SUMO Air Space - Multispectral Surveys to Identify Solution Features
- Claire Rose
- 4 days ago
- 3 min read
Updated: 3 days ago
The latest from SUMO GeoSurveys, providing a range of aerial and geospatial surveys using drones, known commercially as UAS (Unmanned Aircraft Systems).
The Solution is a Drone Survey
Drone Multispectral Surveys have the ability to identify possible solution features on large areas, serving as a first port of call for site investigations.
These surveys allow geological anomalies to be targeted by other specialist geophysical techniques such as Ground Penetrating Radar (GPR), Electromagnetic Conductivity (EM), or Resistivity Imaging (ERT); or directly by intrusive investigations..
This fast and informative approach can greatly assist design, identify potential hazards to construction operations, and prevent the development of sink holes.
Solution, Dissolution, and Sink Holes
A solution or dissolution feature is a cavity in soluble bedrock like limestone, chalk or gypsum, formed in the distant past by natural erosion over long periods of time. These cavities can be infilled by soft sediment (superficial Quarternary deposits), especially in chalk. Erosional processes, such as flowing/leaking water, or mechanical disturbances can cause the sediments to be destabilised and removed, resulting in sink hole formation.

Above: Multispectral image from a Solution Feature survey.
The Multispectral Method
Multispectral surveys involve a drone equipped with a 5-band sensor array which collects images at different wavelengths using reflected light. These bands are green, red, red-edge, near-infrared, and RGB, the latter of which can be processed to extract the blue band.
For a survey area covered in vegetation, the reflectance represents the amount of chlorophyll present in the plants; an indicator of the plants’ health. Since plant health can be influenced by sub-surface features, Multispectral Surveys can show where these features are by the appearance of the plants in the processed image.
For stripped or bare earth survey areas, the reflectance can represent soil organic carbon, soil moisture, or soil texture/density.

Above: Site undergoing geotechnical investigations including a Drone Multispectral Survey to detect solution features
Raster Transformations
The multispectral orthorectified photo can undergo a series of raster transformations, according to different Vegetation Indexes (VIs).
VI formulae combine surface reflectance using two or more wavelengths that are designed to highlight a particular property of vegetation, which may then indicate sub-surface variation. These formulae are applied to multispectral images to produce a variety of indices. We typically carry out 9 transformations including: Normalized Difference Vegetation Index (NDVI) which quantifies the presence of living green vegetation using reflected light in the visible and near-infrared bands; and Red Edge Normalized Difference Vegetation Index (RENDVI) which uses reflectance measurements in the Red Edge (RE) to establish changes in vegetation health.
The various transformations provide a detailed account of plant health and soil composition, allowing for greater understanding of sub-surface potential.

Above: Various vegetation indexes.
Thorough Approach
We have the capacity to capture RGB and multispectral data simultaneously, enabling us to conduct an earthwork and sub-surface survey at the same time. With the ability to record upwards of 100 hectares in a single day, we can very quickly and efficiently provide detailed knowledge of an historic landscape.
Both datasets will be georeferenced to OS coordinates, generally achieving an error of <3cm and a ground sampling distance of 1 – 3cm / pixel.
The RGB survey will produce an orthorectified photo, Digital Elevation Model (DEM), and 3D model of the site, to complement the various transformations from the multispectral survey.

Above: Orthorectified photo of a large landscape.
The various multispectral and RGB outputs are analysed to produce an interpretation figure, highlighting possible solution features and categorising them into priorities for further investigation, according to the strength of the anomaly.

Above: Interpretation figure, highlighting anomalies to be prioritised for further investigation.
Want to learn more?
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