Photogrammetric software that uses the 'structure from motion' (SFM) methodology can construct a 3D representation of the subject matter from multiple overlapping images. The 3D data can be viewed and edited as a 'point cloud'. Each point represents a position in 3D space and can also be coloured in accordance with the photographs to produce a realistic 3D model. Measurements can be made in a point cloud to determine distances between points in three dimensions and to determine volumes. The point cloud is the dataset that allows further processing into a digital surface model (DSM) and, finally, into an orthorectified image or "orthomosaic". An orthomosaic is a collection of aerial images geometrically corrected (orthorectified) such that the scale is uniform. Unlike an uncorrected aerial photograph, an orthoimage can be used to measure true distances because it is an accurate representation of the Earth’s surface, having been adjusted for topographic relief, lens distortion, and camera tilt.
Taking a step back: The point cloud can be classified into collections of point clusters that variously represent 'terrain' (ground, road surface) and 'objects' like vegetation, buildings and human-made objects. The software can now, by only referencing the points that represent 'terrain' estimate a Digital Terrain Model (DTM). The DTM forms the basis of terrain analysis functions like contour generation, hydrological analysis and landscape characterisation.
By Using a GIS platform, information from surface models, terrain models and the orthomosaic can be used in various ways to produce maps that depict the required features.
3D Point Cloud
Camera positions for multiple overlapping images
Using the DSM and DSM raster products, a variety of terrain characters can be derived using GIS algorithms. Commonly, the DSM is given hillshading to make it visually intuitive and the DTM is used to derive, for instance, drainage channels. Contour lines are derived from the DTM rather than the DSM so that buildings and trees are not contoured.
The final product of the photogrammetric processing is the orthomosaic. It is geometrically corrected ("orthorectified") such that the scale is uniform and the image follows a given map projection. Unlike an uncorrected aerial photograph, an orthophoto can be used to measure true distances, because it is an accurate representation of the Earth's surface. Orthomosaics are commonly used in geographic information systems (GIS) as a "map accurate" background image.
The perceived quality or resolution of an orthomosaic and of the DSM on which it is based is largely dependent on the resolution at which the photographs were taken. In aerial surveying, this resolution is quoted as the Ground Sample Distance (GSD). In an image with a 10cm GSD, adjacent pixels image locations are 10cm meter apart on the ground. GSD is a measure of one limitation to image resolution, that is, the limitation due to sampling. Given that a camera in a moving aircraft is not a perfect optical sampling device (lens aberrations, atmospheric haze, vibration), the resulting image will be somewhat less true than the resolution suggested by the GSD. The resolution of the imagery produced can be expressed in terms of 'Spatial Resolution". This is a measure of how closely lines or objects can be discerned from each other in an image, and it depends on properties of the system creating the image, not just the pixel resolution or GSD.
The top image on the right was taken at a GSD of 25cm/pixel. The image below that is a crop of a small area (red rectangle) within the larger image (zoomed in, so to speak) to show the spatial resolution in the orthomosaic. Judging by the railway tracks, the vehicles and the resolvable distance between the containers, the spatial resolution comes out at about 35-40cm. There is no hard rule by which to estimate the spatial resolution resulting from a particular GSD. By using the best available cameras and lenses, by eliminating vibration, by using optimal camera settings for the conditions and by only flying in suitable conditions of light and visibility we find that we can usually achieve a spatial resolution of 1.5 x GSD. For objects that are partly obscured or do not contrast well against background, spatial resolution deteriorates.
We have, over the years, amassed sufficient projects at various resolutions ranging from 2cm/pixel to 30cm/pixel to make an educated recommendation of GSD for a particular project.
The total area of a project and GSD are the determining factors of cost. The shape of a project area and the distance from our home base are also cost factors, but to a lesser degree.
A variety of other products
There is a wide scope of products that can be derived from aerial photography and photogrammetry. By using our narrow band multispectral camera rig we produce images and orthomosaics showing various spectral indices, such as those used for plant health monitoring in agriculture including NDVI.
By flying relatively low and using a telephoto lens, surprising detail can be captured. Animals, vehicles and other objects of interest can be detected from aloft and then photographed at closer range to reveal their size, well-being or identity.
False colour NIR reflectance map
Cropped image taken from our manned aircraft using a 300mm lens
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