Removal of Commission Error from MCD10A1 in Iran

Document Type : Research Paper

Author

Professor of Climatology, Faculty of Geographical Sciences, Isfahan University, Isfahan, Iran

Abstract

Life in Iran and Iranian civilization depend on mountain snow reservoirs. Knowing about the status and changes of these snow reservoirs is a need that does not require a conversation. With the global warming and the destruction of these snow reservoirs, the Iranian civilization is going to shut down. Remote sensing is a cheap and fast way to achieve this knowledge. However, snow detection algorithms erroneously report snow-like features that have similar spectral characteristics to snow (such as salt pans) as snow (commission error). In Iran, due to the abundance of bright surfaces (salt flats, reservoirs, the bed of ancient lakes, etc.), frequency of commission error is very high. In this research, about 21 years of data of the Normalized Difference Snow Index (NDSI) of MODIS Aqua and Terra were used in order to remove the commission error. A principal component analysis was performed on the array of daily long-term mean NDSI ​​of 23,960 pixels from snow reservoirs and snow-like surfaces with dimensions of 23,960 x 365. This study showed that the seasonality of snow cover in Iran, in contrast to the continuous brightness of snow-like surfaces throughout the year, can make a basis for removing commission error. On the snow reservoirs, the NDSI is great only during the snow season, i.e. the cold period of the year, but on the snow-like areas, NDSI is great throughout the year. This feature is so prominent that the first principal component distinguished these two areas from each other.

Keywords

Main Subjects

References

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Geography and Development
Volume 24, Issue 82 - Serial Number 82
January 2026
Pages 177-192

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History

  • Receive Date: 12 November 2024
  • Revise Date: 05 April 2025
  • Accept Date: 07 April 2025

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