETM+, and OLI observations over mainland Southeast Asia (MSEA) from 1986 to 2015. Four significant results were found. First, the cumulative average acquisition probability of available Landsat observations over MSEA at the 30% cloud cover (CC) threshold was approximately 41.05%. Second, monthly and ten-day level probability statistics for the 30% CC threshold coincide with the temporal distribution of the dry and rainy seasons. This demonstrates that Landsat images acquired during the dry season satisfy the requirements needed for land cover monitoring. Third, differences in acquisition probabilities at the 30% CC threshold are different between the western and eastern regions of MSEA. Finally, the ability of TM, ETM+, and OLI to acquire high-quality imagery has gradually enhanced over time, especially during the dry season, along with consequently larger probabilities at lower CC thresholds.