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Free high-resolution satellite imagery and how to find it.

The resolution of satellite imagery is crucially important to its usefulness to the archaeologist because it directly impacts the features you can see and the precision with which you can georeference other data. For some purposes (such as overviews or larger maps) we might only need low or medium resolution imagery, but in many cases high resolution imagery is essential to our research objectives. During my recent georeferencing project, it was necessary to use the highest resolution imagery I could obtain to locate the historic maps as precisely as possible.

Unfortunately, although you can purchase high resolution satellite imagery from various providers, it is often expensive and the contract comes with quite strict restrictions regarding what you can do with it and with whom you can share it. This makes free high resolution imagery a very valuable resource for the archaeologist, although it does have limitations. There are various ways to obtain free high resolution satellite imagery, but here I compare the imagery provided by three of the most common providers Google Earth, ESRI ArcGIS World Imagery and Bing Maps. Imagery from all these providers can be accessed online in their applications, where you can also access archived imagery through Google Earth historical imagery or the ESRI Wayback app. But if you want to do much more than look at the imagery it is advisable to access it through a GIS. If you are using ESRI ArcGIS World Imagery you can access it through the basemapping layers of ArcGIS, but all three providers can also be accessed through the Contributed Services of the QuickMapServices plugin of QGIS.

Comparing imagery of Dra Abu el-Naga

Dra Abu el-Naga, at the north-eastern end of the Theban Necropolis, is a an important area where 17th Dynasty royals and Ramesside nobles were buried. It continues to be excavated by various teams, including the Djehuty Project, the German Archaeological Institute (DAI) and the University of Pisa and is the subject of several recent publications, concerning its geomorphology and landscape archaeology.

The following images compare three different open-source high resolution satellite images of Dra Abu el-Naga at the same scale. You can also see a more dynamic comparison in this video on my YouTube channel. first satellite image comes from Bing maps. It is reasonably clear at a scale of 1:2000, revealing the structures of the excavated tombs and the open shafts in front of them, but when you zoom in it becomes blurry and the features are difficult to distinguish (from 1:59 minutes in the video).

Image showing a satellite image of the northern part of Dra Abu el-Naga. Tomb structures and open shafts are relatively clear.
The northern part of Dra Abu el-Naga in the Theban necropolis, as rendered by Bing maps on 2 March 2021 in QGIS using the QuickMapServices plugin ©2021 Maxar, ©2021Microsoft.

The Google Earth satellite image is much brighter and somewhat clearer than the the Bing maps image (from 2.45 in the video). It’s worth noting that the Bing maps image appears to be older than the Google Earth imagery. The Google Earth imagery shows tombs in the bottom left corner, which are covered with debris in the Bing maps image (above).

A satellite image showing the same northern part of Dra Abu el-Naga as it appears in Google Earth imagery. The image is brighter and tomb structures and shafts are visible. More tombs are visible in the bottom left of the image where debris has been removed.
The northern part of Dra Abu el-Naga, as shown in Google Earth satellite imagery on 2 March 2021, displayed in QGIS using the QuickMapServices plugin ©2021 ORION-ME, ©2021 Maxar Technologies, ©2021Google.

In my opinion the ESRI ArcGIS World Imagery is the best of the three, although it is not as bright as the Google Earth imagery. The tomb structures and shafts are still visible, but the imagery is sharper and easier to understand (from 4:10 in the video). It also stands up to zooming better than either the Bing maps or the Google Earth imagery. It’s worth noting that you may need to use ArcGIS to export ESRI World Imagery. Although its possible to view it in QGIS, it failed to export as an image.

Image of the northern part of Dra Abu el-Naga showing tomb structures and shafts. The image is of a good contrast, recent and shows the features well.
The northern part of Dra Abu el-Naga as shown by ESRI ArcGIS World Imagery on 2 March 2021, displayed in ArcGIS 10.

