The Open Data Cubes in Mongolia and Kyrgyzstan

eOsphere have built two Data Cubes as a part of the SIBELIUs project. One in Mongolia and one in Kyrgyzstan, where in both cases satellite data from the Sentinel-2 and Landsat8 satellites is being used, in conjunction with lower resolution data from the satellites carrying the MODIS and VIIRS sensors. Output products, for example relating to pasture and snow, from the Data Cubes can be ingested by desktop applications, web apps and dashboard front ends for stakeholders to integrate into their workflows.

Data Cube statistics for Mongolia and Kyrgyzstan. Both Data Cubes are growing all the time as new satellite data is acquired and ingested, however, the Mongolian Data Cube will always be substantially larger than the one in Kyrgyzstan, because it is a much larger country.

Data Cubes provide an integrated gridded environment for storing large time series of satellite data and derived products, which can be efficiently accessed and queried, so environmental parameters can be monitored and analysed.

The Open Data Cube architecture, pioneered by Geoscience Australia and now its own development entity, has the stated aim of opening up access to analysis ready data (ARD) to a wider range of users. Once an Open Data Cube has been deployed covering a given geographical region, it allows for the rapid expansion in the use of satellite data, often including unforeseen applications that are stimulated once different user groups see what data and resultant information is available. This increase in capability is due to the structured deployment of satellite data within the Open Data Cube’s database which allows for the easy viewing of data both spatially and temporally. For example, allowing users to view data either over large areas of the Earth or stretching back into the past to gain an insight into how the environment has changed over time. Crucially, it allows a single system to be deployed that allows users to rapidly interrogate data across the different dimensions of the Cube, with minimal training required.

The Data Cubes in both Mongolia and Kyrgyzstan contain a mixture of lower and higher resolution data provided by the satellites listed above.

The main aim of the eOsphere Data Cube in Mongolia is to provide environmental information to be better prepared in the event of poor pasture conditions, which can have a big impact on the country’s herding community and the wider economy. During 2020 a large region in central Mongolia suffered from poor rainfall in the spring and early summer months, which led to substantially worse pasture compared to normal, which can be seen in the pasture anomaly image below highlighted in red.

Pasture anomaly in 2020 in Mongolia
The SIBELIUs Visualisation Website provides a simple means of accessing information from the Mongolian Data Cube. The large red region shows substantially worse pasture conditions in June 2020, compared to the average conditions for the same time of year, calculated from the mean of the previous 10 years of historical data.

Kyrgyzstan, like Mongolia, has a large population reliant on livestock herding, however, the main pasture problems are caused by a general degradation of pasture productivity and the intrusion of shrubs and bushes that are inedible by livestock. The Kyrgyz SIBELIUs Visualisation website provides access to pasture information in the Data Cube that can be used by governmental institutions and also by local officials and Pasture Committees.

Snow also plays an important role in the lives of rural communities in Kyrgyzstan. Melting snow in the mountains, provides irrigation in the spring and early summer months which is a critical time for agricultural crops as well as fodder, which is needed to feed the livestock through the winter months. Many herders in Kyrgyzstan are reporting that winter snowfall is becoming increasingly unreliable as a source of water, which is believed to be one of the impacts of our climate change.

Melting snow provides a large percentage of the water needed for herding. Many herders are reporting that lower levels of snow are leading to water shortages. The Kyrgyz Data Cube allows changes in snow patterns to be analysed and to derive information about current snow conditions, to help understand the likely availability of irrigation from melting snow.