Screening, not diagnosis
A persistent anomaly can prioritise inspection. Ganoderma confirmation still depends on qualified field assessment and, where appropriate, laboratory testing.
White paper · Version 2.0
One estate record, from satellite context to field confirmation.
PalmWatch connects repeat landscape observations with targeted close inspection. The aim is not to turn imagery into an automatic diagnosis, but to make change visible, reviewable, and traceable.
Executive summary
Continuous context. Selective detail. Confirmed action.
Satellite time series help teams watch broad change across an estate. Targeted drone flights then provide higher-resolution RGB, multispectral, and thermal evidence over priority areas. Agronomists and laboratories close the loop.
That division of labour matters: medium-resolution satellite pixels may contain several palms and surrounding ground, while drone imagery can support closer crown-level comparison. Neither should be treated as a disease verdict on its own.
The monitoring architecture
- 01
Satellite watch
Build repeat estate-wide observations from optical and, where useful, radar sources. Weather, terrain, and independent soil-context datasets add explanatory context.
- 02
Change screening
Compare blocks and time periods while accounting for cloud, seasonality, sensor differences, palm age, and management events.
- 03
Targeted drone survey
Collect calibrated RGB, multispectral, and thermal evidence over priority blocks instead of treating every hectare as equally urgent.
- 04
Field confirmation
Attach inspection findings and, where required, laboratory results to the same palm or block record.
- 05
Monitor outcomes
Track intervention, follow-up observations, and unresolved cases through a consistent audit trail.
Why two viewing scales?
Satellite and drone evidence answer different questions.
QuestionSatellite layerDrone layer
Best useRepeated estate context and broad changePriority-block and crown-level evidence
CoverageLarge, systematic footprintsSelective, flight-defined areas
Practical limitCloud and mixed pixels can obscure local detailRequires flight planning, calibration, and repeatable conditions
Decision roleWhere should the team look more closely?What closer evidence should field teams review?
Evidence boundaries
What PalmWatch can—and cannot—claim.
Context, not direct soil measurement
Satellite observations can contribute vegetation and surface-condition signals. Soil maps, sampling, weather, terrain, and management records remain separate contextual inputs.
Local validation, not a universal threshold
Vegetation indices vary with sensor, canopy, illumination, season, soil background, and processing. Models must be tested on farms excluded from training.
Ganoderma impact
Per-acre loss depends on the palms, the incidence, and the baseline.
An MPOB case study in Johor reported FFB reductions from 0.04 to 4.34 tonnes per hectare across palms aged 10 to 22 years—approximately 0.016 to 1.76 tonnes per acre. This is a study-specific range, not a universal annual loss for every acre.
A separate Bayesian model estimated economic loss could reach 68% of attainable yield among infected palms. Estate exposure therefore depends on how much area is affected, the age and productivity of those palms, disease progress, neighbouring infection, price, and management response.
Open the loss methodology and calculator →Proposed PalmWatch research design
Study targets are not deployment results.
- 120
- balanced study farms
- 6,000
- mapped palms
- 3
- repeat survey rounds
- 18,000
- tree observations
These figures describe a recommended minimum design for expanded validation. They are not accuracy, deployment, or customer-performance claims.
Selected references
- Roslan Abas & Idris Abu Seman. Economic Impact of Ganoderma Incidence on Malaysian Oil Palm Plantation. MPOB, 2012.
- Kamu et al. Estimating the Yield Loss of Oil Palm Due to Ganoderma Basal Stem Rot Disease. Journal of Oil Palm Research, 2021.
- Izzuddin et al. UAV-Based Remote Sensing for Early-Stage Detection of Ganoderma. Remote Sensing, 2022.
- ESA. Sentinel-2 facts and figures. Accessed September 2026.
- Basal Stem Rot of Oil Palm: The Pathogen, Disease Incidence, and Control Methods. Plant Disease, 2023.