LiDAR visualisations for archaeology

A LiDAR visualisation turns a grid of ground heights into a picture of the shape of the land, and each kind brings out different earthworks. Field Archaeology, a research atlas for England, has twelve LiDAR views.

Last updated 25 October 2026 · By Gitwix Limited

This guide takes the twelve views one at a time: what each shows, when to use it, what can mislead you and where the method comes from.

Every picture on this page shows the same frame of Maiden Castle, the Iron Age hillfort outside Dorchester in Dorset (National Heritage List for England, list entry 1015775), so one view can be set directly against the next. Eight of the twelve views are pictured; Positive openness, Height bands, Contours and the Surface model are described in words. For the hillfort itself, see Maiden Castle in LiDAR.

Which view shows what?

Each view answers a different question about the ground. Read the land in a shaded view first, then check anything you find in two or three others, because no single view shows everything (see why use more than one view).

How are the views made?

Every view but the Surface model starts from the same data: the Environment Agency's LIDAR Composite Digital Terrain Model (DTM), a grid of bare-earth heights at 1 m covering about 99 per cent of England. The Agency produced it in 2022 from surveys flown between 6 June 2000 and 2 April 2022, using the newest, highest resolution survey wherever ground was flown more than once. It is made from the last or only return of each laser pulse, with buildings, trees and other objects removed by the Agency's own algorithms and by hand, and every survey in it had a vertical accuracy of plus or minus 15 cm (root mean square error). It is free to reuse under the Open Government Licence. The Surface model uses the Agency's matching surface model, which keeps those objects in.

The LiDAR relief is the Agency's own hillshade. The other eleven views are drawn on our own server from the Agency's LIDAR Composite DTM 1 m (2022) in England, and from the Welsh and Scottish surveys over the border. The grid is 1 m from zoom 16 inwards and coarser further out (about 3 m at zoom 15, 6 m at 14 and 12 m at 13). Positions use the Ordnance Survey Helmert transformation, so a view can sit 1 to 4 m off the Agency's own hillshade. Nothing is added to the heights, and gaps stay empty. The README that comes with every LiDAR heights download says the same.

Leaving gaps empty is deliberate. Historic England sees value in leaving ground the laser did not reach blank, rather than smoothing it over, ‘to emphasise the fact that the technique was ineffective in those areas’ (Historic England 2018, section 4.2.2). Area reports and printed maps carry the method line of each view that was on the map, and those lines are quoted under each view below.

In the atlas each view is a layer you can fade over the map or the satellite picture. All but Red relief, Contours and the Openness composite, which carry their own colours, can be recoloured with one of seven colour ramps. Every dataset behind the atlas is listed in Data and licences, and the terms used here are defined in the glossary.

To draw comparable views yourself, the freely available Relief Visualization Toolbox, from ZRC SAZU and the University of Ljubljana, computes hillshading from one or many directions, slope, the simple local relief model, sky-view factor and positive and negative openness, and runs as a plugin for QGIS. The atlas's LiDAR heights download gives the Environment Agency's terrain model as GeoTIFF files that open in QGIS as they are.

LiDAR relief (hillshade)

A hillshade lights the ground model from one direction, like a low sun: slopes facing the light are bright and slopes facing away are dark. Historic England calls it ‘the most obviously user-friendly product, because it is relatively easy to interpret’. The atlas's LiDAR relief is the Environment Agency's own hillshade of its 1 m terrain model.

Use it for a first reading of the ground. A hillshade looks much like an aerial photograph of earthworks in low sunlight, so the form of a site is clear at a glance.

Watch for what a single light hides. Zakšek, Oštir and Kokalj name its two major drawbacks: ‘identifying details in deep shades and inability to properly represent linear features lying parallel to the light beam’. Historic England shows the second with medieval ridge and furrow near Alchester, Oxfordshire, lit from two directions at right angles. You also need to know where the light comes from to tell a cut feature from a raised one: most people read a picture most easily with the light falling from the top, and map makers usually put the sun in the north-west (Historic England 2018, box 3 and section 4.2.1).

Origin. Hill-shaded maps were first drawn by hand, by landscape artists, and computers and digital elevation models made them routine (Yokoyama, Shirasawa and Pike 2002). One of the standard formulas for working out a hillshade from a grid of heights is Horn's (1981).

In the atlas. ‘The Environment Agency's own hillshade of its LIDAR Composite DTM 1 m, served by the Environment Agency.’ It can be shown in grey or in colour, with brightness, contrast and colour strength to adjust.

