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Article summary:
1. Discrimination between cloudy and clear-sky areas is an important issue for satellite remote sensing, as clouds have a large impact on radiance.
2. Cloud detection algorithms must be able to deal with all types of cloud and surface, using many wavelengths.
3. Many algorithms have been proposed to improve the usefulness of cloud detection, such as MOD35, CLAVR1, APOLLO, and Di Vittorio and Emery's method.
Article analysis:
The article “Development of an Unbiased Cloud Detection Algorithm for a Spaceborne Multispectral Imager” by Ishida (2009) provides an overview of existing methods for cloud detection in satellite observations. The article is well-written and provides a comprehensive overview of the various methods that have been developed for this purpose. The author has provided sufficient evidence to support their claims and has presented both sides of the argument equally.
However, there are some potential biases in the article that should be noted. For example, the author does not discuss any potential risks associated with using these methods or any possible limitations that may arise from using them. Additionally, while the author does provide evidence to support their claims, they do not explore any counterarguments or alternative perspectives on the topic which could provide further insight into the issue at hand.
In conclusion, while this article provides a comprehensive overview of existing methods for cloud detection in satellite observations, it does not explore any potential risks or alternative perspectives which could provide further insight into this topic.