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 »
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 »
Geospatial Intelligence conducted a remote sensing assessment for an Australian orchard to identify unhealthy or damaged trees at scale. Using satellite imagery and NDVI analysis, the project produced a detailed tree health classification map, accuracy report, and geospatial outputs for operational use. The insights allow the orchard to detect issues earlier, improve decision making, and support long term productivity and orchard health.
Orchard Management Using Satellite-Based Tree Health Detection Read More »
Remote sensing using EO and SAR imagery enabled accurate monitoring of drill pads, subsidence, and site activity across a large Australian mining operation, improving safety and compliance.
Monitoring Mine Site Integrity with EO and SAR Remote Sensing Read More »