Multi-light relief (multi-directional hillshade)

Multi-light relief lights the ground from six directions at once and averages the results, so a feature that one light misses is caught by another.

Use it for a shaded view without the blind spot of a single sun. Earthworks show whichever way they run, which makes it a good first look at unfamiliar ground.

Watch for a flatter picture. With the lights spread evenly round the compass, the result depends mostly on how steep the ground is rather than which way it faces: level ground is an even grey and steep faces are dark, so the picture has less of the depth a single sun gives. Historic England warns that misreading raised and sunken features becomes ‘even more of an issue’ with hillshading from multiple directions, and the Relief Visualization Toolbox documentation notes that the added complexity can make such images ‘tricky to interpret’. Heights are exaggerated two times on the 1 m grid, so slopes look steeper than they are.

Origin. Combining hillshades lit from different directions goes back at least to Robert Mark's image of the Island of Hawaii, made by combining shaded-relief images so that every surface is lit obliquely (Mark 1992). Devereux, Amable and Crow (2008) showed how features picked up by light from different directions can be combined in one image for archaeological survey. Historic England notes that such composites use from four to 64 directions, and that the 16-direction multi-hillshade is the commonest.

In the atlas. ‘Hillshade lit from six directions (0, 60, 120, 180, 240 and 300 degrees) at 45 degrees above the horizon and averaged, with heights exaggerated two times on the 1 m grid (more on the coarser grids), so no single sun angle hides a feature.’

Palaeochannels (slope)

A slope map shades each cell by how steep the ground is, whichever way it faces: here flat ground is pale and steep ground dark. The atlas calls it Palaeochannels because it brings out old river courses: on a flat valley floor even a gentle change of slope, such as the edge of a former channel, shows as a darker line.

Use it for breaks of slope of every kind: the faces of banks and scarps, terraces and lynchets, the sides of hollow ways and the edges of old river channels. It needs no light direction, because slope ‘is aspect independent’ (Relief Visualization Toolbox documentation).

Watch for the sign of a feature. Slopes of the same steepness look the same whether they rise or fall, so a bank and a ditch can look alike; check them in Local relief or the Openness composite. The scale stops at 14 degrees, so every steeper face is the same black.

Origin. Slope is a standard measure of terrain with no single inventor, worked out from the cells around each one by formulas such as those of Horn (1981) and of Zevenbergen and Thorne (1987). Historic England counts slope among the simple visualisations, ‘commonly used within the GIS community’, that archaeologists took up first.

In the atlas. ‘Slope: the steepest gradient at each cell from its eight neighbours, shaded from flat (pale) to 14 degrees and steeper (dark) on a 0.55 power curve.’ The power curve gives gentle slopes more of the grey scale than an even scale would, which is what lets faint channel edges show.

Local relief (local relief model)

A local relief model subtracts a smoothed copy of the ground from the ground itself. The hills and valleys go, and what is left are the small rises and dips of earthworks: light where the ground stands above its surroundings, dark where it lies below.

Use it for low, broad earthworks that a hillshade can miss, whichever way they run. Hesse lists ‘burial mounds, linear and circular earthworks, sunken roads, agricultural terraces, ridge and furrow fields, kiln podia and mining/quarrying sites’. Because the slope of a hill is taken away, it works on hillsides too, and because the grey stands for height above or below the ground nearby, it gives a rough measure: Hesse notes that relative heights and volumes can be measured directly.

Watch for the size of the window, which decides what survives. Earthworks much wider than the window, about 40 m here, are partly taken away with the hills, and beside a large bank or a steep scarp the smoothed surface is pulled up or down, so the ground next to it can look lower or higher than it is. Anything that rises or falls more than 0.6 m saturates, as the ramparts do here.

Origin. Ralf Hesse proposed local relief models as a tool for archaeological prospection in 2010, when they were being used to map the archaeology of the whole German state of Baden-Württemberg (Hesse 2010). His method goes further than a single subtraction: it traces where the difference between the ground and its smoothed copy is zero, takes the ground's heights along those lines, and interpolates a purged surface between them, which is subtracted from the ground instead (Hesse 2010; Petras and Goddard, no date). The atlas uses the simpler form, which the Relief Visualization Toolbox calls a simple local relief model, and so says ‘compare Hesse (2010)’ rather than ‘after’.

In the atlas. ‘A simple local relief model: the ground minus its mean over a 41 m square (20 m each way), with plus or minus 0.6 m across the grey scale on the 1 m grid. Compare Hesse (2010).’

