Remote Sensing in Archaeology: Monk's Mound, Cahokia

Cahokia Mounds
     The Cahokia Mounds are all that remain of a once thriving city in North America located in Collinsville, Illinois. Inhabited between 600 - 1400AD (during the late Woodland/early Mississippian periods), the site at its peak boasted a population of 10,000 to 20,000 people. It originally consisted of more than 100 earthworks and mounds but only about 80 currently remain.
     The cause for the site's eventual abandonment is unknown but it was in decline around a century before Europeans arrived. What was once the largest prehistoric Native American settlement north of Mexico is now situated amidst modern development.
     The mounds are designated a National Historic Landmark and a UNESCO World Heritage site. Monk's Mound is the largest mound in the complex. For this assignment, we performed two different types of raster classification in ArcMap. We visualized Monk's Mound after these classifications to see how they are classified.

Unsupervised Classification
Below is the map end product generated from running an unsupervised classification in ArcMap. There is a fair amount of confusion between the classes (for this assignment we used 8) with vegetation being represented by 5 of the 8 classes. Monk's Mound is classified as urban or bare earth.

A map of an unsupervised classification performed on raster data
acquired from USGS for the Cahokia site in Illinois. 

Supervised Classification
Here is the map end product of running a supervised classification for the same image. Instead of telling the program to derive the classes, samples were used to create a signature file. These signatures were in turn used to classify the raster. In this classification, I attempted to use 6 classes to separate the raster pixels. There is plenty of error in that dark features (like water and shadowed trees) are lumped together. Trees are not captured well either and it the classification makes it seem like there are less than there really are. Here, like the previous unsupervised classification, Monk's Mound is classified as an urban/road feature again.

A supervised classification performed on raster data
acquired from USGS for the Cahokia site in Illinois. 

3D Modeling of Shovel Test Data

     This week's assignment focused on learning how to manipulate archaeological data in ArcScene (a 3D environment). To prepare data for ArcScene, shovel test data was examined in ArcMap. Geological surfaces were rendered/interpolated using the IDW (inverse distance weighted tool). These surface were used to make the map you see below. The shovel test data was also imported into ArcScene and we used the Base Height tab and the Extrusion tab to project the 2D data into 3D space.

A simple map showing three interpolated surfaces derived from shovel test data. 

     Using the Fly tool (link) and Animation tool (link) I created a video that travels through the shovel tests. While not essential to understanding this data it is a neat way to visualize and interact with it. (Bonus: these types of visuals can also be used to enhance a presentation.)

     This assignment brought together several of the skills we have learned throughout the semester and helped prepare us for the final project. As a continuation of this theme, our discussion post focused on the application of 3D technology in archaeology. I mention this because you may have fun exploring some of the sites I found, CyArk, MayaArch3D, a Roman statue base, and other tech summary sources. Try to contain your excitement :).

Surface Interpolation Techniques - Examining Patterns In Archaeological Data

     This week our lab introduced surface interpolation and kernel densities as a means of examining, analyzing, and interpreting patterns in archaeological data. We used shovel test data and (insert PArt 2 data description) data to practice the application of these techniques. The tools used are all part of the Spatial Analyst extension. I used the kernel density, IDW (Inverse Distance Weighted), kriging, spline, and natural neighbor interpolation tools to see how they each visualize the same dataset. Below is a poster that shows these methods applied to two datasets mentioned above. In addition, here is a helpful link for a discussion of the interpolation tools I noted and that are offered in the Spatial Analyst extension.

A 'poster' showing the various interpolation methods used to examine two sets of data. 