Limitations of free imagery

Bing, Google and ESRI do not own their own satellites, instead they provide imagery from commercial and government sources. These free high resolution images will not be as good as if you purchased them for yourself, but provided we’re aware of the limitations they can still be incredibly helpful.

The first problem with these images is that they are often provided without metadata, so we don’t know which satellite took them or when. Nor do we know the precise resolution, whether the image is pan-sharpened or which electromagnetic bands are included. Based on how clear they appear I would guess that all the images in this blog post have a resolution of 30-60cm, with the Bing maps image being the lowest resolution and the ESRI image the highest. But it is just a guess. Similarly I believe the Bing image is older than the Google Earth and ESRI images, based on the greater exposure of archaeology in the latter, but I cannot say precisely from the imagery.

Another difficulty with free imagery is that it is updated by the provider intermittently. An image that covered your site last year might have been replaced by now with a less useful version, perhaps with cloud cover, dust or an error in georeferencing. Even if there isn’t an obvious error or kink in the georeferencing, you may find that the new image doesn’t match the rest of your data as well. Global imagery providers use a global coordinate system to display satellite imagery, which may be different from the local coordinate system and projection you are using. As a result you may find a feature does not appear in exactly the same location in the new satellite image as in the old one. The difference is not likely to be large and may not be significant for your project, but if you are using free high resolution imagery for survey or other precision tasks, a shift of a few metres could represent a serious problem.

A lot of the value of high resolution satellite imagery is in the multiple multi-spectral bands provided and the opportunities for raster analysis and pan-sharpening. Free high resolution imagery does not provide access to the individual bands, permit bands to be recombined or allow for raster analysis. While such imagery can form a useful basemap for display or georeferencing, it isn’t suitable for various remote sensing applications or analyses.

Don’t forget to reference

Referencing your satellite imagery is just as important as citing written sources, and perhaps more so, because the ‘fair use’ carve outs are much less clear and tested with this relatively new type of data. ArcGIS provides relatively clear instructions on citing their products. ArcGIS, Bing and Google Earth programmes watermark downloads, but these watermarks may not be included when using 3rd party software, such as QGIS. You may therefore need to check relevant information for how to cite Bing and Google Earth maps in your captions. You may also need to include acknowledgements or further references depending on the terms of service.

Acknowledgements and References

The first two images in this blogpost were created in QGIS using Bing and Google Earth satellite imagery respectively. The third image was created using ArcGIS® software by Esri. ArcGIS® and ArcMap™ are the intellectual property of Esri and are used herein under license. Copyright © Esri. All rights reserved. For more information about Esri® software, please visit http://www.esri.com.

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Finishing the map, georeferencing the pyramid of Djedefre

In a previous post I described how I georeferenced a difficult map of Abu Rawash. During that process I had to ignore the pyramid of Djedefre because it was drawn at a different scale to the rest of the map. Here and in this video I discuss how I subsequently georeferenced the pyramid of Djedefre at the correct scale.

The map of the pyramid of Djedefre was cropped from map I in Porter and Moss’ (1932) Topographical Bibliography volume IIIi, which is featured in my previous post.

Comparison of the angle of the causeway after accurately georeferencing the pyramid (left) and the angle of the causeway in the satellite imagery (right). Map cut from Porter and Moss 1932, volumne IIIi, map I.

First, I identified the archaeological features in the map and the satellite image. Although the pyramid is very clear in the satellite imagery, this process was complicated by the long ramp or causeway heading north from the pyramid. Initially I assumed this was the pyramid’s causeway to the Valley Temple, but the angle of this feature in the map, and the angle in the satellite imagery were different. This made me wonder if the feature I could see in the satellite imagery was some kind of recent Decauville track for removing spoil from the pyramid, and the actual causeway ran at a different angle and had been removed. Having georeferenced the map I think the feature is probably the pyramid causeway in both cases, the angle in the map being incorrect due to the differences in scale between the drawing of the pyramid and the rest of the map. If you review the image of the georeferenced map in my previous post you will see that the end of the causeway as drawn in the map lines up with the end of the feature in the satellite image, even though the pyramid is incorrectly drawn. This suggests that the angle of the causeway became misaligned when the pyramid and the rest of the map were joined together. Nevertheless I chose to ignore the causeway when georeferencing the pyramid, because its questionable accuracy would make georeferencing more difficult and it was readily visible in the satellite image anyway.