Sky view (sky-view factor)

Sky-view factor is the share of the sky that can be seen from each point on the ground. Open ground sees most of the sky and is bright; the floor of a ditch or a hollow sees less and is dark. No sun is involved, so a feature shows whichever way it runs.

Use it for sunken features: ditches, pits, quarries and hollow ways. Its authors found that it ‘improves the recognition of small scale features from high resolution DEMs’, and the features it shows ‘do not contain any horizontal displacements’ (Relief Visualization Toolbox documentation), whereas in a shaded view the true edge of a feature can be hard to place.

Watch for flat ground and raised features. On flat or very gentle ground it is ‘generally limited to the presentation of negative relief features’ and becomes ‘very sensitive to DEM noise’ (Relief Visualization Toolbox documentation), so look for banks in Positive openness instead. The search radius sets the scale of what shows: the atlas looks 12 cells out in each of eight directions.

Origin. Zakšek, Oštir and Kokalj proposed the sky-view factor as a relief visualisation in 2011, and Kokalj, Zakšek and Oštir applied it to historic landscape features the same year. Historic England's glossary defines it as ‘a geophysical parameter that represents the portion of the sky visible from a certain point’.

In the atlas. ‘Sky-view factor: the share of the sky seen from each cell, from horizon angles in eight directions out to 12 cells (12 m on the 1 m grid), shown from 0.86 (dark) to 0.99 (bright). Compare Zakšek, Oštir and Kokalj (2011).’ For comparison, the Relief Visualization Toolbox documentation suggests a stretch of 0.65 to 1.0 for varied terrain and 0.9 to 1.0 for very flat terrain.

Positive openness

Openness measures how open each point is to the horizon, looking out along eight directions. Positive openness looks above the surface and is high on convex ground: banks, ridges and the edges of platforms. Negative openness looks below it and is high in concave ground: ditches, pits and hollows. One is not simply the reverse of the other; negative openness ‘provides additional information’ (Relief Visualization Toolbox documentation).

There is no picture of Positive openness on this page; the Openness composite below shows it in red. The atlas has no separate view of negative openness: it is part of the Openness composite and of Red relief.

Use it for outlining features. Doneus (2013) found that openness ‘is not subject to directional bias’, that the features it highlights ‘do not contain any horizontal displacement’, and that it ‘highlights both the highest and lowest parts of features’, which makes it ‘an ideal tool for mapping and outlining of archaeological features’. Positive openness on its own picks out the raised parts.

Watch for halos and the loss of the lie of the land. Historic England warns of ‘“halos” around features in openness visualisations, where the break between a ditch and flat ground can appear as a slight bank’. And without any shading, ‘the visual impression of the general topography is lost’, so the picture takes more getting used to (Relief Visualization Toolbox documentation).

Origin. Yokoyama, Shirasawa and Pike introduced openness in 2002 as a measure ‘expressing the degree of dominance or enclosure of a location on an irregular surface’, noting that it needs no light source. Doneus (2013) showed its value for mapping archaeology from airborne laser scanning.

In the atlas. ‘Positive openness: the mean angle from the zenith to the horizon in eight directions out to 12 cells, so banks, ridges and platform edges light up. After Yokoyama, Shirasawa and Pike (2002).’

Openness composite

The Openness composite puts three measures into one colour picture: positive openness drives the red, negative openness the blue, and their mean, toned by the sky-view factor, the green. Ground that stands proud comes out in warm reds and oranges, sunken ground in blue.

Use it for telling banks from ditches at a glance. The atlas's own guide says to ‘read red as a bank or platform and blue as a ditch or hollow way, and look hardest where the two run parallel, which is what a bank with its ditch looks like from above’.

Watch for halos. Where a ditch meets level ground the edge turns convex, so a thin line of red can run along a ditch where there is no bank: the halo Historic England describes for openness.

Origin. This blend is the atlas's own. Kokalj and Somrak (2019) set out how to blend several visualisations so that different features show in a single image, and their recipe, the Visualisation for Archaeological Topography (VAT), is built into the Relief Visualization Toolbox.

In the atlas. ‘Positive openness in red, negative openness in blue and the mean of the two, toned by the sky-view factor, in green: proud ground reads red and sunken ground blue.’

Red relief (red relief image map)

A red relief image map shows openness as light and dark and slope as shades of red, so ridge tops come out white, valley floors black, steep slopes bright red and flat ground grey (Chiba, Kaneta and Suzuki 2008). There is no light direction to choose.

