Smart, Drone Mapping for Better Farming Decisions
We turn drone flights into clear, easy-to-use crop intelligence — helping you grow healthier crops, reduce waste and make more confident decisions across your farm.
Our Services
At Cambridge Drone Services, we deliver high-resolution maps and crop insights using the DJI Mavic 3M and advanced processing tools.
Our mapping feeds directly into practical decisions: nutrition, drainage, weed control, SFI evidence, variable rate application and more.
Whether you manage 50 ha or 5,000 ha, our aim is simple:
give you the tools, maps and clarity you need to improve your land and your margins.
Whole-Farm Drone Mapping
High-resolution RGB mapping showing true crop condition, tramline accuracy, missed strips, overlaps and headland stress — far clearer than satellite or phone images.
Crop Monitoring (RGB + Multispectral)
Regular drone flights with NDVI, NDRE, SAVI and more to identify nutrition issues, stress patches, compaction and yield variability early in the season.
Variable-Rate (VRA) Prescription Maps
Turn crop data into precise prescription files for fertiliser, nitrogen, lime and micronutrients. Delivered as ISO-XML or shapefiles for most modern spreaders and sprayers.
Spot-Spraying & Weed Mapping
AI-assisted maps identifying blackgrass and other weed patches. Reduce chemical use, diesel and time by targeting only the areas that need treatment..
Trial Plots & Strip Analysis
Mapped, labelled and analysed trial strips and treatment plots with statistics and annotations — ideal for variety tests, seed rate trials and product comparisons.
PDF Reports & Documentation
Clear, farmer-friendly PDF reports including RGB maps, index maps and annotated insights you can share with agronomists, contractors or SFI inspectors..
Elevation & Drainage Modelling
Digital elevation models and contour lines to highlight wet spots, runoff paths, erosion risks and drainage issues across your fields.
Woodland & Habitat Surveys
Tree counts, canopy condition, habitat mapping and margin assessment using drone imagery and vegetation indices — perfect for estates and environmental auditing.
SFI & Stewardship Mapping
Accurate, date-stamped maps to support SFI and CS evidence, including boundaries, margins, cover crop establishment and environmental features.
Vegetation Indices Explained
Each index is designed to highlight different aspects of crop health, canopy structure, or nutrient uptake. Used together, they help build a complete picture of how your field is performing and where to focus attention..
NDVI – Normalized Difference Vegetation Index
✅ 1. NDVI – Normalized Difference Vegetation Index
Formula: (NIR - Red) / (NIR + Red)
What it shows:
NDVI measures photosynthetic activity by comparing red absorption (chlorophyll use) with near-infrared reflection (cell structure). High NDVI = healthy, vigorous plants with strong biomass. It’s the global standard for crop monitoring.
Best use: Early to mid-season — emergence through canopy closure.
Crop-specific use cases:
- Wheat / Barley: Identify thin stands at tillering, compare drilling accuracy, monitor establishment success.
- Sugar Beet: Spot weak rows before canopy closes, evaluate re-drill thresholds.
- OSR: Highlight slug damage, flea beetle pressure, or uneven emergence.
- Potatoes: Assess stand uniformity, row emergence, and canopy progress.
Agronomic decisions enabled:
- Re-drill or roll patches after poor emergence.
- Benchmark establishment across varieties or seed rates.
- Record establishment success for SFI scheme evidence.
- Identify early-season variability before inputs escalate.
Interpretation guidance:
Values: ~0.2 (bare/poor cover) to 0.7+ (dense, healthy canopy).
Watch for saturation effect — late in the season, NDVI “flattens” at high biomass, so use NDRE for mature crops.
NDRE – Normalized Difference Red Edge Index
✅ 2. NDRE – Normalized Difference Red Edge Index
Formula: (NIR - Red Edge) / (NIR + Red Edge)
What it shows:
NDRE focuses on red-edge wavelengths to assess chlorophyll content. It penetrates deeper into the canopy than NDVI and reveals subtle differences in N uptake and plant stress that NDVI can miss.
Best use: Mid to late season — stem extension through flowering, pod-fill, or tuber bulking.
Crop-specific use cases:
- Wheat / Barley: Assess N uptake at flag leaf, refine split-N timing, identify headland stress.
- Sugar Beet: Detect canopy stress during bulking; compare field zones for late foliar nutrition.
- OSR: Track pod-fill and flowering variability; support fungicide/PGR strategy.
- Potatoes: Identify canopy thinning or early senescence during bulking.
Agronomic decisions enabled:
- Nitrogen top-up rates/zoning.
- Pinpoint areas for tissue testing.
- Forecast yield potential at canopy peak.
- Identify drought or compaction zones.
Interpretation guidance:
NDRE excels where NDVI “saturates.” Use it for nutrient efficiency and late growth stage decisions.
GNDVI – Green NDVI
✅ 3. GNDVI – Green NDVI
Formula: (NIR - Green) / (NIR + Green)
What it shows:
By using the green band, GNDVI detects subtle differences in early canopy stress. Especially valuable in light or reflective soils where NDVI struggles.
Best use: Very early growth — 1–6 leaf stage, tillering, early canopy.
Crop-specific use cases:
- Wheat / Barley: Spot shallow drilling or poor establishment before NDVI reacts.
- Sugar Beet: Identify poor germination or trace element deficiencies (e.g. manganese).
- OSR: Detect slug grazing or poor seed-to-soil contact.
- Potatoes: Highlight non-emerged rows or patchy canopy formation.
Agronomic decisions enabled:
- Trigger early trace element sprays.