I then scaled the image to the correct scale to align it to the satellite imagery (from 1.20 minutes in the video). As I note at 4.59 in the video, one thing to be aware of when georeferencing maps is that the lines of the map occupy space within the GIS – so the line of the enclosure wall of the pyramid complex represents 3m on the ground after georeferencing. This can make it difficult to align the map with satellite imagery, particularly if the map only covers a small area and/or is cropped from a much larger map.

Once I determined approximately the correct scale (1:2250) I began linking the ground control points in the map and satellite imagery (from 4.15 minutes in the video). This revealed further inaccuracies and forced me to make decisions about which points in the map I believed were more accurate than others. In this previous post I discussed the importance and limitations of RMSE. The georeferencing of the map of the pyramid of Djedefre really emphasises how RMSE and residuals can be used to improve georeferencing, and also the limitations of the process. I used the RMSE and residuals, combined with the visual position of the map on the satellite image, to test the ground control points (from 10.08 in the video). They rapidly revealed that parts of the pyramid complex had been drawn inaccurately in relation to each other. After noting that the satellite pyramid and south-west corner of the enclosure were in dashed lines, I opted to set the ground control points elsewhere as it seemed likely that the satellite pyramid was more speculatively drawn. Testing various ground control points also revealed that the enclosure wall around the complex was drawn closer to the pyramid than it really is, forcing me to chose whether to include the complex enclosure wall in the ground control points or concentrate on the pyramid. I chose to focus upon the pyramid and mortuary temple, and rectified the map with an RMSE of 3.59, which was an improvement on a previous attempt, but still far from the 0.75m RMSE which would represent the 1:3000 ideal (Conolly and Lake 2006, 82-83). The inaccuracy in the map, its scale and the resolution of the satellite imagery are all contributors to this high RMSE. Depending on what I need to do with the map, I may seek out a more recent map or re-georeference it. Georeferencing a map this small, with this many inaccuracies, to satellite imagery, is always going to be difficult and likely to produce a high RMSE.

A satellite image of Djedefre's pyramid complex overlaid with the plan from Porter and Moss 1932, map I.

Acknowledgements and References

Conolly, J. and Lake, M. 2006. Geographical Information Systems in Archaeology. Cambridge.

Porter, B, and Moss, R. 1932, Topographical Bibliography of Ancient Egyptian Hieroglyphics, Texts, Reliefs and Paintings III: Memphis 1. Abu Rawash to Abusir. Oxford.

Maps and images throughout this blog post were created using ArcGIS® software by Esri. ArcGIS® and ArcMap™ are the intellectual property of Esri and are used herein under license. Copyright © Esri. All rights reserved. For more information about Esri® software, please visit http://www.esri.com.

All the satellite imagery used is ArcGIS World Imagery. Sources: Esri, DigitalGlobe, GeoEye, i-cubed, USDA FSA, USGS, AEX, Getmapping, Aerogrid, IGN, IGP, swisstopo, and the GIS User Community.

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Errors, inaccuracies, resolution and RMSE: Georeferencing a difficult map of Abu Rawash’s pyramid and cemeteries

In a previous post I introduced the georeferencing work I was doing, with a video of me georeferencing Porter and Moss’ map of the Cemetery F mastaba field at Abu Rawash. Here I delve into the process a little more, with help from a further video, which shows me georeferencing a more difficult map of Abu Rawash using ArcGIS basemap World Imagery.

The map I am georeferencing in those videos is map I in Porter and Moss’ (1932) Topographical Bibliography volume IIIi. It shows the entire area of Abu Rawash from the pyramid of Dejedefre, to the north-west cemetery in Wadi Qaren and the village of Abu Rawash on the edge of the cultivation.