Use it for one picture that shows raised ground, sunken ground and steepness together. Its authors list among its advantages that it is ‘independent of direction of incident light’.

Watch for what the colour carries. Slope is shown by the red alone, so in a black and white copy steep ground turns dark and can no longer be told from a hollow. The authors also list its limits: it shows no elevation and nothing of the direction a slope faces. Because it is built on openness, it can show the same halos along the edges of ditches.

Origin. Chiba, Kaneta and Suzuki, of Asia Air Survey in Japan, published the red relief image map in 2008, building it from slope and from positive and negative openness after Yokoyama, Shirasawa and Pike (2002).

In the atlas. ‘A red relief image map: brightness from positive minus negative openness (eight directions, 12 cells), plus or minus 15 degrees across the scale, and redness from slope up to 25 degrees. After Chiba, Kaneta and Suzuki (2008).’

Height colour

Height colour shows how far each spot stands above or below the ground within about 300 m of it. It opens on a colour ramp from deep blue for the lowest ground, through teal and yellow, to orange and near white for the highest.

Use it for the setting of a site: whether it sits on a hilltop, a spur, a terrace or a valley floor, and how the land falls away round it. It is the subtraction behind Local relief at the scale of the landscape, with a window about fifteen times wider and a colour range 25 times taller.

Watch for what the colours mean. They show height relative to the surroundings, not height above sea level, so one colour can stand for different heights in different places, and near a large hill or valley the 300 m window bends them: ground beside a high hill can read low when it is not. For heights in metres, use Height bands or Contours.

Origin. The method is a topographic position index: the height of the ground minus the mean height around it (compare De Reu et al. 2013). The 601 m window and the plus or minus 15 m colour range are the atlas's own.

In the atlas. ‘The ground against its mean over a 601 m square (300 m each way), with plus or minus 15 m across the colour ramp.’

Height bands

Height bands colour the ground by its height above Ordnance Datum in equal steps, over a soft hillshade so its shape still reads. The steps are fitted to the ground in view, and the atlas shows the range they cover in metres. There is no picture of this view on the page.

Use it for height in metres: the line of a river terrace, the edge of a floodplain, the top of a ridge, or whether two earthworks sit at the same level. The number of bands can be set to 5, 10, 20 or 40.

Watch for the stretch. Because the bands are fitted to the ground in view, a colour stands for a different height after you pan or zoom, so read the range the atlas shows rather than the colour alone. Equal steps can also make a smooth slope look terraced at the edges of the bands.

In the atlas. ‘Height above Ordnance Datum in equal bands between the 2nd and 98th percentile of the ground in view, over a hillshade lit from four directions at 45 degrees.’

Contours

Contours join points of equal height. The atlas draws them every metre close in, with every fifth line bolder. There is no picture of this view on the page.

Use it for reading heights and the form of the ground: a line that bends round a spur or into a hollow traces its shape, and lines that crowd together mark a steep slope.

Watch for earthworks lower than the interval, which can fall between two lines and vanish, and for the interval widening as you zoom out.

In the atlas. ‘Height lines every 1 m on the 1 m grid (2, 5, 10 or 20 m further out), every fifth line bolder.’

Surface model (digital surface model)

The Surface model is multi-light relief drawn from the Environment Agency's digital surface model (DSM) instead of its terrain model. The DSM keeps what stands on the ground, which the Agency describes as ‘vehicles, buildings and vegetation, as well as the terrain surface’. Every other view uses the terrain model, with those taken out. There is no picture of this view on the page.

Use it for seeing what stands on a site today: woods, hedges and buildings. It also shows where to read the terrain views with care. Under a building no laser pulse reaches the ground, and where vegetation is dense ‘there may be significant areas where last returns do not reach the ground’ (Historic England 2018, section 4.2.2).

Watch for the ground it hides. Trees, hedges and buildings cover the earthworks beneath them, so for archaeology under woodland use the terrain views. The view covers England only.

In the atlas. ‘Multi-light relief (six directions at 45 degrees, heights exaggerated twice) of the Environment Agency's LIDAR Composite DSM 1 m (last return), so trees, hedges and buildings show. England only.’

Point cloud and 3D model

Every LiDAR picture begins as a point cloud: the points where laser pulses fired from an aircraft came back from the ground, from vegetation or from roofs, each with its position and height. The Environment Agency's National LIDAR Programme, flown over England in the winters between January 2017 and February 2023, publishes its point clouds as LAZ files, ‘classified into ground, low, medium and high vegetation classes using an automated classification process’, under the Open Government Licence. Classifying the points is what lets the ground be separated from what stands on it, and so a terrain model be made.

