Satellite Earth observation can provide information from which actions can be taken to protect lives and livelihoods. eOsphere has provided satellite solutions around the world that are being used to trigger alerts and responses to emergencies such as forest and wildfires, coastline protection, drought preparedness and climate change resilience. The increasing number of satellites, including many where the data is freely accessible, have expanded the opportunities for understanding our environment and warning us of impending risks. However, increasingly large volumes of satellite data can present significant challenges.

eOsphere have many years’ experience building systems that process satellite data into products ready to use in Geographical Information Systems (GIS). Typically this includes the provision of systems for handling large data volumes, extracting useful information from data, image visualisation systems and the generation and distribution of clear products which allow the best possible decisions to be made.

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 the 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.

eOsphere have built two Data Cubes as a part of the SIBELIUs project. One in Mongolia and one in Kyrgyzstan, wherein 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. The products from these systems are being served to stakeholders via web applications for further analysis and to support their operations. Output products, for example relating to pasture and snow, from the Data Cube can be ingested by desktop applications, web apps and dashboard front ends for stakeholders to integrate into their workflows.

eOsphere has many years of experience in processing satellite data so that it is ready for end-users to use in their GIS systems. It is quite common for those not familiar with satellite imagery to underestimate how time-consuming this process can be. eOsphere has worked with many institutions, completing these processing chains, which enables experts to get on with their job of interpreting the information contained within the data, without having to worry about the proceeding stages.

Recently the concept of Analysis Ready Data (ARD) has been devised which provides a common standard for processors to follow so that different end users can use data processed through different chains. eOsphere has adopted the ARD standard in much of its work, including the SIBELIUs projects in Mongolia and Kyrgyzstan.

The main data steps in the ARD processing chain used by eOsphere are:

1. Download Level-1 terrain corrected data and provide an initial quality assessment. Or if data is being received from an eOsphere ground receiving station, first convert the Level 0 raw binary data to Level 1.
2. Convert the imagery from satellite digital numbers to radiance.
3. Convert the imagery to top-of-atmosphere (TOA) reflectance.
4. Atmospheric/topographic correction, which is the elimination of atmospheric and illumination effects to retrieve physical parameters of the Earth’s surface, i.e., the retrieval of surface spectral reflectance.
5. Produce cloud, haze and snow masks.
6. Calculate surface emissivity and surface (brightness) temperature outputs for thermal band sensors.
   
   

Finally, the image is considered an Analysis Ready Dataset.

eOsphere has many years of experience developing dashboards and visualisation systems tailored to meet customers’ requirements. These dashboards allow users to easily and quickly interact with satellite data such that they can quickly understand and interpret the information of the derived products and make informed, actionable decisions.

For eOsphere ground station installations, we include a fully-featured visualisation system for the display of satellite imagery and products, along with tools for re-projection, re-sampling, aggregation, re-formatting and delivery of products.

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