Map of Abu Rawash showing the pyramid to the south-west, and various cemeteries in the desert around.
Map I from Porter and Moss’ 1932, Volume IIIi, of the Abu Rawash area.

Accuracy and precision.

When working through the georeferencing process, its important to carefully consider the precision and accuracy you are aiming for, taking into account likely distortions in the image to be georeferenced; the resolution and accuracy of the data (the satellite imagery) you are georeferencing with; and the ultimate function of the georeferenced image.

All data, even GCP collected on site with differential GPS, have some level of error in them. What matters is that they are sufficiently accurate and precise for the task you have in mind. Accuracy and precision are also different. Accuracy refers to whether something is correct. In other words, is the map you are georeferencing in the right place? Precision is easiest to think of as resolution or the level of detail. Something can be very precise but very inaccurate, or something can be very accurate and very imprecise. It is accurate to say I live in the United Kingdom, but it is not very precise. It is precise to say I live in N7 6RY (A postcode in Finsbury Park, London) but that is not accurate – I do not live there any more.

The accuracy of the georeferenced image can be affected by drafting or composing errors in the original map, or by distortions introduced during printing or digitising. Such inaccuracies and distortions affect how well the map can be overlaid on the satellite imagery. The satellite imagery can also contain distortions. Gross and obvious distortions, like the kinks in the Deir el-Bahri temples I published in a previous post and distortions due to the angle of the satellite to the ground affect the georeferencing process.

As with accuracy, the precision of the georeferenced image is affected by the precision of the map we are georeferencing, and the resolution of the satellite imagery. If the map is sketchily drawn or details are missing this may make it more difficult to locate precisely. The resolution of the satellite imagery (or any other ground control data) also affects the precision of the georeferenced image. Georeferencing requires that we line up the map with the same features in the satellite image. The more precisely a feature appears in the satellite image, the more precisely we can locate the map we are georeferencing. The pixel size (resolution) of the satellite imagery therefore places considerable limits upon the precision of the georeferenced image.

Locating the archaeological features at Abu Rawash

It feels like it ought to be easy to identify the pyramid of Abu Rawash and associated cemeteries. After all, pyramids are not known for their discretion, particularly once they’ve been excavated. While the pyramid of Abu Rawash is pretty clear in the satellite imagery, the huge amount of quarrying and agricultural and housing development in the Abu Rawash area made it difficult to identify the geographical and archaeological features in Porter and Moss’ 1932 map. The Survey of Egypt 1:25,000 scale map of 1942 shows how little development had taken place 80 years ago.

Map of the Abu Rawash area from 1942 showing minimal modern development in the desert.
Abu Rawash in 1942 (Survey of Egypt 1:25,000 scale map of Kirdasa).

In contrast the modern satellite image shows the pyramid and cemeteries as islands of archaeological landscape in a highly developed area.

Image of the Abu Rawash area showing considerable quarrying and development around the pyramid and cemeteries.
The area of Abu Rawash today, note the considerable development and quarrying in the area.

This made it more difficult to relate Porter and Moss’ map to the satellite image, although the preservation of the pyramid and the cemeteries did help (see from 0.35 minutes in the video).

Scaling the map for georeferencing

Once we identify the area, we need to scale the map to fit that area in the satellite imagery. You can see me undertaking this task from 1.10 minutes in the video. During the process, I discovered an inaccuracy in Porter and Moss’ map – the pyramid of Djedefre had clearly been drawn at a different scale to the rest of the image. Drafting and composing inaccuracies of this type are frustrating but do occur with historic imagery. Other sources of inaccuracies include distortions introduced during the scaling of maps for publication and when publications are scanned or photographed to generate digital images. Photography is particularly problematic as the camera lens needs to be parallel to the image to avoid distortion, but even scanning can produce minor inaccuracies. Dealing with these inaccuracies often means adjusting the georeferencing, splitting an image or ignoring part of the map during the georeferencing process. In this case I chose to georeference the map, while ignoring the pyramid and subsequently cropped out the pyramid and georeferenced it separately.

