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Mapping & 3D Photogrammetry

2D Orthomosaic Mapping & 3D Modelling

Orthomosaic maps are a selection of overlapping images of a defined area, which we process to create a highly detailed, up-to-date map. An automated flight path is plotted prior to arriving on site and parameters are set to capture the correct amount of photos to give optimum accuracy and scale, providing visual progress reports, safely and quickly, with the capability of mapping difficult terrains or inaccessible areas on a large scale.

Mapping extensive and difficult terrains using traditional methods can bring to light many issues, even when using ground-based LIDAR scanners. For example, when mapping a large lake many points are often undetectable due to vegetation growth, marshland or hard to access areas, resulting in gaps in the 3D point cloud and inconsistency within the finished survey.

With drones we can create an automated flight plan which will capture the whole area in minutes. The data collected can be used alone to create 2D orthomosaic maps, or 3D models which can be exported and used with CAD files and other format files so that you can build your digital dataset of your assets. You have the option of owning the raw data and combining it with your own data to fill in the gaps, or we can process it for you within a 48 hour timeframe.


2D and 3D topographic survey maps are proving to be very useful in the construction, forestry and surveying industries, giving you the option to virtually tour your construction site or real estate from the comfort of your PC.

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A 2D orthomosaic map comprising of 600 photos, stitched together with an 85% overlap. This was a 15 minute automated flight plan created using drone deploy software.


A digital surface model used for measuring the elevations of landscapes. This allows us to measure the height of certain features, the slope of the line segment and the elevation and depth of each area of the 2D map.

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Plant Health - NDVI Data

Normalised Difference Vegetation Index (NDVI) is a respected index for assessing vegetation health. Each pixel is assigned a colour value within a range, based on a formula that measures the relationship between bands of light.

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