- Prioritise fields for crop walking.
- Benchmark drills/varieties under stress.
- Support replant decisions.
Interpretation guidance:
Use GNDVI as a “stress early-warning system.” It often reacts before NDVI in thin crops or problem soils..
SAVI – Soil Adjusted Vegetation Index
✅ 4. SAVI – Soil Adjusted Vegetation Index
Formula: ((NIR - Red) / (NIR + Red + L)) × (1 + L), with L=0.5
What it shows:
SAVI corrects for soil background, reducing false readings where bare soil dominates. It’s best for early scans or no-till systems with low cover.
Best use: Post-emergence, before full canopy closes; particularly useful in patchy fields.
Crop-specific use cases:
- Wheat / Barley: Identify emergence issues in compacted headlands or wide rows.
- Sugar Beet: Map ridge/row consistency in early growth.
- OSR: Detect bare patches due to pests or poor seedbeds.
- Potatoes: Evaluate uneven beds in dry or sandy soils.
Agronomic decisions enabled:
- Support re-drill/replant cost-benefit.
- Benchmark soil-to-plant establishment.
- Provide early SFI compliance evidence for emergence.
Interpretation guidance:
Use SAVI in low biomass stages or highly variable soils. It avoids false “low vigour” readings caused by soil colour differences.
LCI – Leaf Chlorophyll Index
✅ 5. LCI – Leaf Chlorophyll Index
Formula: (NIR / Red Edge) - 1
What it shows:
LCI directly tracks chlorophyll content, linking closely to nitrogen uptake and photosynthetic activity.
Best use: Mid-season, at full canopy — after main N applications.
Crop-specific use cases:
- Wheat / Barley: Confirm uptake after top dressing; identify N-deficient zones.
- Sugar Beet: Pinpoint chlorosis or weak foliar response.
- OSR: Detect zones with better/worse N efficiency in stem extension.
- Potatoes: Monitor canopy vigour during bulking; spot nutrition gaps.
Agronomic decisions enabled:
- Adjust foliar N/top-ups.
- Diagnose poor uptake areas for soil/tissue testing.
- Improve NUE reviews field by field.
Interpretation guidance:
Use LCI with NDRE/CCCI for a full nitrogen story — NDRE for uptake, LCI for leaf tissue concentration.
CCCI – Canopy Chlorophyll Content Index
✅ 6. CCCI – Canopy Chlorophyll Content Index
Formula: (NDRE / NDREmax) × (NDVI / NDVImax)
What it shows:
CCCI integrates canopy structure (NDVI) and chlorophyll (NDRE), making it the best index for Variable Rate Application (VRA).
Best use: Mid-season (GS31–59) when canopy is established and input zoning matters.
Crop-specific use cases:
- Wheat / Barley: Generate N-fertiliser VRA maps tailored to canopy potential.
- Sugar Beet: Forecast harvest variability; identify high/low potential zones.
- OSR: Detect uneven layering or lodging risk pre-flowering.
- Potatoes: Create VRA for irrigation/nutrients during canopy bulking.
Agronomic decisions enabled:
- Precision VRA prescriptions (fertiliser, irrigation, fungicides).
- Target scouting where canopy + chlorophyll diverge.
- Optimise yield maps by linking potential and uptake.
Interpretation guidance:
CCCI is the “action index” — used directly for prescriptions (shapefiles, ISO-XML).
TGI – Triangular Greenness Index (RGB only)
✅ 7. TGI – Triangular Greenness Index (RGB only)
Formula: Green - (0.39 × Red) - (0.61 × Blue)
What it shows:
TGI is a colour-based greenness score from RGB images. While less precise, it’s great for fast assessments or when only RGB cameras are available.
Best use: Any stage — especially early demo flights, crop walks, or with standard drones.
Crop-specific use cases:
- All crops: Quick visual checks, comparisons across trial plots, or to share with stakeholders.
Agronomic decisions enabled:
- First-pass scouting before investing in multispectral flights.
- Communication tool for growers/agronomists.
- Public reporting (e.g. SFI evidence, newsletters).
Interpretation guidance:
Not for input decisions. Use TGI for visual benchmarking and communication.
VARI – Visible Atmospherically Resistant Index (RGB only)
✅ 8. VARI – Visible Atmospherically Resistant Index (RGB only)
Formula: (Green - Red) / (Green + Red - Blue)
What it shows:
VARI uses RGB bands but corrects for atmospheric effects (light, haze). It’s more reliable than TGI for RGB-only scouting.
Best use: Throughout the season, especially on cloudy/hazy days, or when using consumer drones/phones.
Crop-specific use cases:
- All crops: Pre-scouting flights, identifying problem areas quickly without needing multispectral.
Agronomic decisions enabled:
- Prioritise fields needing detailed mapping.
- Identify “hot spots” for follow-up with main drone.
- Provide low-cost vigour checks across large areas.
Interpretation guidance:
Use VARI when budget or weather limits multispectral use. It’s simple, fast, and effective for scouting decisions.
Join the Agricultural Revolution
Drone mapping isn’t just about great images — it’s about changing how you manage your land.
With Cambridge Drone Services, you get clear, practical insights that help you:
- Spot issues early before they cost you yield
- Apply inputs more accurately and reduce waste
- Track crop performance through the season
- Make confident, data-driven decisions
- Support SFI, stewardship, and IPM with real evidence
Farming is changing fast. Drone data gives you the advantage — clearer crops, smarter planning, and better margins.
Ready to see your fields in a whole new way?
Let’s take your farm to the next level..