Adding control points (GCP)

Once Porter and Moss’ map had been scaled to approximately the right scale, it was aligned more precisely to the satellite imagery using ground control points (GCP). These appear in ArcGIS as ‘Links’, and operate essentially as pins. You select a point in the map and then select the same point in the satellite image and ‘pin’ them together. You can see me undertake this process from 7.20 minutes in the video. Ideally, it would be possible to locate these links very precisely in each set of data, but in this example, we are constrained by the contents of Porter and Moss’ map, which does not include many clear points that can be related precisely to points in the satellite imagery. The resolution of the satellite imagery is also a factor. The ArcGIS Basemap World Imagery uses a variety of satellite imagery sources, but the highest resolution of any commercial satellite imagery is currently c. 30cm and much of the imagery is likely to have a resolution of c. 40-50cm or more. This means that the pixels of the satellite image represent 40-50cm on the ground. Any feature smaller than that is invisible, and features that are only slightly larger are difficult to identify. Another effect of the satellite imagery resolution is that when we zoom in close the satellite imagery appears blurry, and a point becomes more difficult to locate than when zoomed out (you can see the effect of this from 8.45 in the video).

Root Mean Square Error (RMSE)

Once we have added four links in ArcGIS, we can open the link table and see a RMSE for the entire map in the top box and the residuals for each point in the right column of the table. Turning off links or adding new links will alter the position of the map and the RMSE accordingly (from 10.30 in the video). The RMSE represents ArcGIS’ calculation of the fit between the actual and desired link positions (Conolly and Lake 2006, 82-83). In simple terms ArcGIS uses the first three links to estimate where it thinks any further links should be. It then calculates the residual for each point as the difference between where you placed a link and where the map ended up based on the other links that have already been placed. The RMSE is the product of all the residuals. Although RMSE is useful, it’s important to recognise that it is reliant upon the accuracy and precision of the map and the satellite imagery. If there are inaccuracies in either, they will increase the RMSE. It is also reliant upon the locations and positioning of the points you choose. The old adage of ‘junk in, junk out’ definitely applies and it is entirely possible to have a low RMSE and a very inaccurate and imprecisely positioned map. So while you can reduce your RMSE by removing links with high residuals and adding new links, it is sometimes better to accept a higher RMSE and keep an important link, recognising that the higher RMSE is due to inaccuracies in the map. Alternatively, it may be necessary to chose which ground control points you believe are more accurate and only link to them.

We aim for an error of less than 1:3000 so for an original image at a scale of 1:15000 an RMSE of under 5 (i.e. 15000/3000) is ideal (Conolly and Lake 2006, 82-83). Ideally we would use the scale given in the original image, but Porter and Moss do not include scale information so we have to work with the scale we established during georeferencing. When I scaled this map I settled on a scale of 1:9000, so any RMSE under 3m would be very acceptable. Here our RMSE is slightly above 3m, which is not unreasonable given the inaccuracies in the map and the difficulty of locating very precise control points due to the resolution of the satellite imagery and changes to the landscape. I subsequently repeated the georeferencing and obtained an RMSE of 2.88, but reducing the RMSE by a large amount is not always possible depending on the scale and accuracy of the map, and the resolution of the satellite imagery. The map of Cemetery F, for example was at a scale of just over 1:500, meaning its RMSE should be 0.16m or under, but I was only able to get it to 0.3m. Nevertheless, under the circumstances that is acceptable because of the resolution of the satellite imagery, which makes it impossible to place a point more precisely than within 0.3m. This is compounded by the imprecise edges of certain archaeological features in the satellite imagery, such as the mastabas of Cemetery F or the satellite pyramid of Djedefre, and any inaccuracies or distortions in the maps. In such cases it is important to be aware of known inaccuracies and distortions in the map and satellite imagery or you can be driven to distraction trying to get inaccurately positioned features to line up.

