The satellites and sensors from which we derive Earth observation (EO) data provide a unique perspective to understand our world. They have the ability to isolate and record key information that can help us understand both human endeavour and environmental impact in new and insightful ways.
EO encompasses a wide range of data from sensors on satellites, planes, drones and ground-based sensors and networks.
At Xerra we leverage the world-class capabilities of our team and robust algorithms to automatically generate insight and information from EO data. This allows us to create accurate, repeatable analyses that can inform high-quality decision making across regional industry, businesses and government.
With the proliferation of smart materials being manufactured into sensors and the falling costs of building and launching satellites, the pool of data we can draw on is bigger than at any other time in human history.
In combination, remote sensors are capable of recording a comprehensive and cumulative data set, documenting subtle changes in chemical composition, temperature, moisture, altitude and colour of the Earth’s surface — which when analysed by scientists and researchers create precisely identifiable signatures.
The real power of EO comes from these multiple perspectives. Rather than analysing a single point of view, or just one set of images from a solitary sensor over time, we can combine and layer the outputs from a range of sensors. This layering gives us an accurate and more holistic picture — one that is ordinarily invisible or incomprehensible to the naked eye.
Due to EO having such broad applications and depth to its analysis, it can be difficult at times to summarise. As such, we break it into four categories: Selection and Processing; Identification; Change Detection; and Insight Generation.
Selection and Processing
While there has been an exponential increase in the volume of EO data, it is often only available in formats that require a high level of familiarity and expertise in order to identify the best data for an intended task.
Xerra can help source and select the EO data that best suits your needs, and optimise the information to make it accessible for non-specialists or further intensive analysis.
Access to a wide variety of EO satellite sensors give our scientists and researchers the ability to identify everything from the chemical composition of soil, to the moisture content in plants.
We do this by matching the target of interest with its relevant characteristics (as captured by the remote sensor) and refining the sensor output through specialised processing and analysis.
This work can range from optical identification (from an image similar to a photograph) through to identification using wavelengths not visible to the human eye (e.g. thermal, multispectral, hyperspectral, etc.).
Once the target is manually identified we use machine learning and other technologies to mine a broader dataset, automate identification and catalogue similar targets.
One of the most powerful applications of EO data is change detection.
Once our scientists and researchers have identified a target using a specific sensor signature, we can then track large data sets over time to identify historical trends or changes in near real time.
This can be applicable to anything from monitoring crop growth to sea vessel tracking and logistics.
After completing an initial EO data analysis, such as identification and/or change detection, we can distill the findings into actionable information.
The delivery of this information is designed to meet the specific needs of the recipient, in a timely and easily-digestible manner. This information is often called ‘EO insights’, as it provides decision-makers with evidence for understanding and addressing a given challenge.
This pool of EO insights can then be combined with new data from other sources, and be used to generate predictive models.
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