Rainforest and peatland fire monitoring
Quickly detect hotspots with high-orbit satellites, assess burned areas with low-orbit satellites and help investigate smoldering peat fires.
Southeast Asia
Regional monitoring for tropical forests, plantations, severe weather and coastal change.
Applications
Oil palm plantation monitoring
Monitor plantation area, crop growth and deforestation with satellites to support certification and compliance reviews.
Natural rubber plantation monitoring
Combine optical and SAR satellites to monitor rubber tree growth and support yield estimates.
Typhoon and heavy-rainfall flood monitoring
Track typhoon rainfall with satellites, map flooded areas with SAR and use drones for emergency mapping.
Illegal logging and deforestation monitoring
Identify logging and deforestation with satellite imagery and use drones to verify findings and collect evidence.
Coastal city subsidence monitoring
Use time-series InSAR to monitor subsidence in coastal cities and support disaster prevention planning.
Coastal erosion and sea-level rise impacts
Monitor shoreline and sea-level changes with satellites to assess erosion and inundation risks.
Service Delivery
Fully Managed Service
STARPATH GLOBAL operates a fully managed satellite data pipeline designed to remove operational complexity from geospatial data acquisition and delivery.
End-to-End Lifecycle Management
We coordinate the full lifecycle of satellite intelligence—from mission tasking and data sourcing to processing, quality control, and final delivery—through a controlled, end-to-end workflow managed by our specialists.
Zero Technical Overhead for Clients
Clients define objectives and review outputs. No technical expertise is required to operate the system. We handle all operational execution, including satellite tasking, sensor selection, data acquisition, and downstream processing within a structured production pipeline.
Faster Decisions, Lower Operational Cost
This model transforms satellite data access into a managed intelligence service, enabling faster decisions, reduced operational overhead, and consistent data reliability at scale.