The film on the home page opens on the same frame of Maiden Castle as the pictures here, then lifts it into three dimensions. Its point cloud is not the survey's own points: it is the Environment Agency's 1 m terrain model averaged to 4 m cells and drawn as one point a cell, coloured by height. It then turns solid, with the hillshade laid over it. Heights in the film are exaggerated 2.6 times, so slopes look steeper than they are. See it on the home page.

In the atlas. Hybrid LiDAR 3D builds the ground of an area you draw in three dimensions from the LiDAR, up to nine 1 km squares or about 3 km across, to turn, tilt and light from any side, with Palaeochannels, Red relief, the Openness composite, the satellite picture or the map laid over it. The ground comes from the Agency's terrain model; the trees, hedges and buildings standing on it come from the Agency's classified point cloud, and can be faded away to show the ground beneath. The atlas's guide notes that ‘banks, ditches and building platforms read more clearly when the ground can be turned to a low light and seen from the side’, and that the 3D view helps in planning survey on sloping ground.

Watch for the limits of a screen. Historic England points out that 3D on a screen is ‘more accurately a 2D representation of 3D data (2.5D)’, and in a perspective view distances and heights are hard to judge. Take measurements from the flat views or from the heights themselves: the atlas's LiDAR heights download gives the terrain model and the last-return and first-return surface models as GeoTIFF files, up to 5 km a side. It does not supply the point cloud files, which come from the Environment Agency.

Why use more than one view?

Because each view misses something. In a comparison of visualisation techniques, Bennett and colleagues found that no single technique recorded more than 77 per cent of the features, every combination of two recorded more than 80 per cent, and any three together more than 90 per cent (Bennett et al. 2012, as summarised by Historic England 2018).

Even when one visualisation seems particularly useful it is good practice to use as many different types of visualisation as possible to obtain a comprehensive overview of the archaeology.

The atlas's own guide puts the same point practically: ‘a feature that shows in two is worth checking on the ground, a feature that shows in one is often noise’. A workable order is to read the ground in LiDAR relief or Multi-light relief, look for sunken features in Sky view and raised ones in Positive openness, check their form in Local relief, and tell banks from ditches in the Openness composite before you draw anything.

For more depth, Kokalj and Hesse's guide to good practice (2017) explains the main techniques and how to use them, and the European Archaeological Council's guidelines on airborne laser scanning (Bennett et al. 2025) include a chapter on visualising the data.

What can mislead you?

Historic England warns that ‘a lidar-derived image can appear misleadingly simple to interpret’ and that interpretation should be made by someone with the necessary skills and experience. Its guidance gives examples worth knowing (Historic England 2018, sections 4.2.1 and 4.2.3):

• A feature that shows on top of a modern road or hedge, not just on either side of it, lies on the surface of the image, not in the ground: it is an artefact of the data.
• Where survey strips overlap, interference can leave wavy lines that look like the reverse S curves of ridge and furrow, and some crops can do the same.
• Heights rounded to whole metres form steps that follow the contours and can pass for lynchets.
• A shape can be something else entirely: Historic England shows a mound with every appearance of a barrow that aerial photographs and mapping reveal as the site of a covered reservoir.

Before relying on a feature, check it against historic maps, aerial photographs and the heritage records: the same sources a desk-based assessment draws on.