Ideally, if the RMSE is too high and cannot be reduced, we would seek an alternative source of data, but such data does not exist for some of these sites. In those cases it is much better to have a slightly less than ideally georeferenced map, than none at all. It is also important to be aware of the purpose of your georeferenced map. In this case the relatively modest aim was to locate archaeological features to within 10m, which is achievable with the accuracy of the maps and the resolution of the satellite imagery.

Overall I was satisfied with the georeferencing of the Abu Rawash map. It was a very difficult map to georeference; hard to locate due to the changes to the landscape; difficult to scale due to the inaccuracy in the pyramid; and difficult to find enough precise features to use as GCP links . Nevertheless, the final georeferenced version gives useful insight into the archaeological landscape. With careful thought and reference to the underlying satellite image, it will be possible to locate any relevant archaeological features during the rest of the project.

A map of the Abu Rawash area, overlying a satellite image. The pyramid is clearly at the wrong scale and angle compared to the rest of the image.
Final georeferenced version of Porter and Moss’ 1932 Volume, IIIi, map I of Abu Rawash.

Acknowledgements and References

Conolly, J. and Lake, M. 2006. Geographical Information Systems in Archaeology. Cambridge.

Porter, B, and Moss, R. 1932, Topographical Bibliography of Ancient Egyptian Hieroglyphics, Texts, Reliefs and Paintings III: Memphis 1. Abu Rawash to Abusir. Oxford.

Maps and images throughout this blog post were created using ArcGIS® software by Esri. ArcGIS® and ArcMap™ are the intellectual property of Esri and are used herein under license. Copyright © Esri. All rights reserved. For more information about Esri® software, please visit http://www.esri.com.

All the satellite imagery used is ArcGIS World Imagery. Sources: Esri, DigitalGlobe, GeoEye, i-cubed, USDA FSA, USGS, AEX, Getmapping, Aerogrid, IGN, IGP, swisstopo, and the GIS User Community.

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Wonky Giza pyramids: Oblique satellite imagery and georeferencing

I’m currently working on a project georeferencing (or georectifying) a lot of historic maps published in Porter and Moss’ Topographical Bibliography. I’m georeferencing these maps with ArcGIS basemap World Imagery and as a result have spent many days looking at satellite images of Egypt.

Satellite imagery is a hugely valuable resource, but it can be misleadingly precise. One feature of satellite imagery that isn’t immediately obvious is the problem of parallax. Parallax is the displacement of an object when seen from different positions. It’s incredibly useful in astronomy, but more of a problem in geodesy. Maps provide a vertical view of surface of the earth, flattened onto a flat plane below the imaginary godlike viewer. Satellites (and aeroplanes) fly across the curving surface of the globe taking images as they move. This means that some or all of the each satellite image is taken from an oblique angle and that can produce parallax.

The parallax is really clear in a georeferenced map of the Giza pyramids. In the satellite image below the points of the three Giza pyramids are to the north-west of the points in the overlaying georeferenced map. This is because the satellite was at a slightly oblique angle to the ground of the Giza plateau when the image was taken. As a result, when I georeferenced this map I had to be careful to line up the map with the corners of the pyramids to ensure the best accuracy. If I had used the tops of the pyramids my map would have been misaligned.

Map of the Giza pyramids overlying a satellite image of the area.
Georeferenced map of the pyramids of Giza, overlaid on the ArcGIS basemap satellite imagery. Note how the tops of the pyramids in the satellite image are offset to the north-west compared to the map. (Map III of Porter and Moss 1932, Volume IIIi)

Acknowledgements and References

Porter, B, and Moss, R. 1932, Topographical Bibliography of Ancient Egyptian Hieroglyphics, Texts, Reliefs and Paintings III: Memphis 1. Abu Rawash to Abusir. Oxford.

Maps and images throughout this blog post were created using ArcGIS® software by Esri. ArcGIS® and ArcMap™ are the intellectual property of Esri and are used herein under license. Copyright © Esri. All rights reserved. For more information about Esri® software, please visit http://www.esri.com.

