Satellite & Remote Sensing
Remote Sensing: For Farmers
What Remote Sensing changes for the person actually doing the work.
For the person running the business, the test of any farm software is whether it removes work or adds it. Public satellite programmes provide regular, free, ten-metre imagery over the whole UK, which is sufficient for most in-season monitoring decisions. This module ingests and processes that imagery into usable indices, handles cloud gaps with radar, and turns the resulting maps into zoning, scouting priorities and scheme evidence rather than pretty pictures.
In their words
What the job actually looks like
These are not marketing personas. Each one is a distinct job with a distinct constraint, and the module is designed so that solving one does not create work for the others.
Large arable manager
Cannot walk everything weekly
Needs a prioritised list of which fields matter this week.
- Register field boundaries
- Ingest imagery automatically on each pass
- Mask cloud and fill with radar
- Calculate indices and build the time series
Grassland farmer
Cover estimation
Needs biomass estimates when the plate meter round is missed.
- Ingest imagery automatically on each pass
- Mask cloud and fill with radar
- Calculate indices and build the time series
- Detect anomalies against the expected trajectory
Scheme adviser
Monitoring and evidence
Needs dated imagery evidence of habitat and cover.
- Mask cloud and fill with radar
- Calculate indices and build the time series
- Detect anomalies against the expected trajectory
- Prioritise scouting and verify on the ground
End to end
How Remote Sensing runs, start to finish
The module is modelled as a state machine, so at any point the business knows exactly which stage every record is at and what has to happen next.
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1
Register field boundaries
This is where the record starts, and getting it right here removes work at every later stage.
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2
Ingest imagery automatically on each pass
The platform prompts only for what this stage genuinely needs, and carries everything forward.
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3
Mask cloud and fill with radar
Conflicts with scheme rules, regulatory windows and existing commitments are flagged here rather than discovered later.
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4
Calculate indices and build the time series
Capture works offline, so this stage is completed in the field rather than remembered afterwards.
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5
Detect anomalies against the expected trajectory
Everything recorded at this point becomes evidence automatically, in every format that will later ask for it.
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6
Prioritise scouting and verify on the ground
This is the stage most businesses currently do twice, once for the operation and once for the paperwork.
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7
Feed zoning and prescriptions
Results feed the whole-farm view, so the effect of this stage is visible against the rest of the business.
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8
Archive as evidence
The cycle closes here, and what is learned is carried into next season's plan rather than lost.
Capabilities
What Remote Sensing does
Every capability below is built on the same underlying record, so entering something once is enough for it to appear wherever it is needed.
Record and plan
- Automated satellite imagery ingestion for every registered field
- Vegetation index calculation including NDVI, NDRE and biomass proxies
- Cloud detection and gap filling using radar backscatter
Operate and monitor
- Time series analysis with within-season and between-season comparison
- Anomaly detection flagging fields diverging from the expected trajectory
- Zoning outputs feeding the variable rate prescription builder
Comply and evidence
- Crop establishment assessment and gap identification
- Grass growth and biomass estimation for the grassland module
- Change detection for land use, habitat and compliance monitoring
Analyse and improve
- Scouting priority list generated from imagery anomalies
- Historic archive access for retrospective claim and insurance evidence
- Imagery-derived evidence packs for scheme monitoring
Find
Find contractors and dealers
Filter by type, nation, distance and accreditation. Results are ranked by relevance to your holding once your holding record exists, and alphabetically before that.
6 records shown from the platform’s own register
- Module Machinery, Fleet & Contracting Flagship
- Module Precision Agriculture, Guidance & Variable Rate Core
- Module Robotics & Field Automation Core
- Module Drones & Aerial Survey Core
- Module Satellite & Remote Sensing Core
- Module IoT Sensors & Rural Connectivity Core
Worked example
How a business like yours would use Remote Sensing
The problem: Needs a prioritised list of which fields matter this week.
What they do
- Register field boundaries
- Ingest imagery automatically on each pass
- Mask cloud and fill with radar
- Calculate indices and build the time series
What changes
- Fields with current imagery
- Anomalies detected and verified
- Scouting time saved
This is an illustrative worked example built from the module design, not a customer reference. Named case studies are published only with the business's written consent.
What we are hearing
The problems people describe to us
These are composite statements drawn from user research conversations, not attributed customer quotes. We publish named references only with written consent.
I am not short of software. I am short of one place where the same field means the same thing in all of it.
The scheme closed on a Tuesday evening. I had the application half built. Nobody told me the budget was nearly gone.
We farm on both sides of the border. Everything takes twice as long and I still cannot see the whole position on one screen.
Audit week costs me three days. Every single record they ask for is already written down somewhere on this farm.
Measurement
How you will know it is working
The module reports against these measures from the day it is switched on, so the value is demonstrable rather than assumed.
- 01Fields with current imagery
- 02Anomalies detected and verified
- 03Scouting time saved
- 04Zoning derived from imagery
- 05Cloud-free coverage achieved
See it working
Book a demonstration on your own holding data
Thirty minutes, using your parcels and your schemes rather than a sample farm, so you can judge it on your own numbers.