Seeing Beyond the Visible: A Practical Guide to Multispectral Drone Imagery

Altum PT Multispectal Sensor

NRG Image of Pilbara Creekline

Multispectral drone imagery is revolutionising the way we assess vegetation, land condition, and crop performance across mining, agricultural, and ecological restoration landscapes. Unlike standard RGB imagery that captures only visible colours, multispectral imaging collects data from targeted wavelengths, some beyond human sight. This allows us to uncover deeper insights into plant health, soil condition, and ecosystem dynamics.

This article explains what multispectral imagery is, how sensors like the RedEdge-MX and Altum-PT work, and how this technology is applied in mining, environmental monitoring, and agriculture. We also explore some key considerations like calibration and weather conditions, so you can get the most out of your data.

What Is Multispectral Imagery?

Multispectral imagery captures light reflected from the Earth’s surface in a handful of narrow, precisely defined spectral bands. Most commonly, these include:

• Blue (~475 nm)

• Green (~560 nm)

• Red (~668 nm)

• Red-edge (~717 nm)

• Near-infrared (NIR) (~842 nm).

  
  

Each of these bands provides a unique window into vegetation health, moisture content, and plant physiology. For example, healthy vegetation reflects strongly in the NIR band due to internal leaf structure, while stressed or sparse vegetation reflects less.

By combining these bands into indices such as NDVI (Normalised Difference Vegetation Index) or NDRE (Red Edge NDVI), we can assess things like plant vigour, chlorophyll content, and canopy development metrics not visible with standard RGB cameras.

How It’s Different from Standard Imagery

Where a typical drone camera produces full-colour images using red, green, and blue channels, multispectral sensors capture each band as a separate grayscale image. These images are calibrated to represent true reflectance values, allowing for consistent, repeatable analysis across time, locations, and lighting conditions.

This makes multispectral imagery especially valuable for detecting subtle changes in vegetation changes that may signal stress, invasive species, or productivity decline before they’re visible to the human eye.

Popular Drone Sensors: RedEdge-MX and Altum-PT

We use two of the most widely used drone-mounted multispectral sensors available:

RedEdge-MX

• Captures 5 narrow bands (Blue, Green, Red, Red-edge, NIR)

• Lightweight and compatible with many commercial drones

• Designed for vegetation analysis in agriculture, mining rehabilitation other ecological studies.

Altum-PT

• Captures the same 5 bands plus a thermal infrared layer

• Higher resolution (12 MP per band) and radiometric thermal data

• Ideal for advanced monitoring: water stress, seepage zones, canopy temperature.

Both sensors include a sunlight sensor and use radiometric calibration techniques to ensure data accuracy and consistency.

Applications in the Field

Mining

Multispectral drones are widely used for rehabilitation monitoring, helping site managers measure vegetation cover, identify struggling areas, and detect changes over time. In tailings areas or waste dumps, they help identify seepage zones or poorly draining areas, especially when paired with thermal data.

Environmental Monitoring

For conservation areas or offset sites, multispectral imagery enables tracking of plant health, species composition, and vegetation establishment. Indices like NDVI and red-edge metrics offer insight into canopy cover, functional diversity, and seasonal variation.

Agriculture

In cropping and grazing systems, multispectral imagery is used for precision agriculture. It helps detect plant stress early, optimise fertiliser use, plan irrigation, and assess crop growth. NDRE is particularly useful for later-stage chlorophyll tracking, while time-series NDVI can predict yield or detect disease before it spreads.

Why Calibration Matters

Because multispectral sensors aim to deliver quantitative, not just visual data, calibration is essential.

1. Reflectance Panels: Before or after each flight, a calibrated panel is photographed. This serves as a baseline to correct the reflectance values in the imagery.

2. Sunlight Sensor: Mounted on the drone, it measures ambient light conditions during flight to adjust for clouds, haze, or time-of-day differences.

3. Flight Settings: Consistent ISO, shutter speed, and overlap (typically 80%+ forward and 70%+ side) help ensure that image data is reliable and repeatable.

Without calibration, changes in NDVI could reflect nothing more than lighting conditions, not real changes in vegetation condition.

Flying Conditions: Getting It Right in the Field

Multispectral flights are sensitive to weather, light, and terrain. For best results:

• Fly near solar noon to reduce shadows and solar angle distortion, though not to close that you get sunspots in the imagery

• Avoid overcast or partly cloudy days and try to only fly when the sky is clear

• Use terrain-following or fixed altitude carefully especially when working on undulating ground.

  
  

Failing to control these factors can introduce artefacts into your mosaics and affect reflectance accuracy.

Final Thoughts

Multispectral drone imagery provides a reliable, scalable approach to quantifying vegetation health and land condition across diverse environments. When used effectively, it offers objective, repeatable data that supports evidence-based decisions in rehabilitation, conservation, and agricultural production.

Multi Scan has been capturing multispectral imagery for the past decade. We offer high resolution, calibrated 5 band data capture anywhere in Australia. Contact us, we’d love to assist with your next multispectral data capture.