All the satellite imagery used is ArcGIS World Imagery. Sources: Esri, DigitalGlobe, GeoEye, i-cubed, USDA FSA, USGS, AEX, Getmapping, Aerogrid, IGN, IGP, swisstopo, and the GIS User Community.

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Shifting mastabas: Georeferencing a plan of a Fourth Dynasty Egyptian mastaba cemetery, at Abu Rawash.

I am currently working on a project to georeference (or georectify) maps of various Egyptian sites from Porter and Moss’ Topographical Bibliography (which can be found online at this Griffith Institute website). Georeferencing is something of a Cinderella job in geographic information systems (GIS) work – its important, but is often ignored in favour of more exciting methods and results. So for those who haven’t had the (sometimes dubious) pleasure of georeferencing a map for themselves, I’m making some videos of the process and uploading them to my own YouTube channel. The first video is available now and features me georeferencing a cemetery at Abu Rawash, north-west of Cairo.

Abu Rawash

Abu Rawash is the site of the pyramid of Fourth Dynasty Pharaoh Djedefre with cemeteries dating from the Early Dynastic period onwards. Cemetery F, like the pyramid, dates from the Fourth Dynasty and contains the high status mastaba tombs of a number of important royal courtiers. The outlines of these mastabas remain visible in the satellite imagery, with their burial shafts appearing as black marks in the centre of the structure.

Cemetery F, as it appears now in satellite imagery. The outlines of the rectangular mastaba tombs are clearly visible, most with two burial shafts in the centre.

Cemetery F was excavated by Bisson de la Rocque, and it is his plan that Porter and Moss include as Map II[1] of volume IIIi of the Topographical Bibliography:

Plan of Abu Rawash Cemetery F aligned and scaled to the mastaba field in the satellite image. (Published in Porter and Moss, 1932, MapII).

Georeferencing

Georeferencing is the process of taking an image and providing it with coordinates that allow the image to be correctly positioned in relation to other geographic data. Most of the historic sketches, excavation and survey plans made by generations of past archaeologists exist as published images. Georeferencing those images is often the first task in collating archaeological data and relating it to modern maps, survey data and satellite imagery.

My task was to use the GIS to locate Porter and Moss’ plan on the satellite image of the mastaba field, allowing, me to obtain geographic coordinates for any of the tombs within it. The georeferencing process I used divided into 3 parts: locating the archaeological features from the Porter and Moss map in the satellite imagery from 2:07 in the Cemetery F video); scaling the Porter and Moss map to the approximately the correct scale (from 2.55 in the Cemetery F video); and then using ground control points (GCP) to link locations on the Porter and Moss map to the same points in the satellite imagery (from 4.30 in the Cemetery F video). This task was complicated by the lack of scale in Porter and Moss’ (1932, Map II) published image (the scale in the image above has been added by me after georeferencing) and the resolution of the satellite imagery, which makes precise location of ground control points difficult at these scales. Nevertheless, the mastabas were relatively obvious in the satellite imagery and georeferencing was therefore easier than it might have been.

The video of me georeferencing mastaba Cemetery F at Abu Rawash, is now available on my YouTube channel and the next image shows the finished project, with the map from Porter and Moss overlaid on the satellite image from the ArcGIS basemap World Imagery layer.

Porter and Moss’ 1932 Map (II[1]) of Cemetery F at Abu Rawash, georeferenced and overlaid upon the mastabas as they appear today in the satellite imagery.

Acknowledgements and References

Porter, B, and Moss, R. 1932, Topographical Bibliography of Ancient Egyptian Hieroglyphics, Texts, Reliefs and Paintings III: Memphis 1. Abu Rawash to Abusir. Oxford.

Maps and images throughout this blog post were created using ArcGIS® software by Esri. ArcGIS® and ArcMap™ are the intellectual property of Esri and are used herein under license. Copyright © Esri. All rights reserved. For more information about Esri® software, please visit http://www.esri.com.

