Landsat scene- and pixel-based cloud cover research: a review - Yin Yang; Peng Li; Arun Jyoti Nath; Zhiming Feng; Zhen Xiao; Jing Yang (International Journal of Digital Earth)
Clouds present a difficulty for optical remote sensing and a variable in regional climate change assessments. The likelihood of acquiring imagery under different cloud cover is crucial for assessing Landsat's capacity to investigate environmental change on varied scales. The Landsat data archive enables comprehensive analyses of cloud cover dynamics, image acquisition probability, and their relationship to climate change. However, thematic reviews that concentrate on the spatiotemporal dynamics and mechanisms of cloud cover change are notably lacking. The research on cloud cover and image acquisition probability at the scene and pixel levels was reviewed, along with its shortcomings, using dozens of journal articles published since 1990. Correlation analysis with biophysical factors was then reviewed, and future pixel-level research on the cloud-climate nexus was prospected. Our findings demonstrate a shift toward a pixel-based paradigm from scene-based collection probabilities studies at particular cloud coverage levels. However, techniques for figuring out these thresholds in image acquisition studies are still lacking. Previous research has focused mostly on cloud-free analysis, with relatively little attention paid to pixel-based cloud occurrence. Future research is expected to concentrate on the dynamics and mechanisms of cloud cover from the perspectives of atmospheric aerosol composition, atmospheric circulation, and climate systems.