Systematic land cover bias in Collection 5 MODIS cloud mask and derived products — A global overview

• Published in: Remote sensing of environment Vol. 141; pp. 149 - 154
• Main Authors: Wilson, Adam M., Parmentier, Benoit, Jetz, Walter
• Format: Journal Article
• Language: English
• Published: New York, NY Elsevier Inc 05-02-2014; Elsevier
• Subjects: Animal, plant and microbial ecology; Applied geophysics; Bias; Biological and medical sciences; Cloud detection; Earth sciences; Earth, ocean, space; Exact sciences and technology; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; Internal geophysics; Land cover; Land surface temperature; MODIS; Net primary productivity; Teledetection and vegetation maps; Validation; Cloud detection; Validation; Bias; Land surface temperature; Land cover; Net primary productivity; MODIS; algorithms; Spatial variability; Space remote sensing; satellite measurements; remote sensing; clouds; interferences; frequency; grasslands; collections; savanna; Environment; Plant cover; land cover; albedo; Reflectance
• ISSN: 0034-4257; 1879-0704
• DOI: 10.1016/j.rse.2013.10.025

Identifying cloud interference in satellite-derived data is a critical step toward developing useful remotely sensed products. Most MODIS land products use a combination of the MODIS (MOD35) cloud mask and the ‘internal’ cloud mask of the surface reflectance product (MOD09) to mask clouds, but there has been little discussion of how these masks differ globally. We calculated global mean cloud frequency for both products, for 2009, and found that inflated proportions of observations were flagged as cloudy in the Collection 5 MOD35 product. These erroneously categorized areas were spatially and environmentally non-random and usually occurred over high-albedo land cover types (such as grassland and savanna) in several regions around the world. Additionally, we found that spatial variability in the processing path applied in the Collection 5 MOD35 algorithm affects the likelihood of a cloudy observation by up to 20% in some areas. These factors result in abrupt transitions in recorded cloud frequency across land cover and processing-path boundaries impeding their use for fine-scale spatially contiguous modeling applications. We show that together, these artifacts have resulted in significantly decreased and spatially biased data availability for Collection 5 MOD35-derived composite MODIS land products such as land surface temperature (MOD11) and net primary productivity (MOD17). Finally, we compare our results to mean cloud frequency in the new Collection 6 MOD35 product, and find that land cover artifacts have been reduced but not eliminated. Collection 6 thus increases data availability for some regions and land cover types in MOD35-derived products but practitioners need to consider how the remaining artifacts might affect their analysis.
•Collection 5 MODIS cloud mask (MOD35) inflates cloud frequency.•This bias reduces available data in derived MODIS products such as NPP and LST.•The Collection 6 MODIS cloud mask reduces, but does not eliminate, this bias.