Data from MOYDGL06*: The image shows the difference between original and improved data. Red indicates overestimation of snow in the original data, rectified by the improved data. Similarly, yellow markings indicate underestimation of snow cover area, newly identified by the improved data. The product makes it possible for scientists to get accurate measurements of snow cover in the HKH.

Snow is a significant component of the ecosystem and water resources in the Hindu Kush Himalaya (HKH). Snow monitoring is therefore a crucial component for water resource management and economic development. However, it is not possible to carry out field-based measurement for snow cover area due to its vast area coverage, so remote-sensing data are widely used for mapping and monitoring snow cover extent across the globe.

This is where Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover data are instrumental in understanding snow cover change and trends; it allows climate scientists to examine and scrutinize changes in snow cover and the influence of climate change. Using Terra and Aqua MODIS snow cover data, ICIMOD scientists have developed a new method to improve interpretation of snow cover data in the region that for the first time allows users and researchers to better understand snow dynamics. This is presented in an article published on Earth System Science Data. The article also shows that use of this modified application improves the interpretation of snow cover data, greatly reducing chances of overestimation of snow cover area (since snow and cloud appear similar in satellite images), which used to be the main issue in the original snow cover data readings.

The methodology uses satellite images from Terra and Aqua MODIS eight-day snow cover combined with Randolph Glacier Inventory (RGI) for the HKH and allows further scrutiny to validate and improve data accuracy by 50%. It uses a multi-step approach – seasonal, temporal, and spatial filters to remove underestimation and combining aqua and terra snow cover products to reduce overestimation. The final result is 99.98% cloud-free, reducing 46% overestimation and 3.66% underestimation.

With the release of this product – called MOYDGL06* – it is now possible for scientists to get accurate measurements of snow cover in the HKH. It could have wider applications as well.

The improved snow data for High Mountain Asia covers the MODIS observation period between 2002 and 2018. The product is available for free download on ICIMOD’s Regional Database System. The authors – Sher Muhammad, Remote Sensing Specialist, and Amrit Thapa, RS & Geoinformation Research Analyst – believe that the products can be used as a standard reference by those working in hydrology, hydro-glaciology, or any study on the High Mountain Asia requiring snow or glaciers as input data.