All the satellite imagery used is ArcGIS World Imagery. Sources: Esri, DigitalGlobe, GeoEye, i-cubed, USDA FSA, USGS, AEX, Getmapping, Aerogrid, IGN, IGP, swisstopo, and the GIS User Community.

Global Xplorer: Satellite remote sensing, looting and crowd-sourcing.

On 30 January of this year, Sarah Parcak, winner of the 2016 TED Prize launched the Global Xplorer platform she has created with her prize money. Like the many archaeological crowd-sourcing  projects on the Micropasts website, Global Xplorer is a crowd-sourcing platform allowing members of the public to take part in archaeological satellite remote sensing from their laptop, phone or tablet.

The heady combination of Sarah Parcak, National Geographic’s own ‘Space Archaeologist’, a TED prize, archaeology and satellite technology has prompted a number of media outlets to report on Global Xplorer, from Forbes to The Guardian. All this publicity means that interested members of the public will soon be working through the imagery on the platform.

But the thought of anyone with a computer logging on to archaeological sites has not been universally welcomed. This recent article on the Cairo Scene website, which has been publicised on social media by the Egyptian Cultural Heritage Organisation, argues that Global Xplorer could be used by looters to identify targets, making the situation worse in countries where protection for antiquities is limited. As someone who works with satellite imagery, I decided to test out Global Xplorer and see if these concerns are justified and provide general review of platform.

Global Xplorer is a straightforward platform. There are several pages of information about the project with videos from Sarah Parcak. Archaeological and cultural details of the countries covered can be found under ‘Expedition’, and there are also areas for donations and FAQs. So far only data from Peru has been included on the platform.

Before you can begin working on satellite imagery you need to register, giving details such as name, email address and a password you generate. Then there is a tutorial explaining briefly what natural and archaeological features look like in satellite imagery and how to identify evidence of looting and avoid false positives. Once you’ve finished the tutorial you begin working on the tiles.

The first goal for users of Global Xplorer is to identify evidence of looting. You won’t be creating a map or identifying archaeological features, but locating traces of antiquities theft for further investigation. Following the tutorial you’ll be shown a 100x100m tile of satellite imagery. The area you need to examine is outlined in white, with a little bit of additional imagery greyed out around the edges to provide some extra context. Depending on whether you can see any evidence of looting or not, you click either the ‘Looting’ or ‘No looting’ buttons and the next tile loads. As you can see I appear to have ended up with a bit of amazon rainforest:

global_xplorer-interface
The Global Xplorer interface.

It’s pretty clear that it would be almost impossible for tomb robbers or antiquities thieves to make use of Global Xplorer to further their nefarious activities. In addition to the off-putting effect of registration,  the user only sees a very small area at any given time, and it is entirely divorced from any geographic context. The FAQs confirm my assumption that the tiles have no coordinates or other geographically identifying data, and the tiles you are shown appear in a randomised order so you couldn’t even associate what you’ve seen in the previous tile with what you see in subsequent ones. Within the tiles there’s very little information to assist you in identifying the location. Even if a pristine archaeological site appeared inside that white square, at best you might be able to discern it was in the rainforest, in a field or in the desert and next to a building, road or river, but the sheer number of possible locations for each tile is immense. In fact the only way looters would be able to recognise an archaeological site is if they had already been there and were familiar with the terrain, and then we can hardly blame Global Xplorer for the looting.

On the other hand Global Xplorer is quite good fun. It works on your phone or tablet, so you can cover a couple of tiles while waiting for the bus/train/plane. It’s very easy and straightforward and quite relaxing in a strange way. While currently the goal is to identify looting, the ‘Current Campaign’ menu at the bottom of image above suggests that users will move on to identifying ‘Encroachment’ and ‘Discovery’ as the programme rolls out.

So if you have a few minutes and fancy trying it out, its straightforward to learn and easy to use, and you certainly don’t need to worry about antiquities thieves learning anything useful.