Remote sensing workflows often contain tasks that are well understood, but still require specialist knowledge and analyst time to perform. Water masking is a good example. Identifying water in satellite imagery is not a new problem. Experienced remote-sensing analysts have several established ways of approaching it. But producing a useful result can still involve image
Overview GNSS interference can change rapidly. Understanding the operating environment therefore requires more than identifying where GNSS quality is currently degraded. Analysts also need to understand when conditions changed, how quickly they changed, and how those changes developed geographically over time. Using Atlas, a change in GNSS quality was observed in a cell on the
Case Study: Tracking Developing GNSS Degradation in the Caspian Region Read More »
Overview Modern aircraft tracking relies heavily on ADS-B position reports, delivering unprecedented visibility across the globe through satellite-based surveillance networks. However, in regions where GNSS performance may be degraded or where navigation environments become more challenging, analysts often need additional tools to assess the reliability of reported aircraft positions. This case study demonstrates how Atlas,
The Atlas approach Analysts first used Atlas to review aircraft operating within the area of interest. Three aircraft were identified for further examination. Using the Aircraft Details page, analysts reviewed: ADS-B signal quality indicators VECTOR-derived positioning Historical aircraft behaviour Recent flight activity The analysis quickly showed that only one of the three aircraft was reporting
Case Study: Investigating Suspected GNSS Degradation Read More »
The project translated crop management, climate and soil data into a scalable soil carbon baseline, giving the client transparent, field-scale visibility to support emissions reporting and net-zero commitments.
Field-Level Soil Carbon Insight Across a Global Grower Network Read More »
By combining high-resolution satellite time series with soil, forest and peat datasets, the assessment delivers a GHG Protocol-aligned emissions baseline that supply chains can use for climate reporting, risk assessment and sourcing decisions.
Decoding Deforestation Risk Across Global Commodity Supply Chains Read More »
A 20-plus year spatially explicit emissions baseline for palm oil sourcing across Southeast Asia, built by integrating traceability data, concession boundaries and satellite-derived land cover change back to 2001.
Benchmarking Supplier Emissions Across the Palm Oil Value Chain Read More »
A geospatial intelligence case study showcasing how OSINT and satellite imagery were used to identify non-compliant livestock sites, improving biosecurity monitoring, traceability, and targeted intervention across Australia’s agricultural sector.
Detecting Biosecurity Gaps in Australia’s Livestock Sector Read More »
A geospatial carbon accounting study mapped carbon storage and sequestration potential across Cape Cod, helping guide conservation, climate mitigation, and long-term regional resilience planning.
Spatial Carbon Accounting for Smarter Climate Action Read More »
Remote sensing and machine learning enabled scalable detection of invasive weeds across mine closure sites, improving rehabilitation monitoring and environmental management.
Remote Sensing Weed Detection for Mine Site Rehabilitation Read More »