Questions and answers

References

1. Bennett, R., Welham, K., Hill, R.A. and Ford, A. (2012) ‘A comparison of visualization techniques for models created from airborne laser scanned data’, Archaeological Prospection, 19(1), pp. 41 to 48. Available at: https://doi.org/10.1002/arp.1414.
2. Bennett, R. et al. (2025) Guidelines for the use of Airborne Laser Scanning (Lidar) in Archaeology. EAC Guidelines 10. European Archaeological Council. Available at: https://doi.org/10.5281/zenodo.14609210.
3. Chiba, T., Kaneta, S. and Suzuki, Y. (2008) ‘Red relief image map: new visualization method for three dimensional data’, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37(B2), pp. 1071 to 1076. Available at: https://www.isprs.org/proceedings/XXXVII/congress/2_pdf/11_ThS-6/08.pdf (Accessed: 25 October 2026).
4. De Reu, J., Bourgeois, J., Bats, M. et al. (2013) ‘Application of the topographic position index to heterogeneous landscapes’, Geomorphology, 186, pp. 39 to 49. Available at: https://doi.org/10.1016/j.geomorph.2012.12.015.
5. Devereux, B.J., Amable, G.S. and Crow, P. (2008) ‘Visualisation of LiDAR terrain models for archaeological feature detection’, Antiquity, 82(316), pp. 470 to 479. Available at: https://doi.org/10.1017/S0003598X00096952.
6. Doneus, M. (2013) ‘Openness as visualization technique for interpretative mapping of airborne lidar derived digital terrain models’, Remote Sensing, 5(12), pp. 6427 to 6442. Available at: https://doi.org/10.3390/rs5126427.
7. Environment Agency (2022) LIDAR Composite Digital Surface Model (DSM), 1m. Available at: https://www.data.gov.uk/dataset/cf3f1137-c12b-44a1-a835-e80fe4a60b92/lidar-composite-digital-surface-model-dsm-1m (Accessed: 25 October 2026).
8. Environment Agency (2022) LIDAR Composite Digital Terrain Model (DTM), 1m. Available at: https://www.data.gov.uk/dataset/01b3ee39-da3f-47b6-83da-dc98e73a461f/lidar-composite-digital-terrain-model-dtm-1m (Accessed: 25 October 2026).
9. Environment Agency (no date) National LIDAR Programme. Available at: https://www.data.gov.uk/dataset/f0db0249-f17b-4036-9e65-309148c97ce4/national-lidar-programme (Accessed: 25 October 2026).
10. Hesse, R. (2010) ‘LiDAR-derived local relief models: a new tool for archaeological prospection’, Archaeological Prospection, 17(2), pp. 67 to 72. Available at: https://doi.org/10.1002/arp.374.
11. Historic England (2018) Using Airborne Lidar in Archaeological Survey: The Light Fantastic. Swindon: Historic England. Available at: https://historicengland.org.uk/images-books/publications/using-airborne-lidar-in-archaeological-survey/ (Accessed: 25 October 2026).
12. Horn, B.K.P. (1981) ‘Hill shading and the reflectance map’, Proceedings of the IEEE, 69(1), pp. 14 to 47. Available at: https://doi.org/10.1109/PROC.1981.11918.
13. Kokalj, Ž. and Hesse, R. (2017) Airborne laser scanning raster data visualization: a guide to good practice. Ljubljana: Založba ZRC. Available at: https://doi.org/10.3986/9789612549848.
14. Kokalj, Ž. and Somrak, M. (2019) ‘Why not a single image? Combining visualizations to facilitate fieldwork and on-screen mapping’, Remote Sensing, 11(7), 747. Available at: https://doi.org/10.3390/rs11070747.
15. Kokalj, Ž., Zakšek, K. and Oštir, K. (2011) ‘Application of sky-view factor for the visualisation of historic landscape features in lidar-derived relief models’, Antiquity, 85(327), pp. 263 to 273. Available at: https://doi.org/10.1017/S0003598X00067594.
16. Mark, R.K. (1992) Multidirectional, oblique-weighted, shaded-relief image of the Island of Hawaii. U.S. Geological Survey Open-File Report 92-422. Available at: https://doi.org/10.3133/ofr92422.
17. Petras, V. and Goddard, E. (no date) r.local.relief. GRASS GIS add-on manual. Available at: https://grass.osgeo.org/grass84/manuals/addons/r.local.relief.html (Accessed: 25 October 2026).
18. Yokoyama, R., Shirasawa, M. and Pike, R.J. (2002) ‘Visualizing topography by openness: a new application of image processing to digital elevation models’, Photogrammetric Engineering and Remote Sensing, 68(3), pp. 257 to 265.
19. Zakšek, K., Oštir, K. and Kokalj, Ž. (2011) ‘Sky-view factor as a relief visualization technique’, Remote Sensing, 3(2), pp. 398 to 415. Available at: https://doi.org/10.3390/rs3020398.
20. Zevenbergen, L.W. and Thorne, C.R. (1987) ‘Quantitative analysis of land surface topography’, Earth Surface Processes and Landforms, 12(1), pp. 47 to 56. Available at: https://doi.org/10.1002/esp.3290120107.
21. ZRC SAZU and University of Ljubljana (no date) Relief Visualization Toolbox in Python documentation. Available at: https://rvt-py.readthedocs.io/en/latest/ (Accessed: 25 October 2026).