Implementation on Landsat Data of a Simple Cloud-Mask Algorithm Developed for MODIS Land Bands

This letter assesses the performance on Landsat-7 images of a modified version of a cloud-masking algorithm originally developed for clear-sky compositing of Moderate Resolution Imaging Spectroradiometer images at northern midlatitudes. While most historical Landsat data include measurements at thermal wavelengths and such measurements are also planned for the next mission, thermal tests are not included in the suggested algorithm in order to maintain greater versatility and ease of use. The evaluation of the masking algorithm takes advantage of the availability of manual (visual) cloud masks developed at the U.S. Geological Survey for a collection of Landsat scenes. As part of the evaluation, we also include the automated cloud cover assessment (ACCA) algorithm which does include thermal tests and is used operationally by the Landsat-7 mission to provide scene cloud fractions but no cloud masks. We show that the proposed algorithm performs on par with the ACCA both in terms of scene cloud fraction and pixel-level mask agreement. Specifically, the algorithm gives an error of 0.8% for the scene cloud fraction of 156 scenes and a root-mean-square error of 7.1%, while it agrees with the manual mask for 93.1% of the pixels. These performance indicators are very similar to those of the ACCA (1.2%, 7.1%, and 93.7%).