Digitizing Archaeological Data - Settlement Survey in Oaxaca, Mexico

     For this lab, data from a settlement survey of the Oaxaca Valley in Mexico was provided to us (by way of scanned chapters and appendices) and each student was assigned units of this survey to digitize. The survey provided land cover data in conjunction with occupation/settlement data (determined through analysis of collected artifacts - like pot sherds). All of this information needed to be digitized and overlaid on the georeferenced topographic map.
    Gathering the data was quick since the maps and information were scanned and provided to us. To prepare the imagery for use in ArcMap I copied and pasted the images of "my" maps into paint and edited them to remove extraneous white space. Georeferencing all of the data was time consuming. Additionally, digitizing also took longer than expected.
     At first, the georeferencing part of the lab went smoothly. I georeferenced a grid map of Oaxaca Valley after a good bit of analysis of the modern topography of the valley. The image gets quite pixelated when zooming in so I had to find a balance between scales to guide alignment and referencing. I then georeferenced the images of my unit only to realize that my original topography, in the area of my assigned units, was skewed to the east. I realized that this resulted from my methodology for georeferencing. I went for overall map accuracy while I should have been seeking accuracy in the relatively small area of my units. Thus, I went back to the drawing board and georeferenced the grid map with emphasis on accuracy in my given area. With better accuracy in my region, I felt confident georeferencing all of my unit squares.
     With the data in my maps georeferenced I went ahead and began digitizing my data. Through the course of digitizing I got very comfortable with the Editor toolbar and the Snapping toolbar. Some of the images became skewed after georeferencing making them difficult to interpret (along with their pixelation). Some numbers were illegible so I had to keep the original data handy for reference. [A quick side note, this assignment made me wish for multiple monitors. I think it would have relieved some of the burden of minimizing windows and managing many windows at once.] Once I finished digitizing all of the data and began to compile maps I noticed that I had some errors. For instance, when I placed the occupation data on top of the land cover data there were alignment issues. Hopefully, for learning purposes these errors are not egregious. In a more rigorous situation (work or publications) I would have spent much more time on this lab. As it stands, this assignment took two weeks to finish. I helped a coworker georeference a map from the 1930s and it took about 45 minutes. It was, however, less challenging data and required no digitizing.
     I provided all the maps I compiled to complete the assignment. One of my units had several maps (unit N2E3A-C) because many time periods were encompassed by the area. I tried to visualize all of the data efficiently hopefully you think so too.

Map 1 - An Overview of Oaxaca Valley
showing the location of my assigned units.

Map 2 - A map showing the same unit split into multiple
occupational periods overlaid upon landcover data. 

Map 3 - A map showing the same unit split into multiple
occupational periods overlaid upon landcover data. 

Map 4 - A map showing an additional unit (adjacent to the one in the previous maps)
overlaid upon landcover data. 

 
   

Historic Maps - Georeferencing

     This week we continued using historic maps but took it a step further. Instead of being provided with a previously georeferenced map we performed that task ourselves. The data for this assignment came from the David Rumsey Map Collection. Specifically, I used the Geographical Searching with MapRank Search to find an historic map of Macau. The map was authored by William Bligh (1754-1817) and James Cook (1728-1779) and published as part of a collection of maps detailing the explorations undertaken during Cook's voyages. The links provided presents more information about the publication and the men themselves. 

Georeferencing

After acquiring the map it was cropped to eliminate irrelevant portions of the image (like the pages and cover). The newly edited image was imported into ArcMap and georeferenced. The historic map shows a much different landscape than that we see for modern Macau. This made the search for control points a challenge. In addition, the historic map was inaccurate (things seemed to align fairly well vertically but were off horizontally). Some features, however, are still present on both maps, like Illa Verde. At any rate, once I had enough control points (n > 10) and a reasonable RMSE (considering time management on the lab), I used a spline transformation to acquire the georeferenced image you see below. The map deliverable shows the georeferenced historic map (40% transparency) over aerial satellite imagery for Macau, China. 

The map deliverable showing the georeferenced
historic map of Macau displayed atop aerial imagery.

    A quick note, if you have some spare time to peruse old maps then let me recommend the site I referenced earlier. The David Rumsey Map Collection is chalk full of neat ways to visualize historic maps. They have georeferenced historic maps displayed on Google Earth where you can compare historic and modern map images. Additionally, they have a 3D GIS Viewer in which historic maps are combined with DEM from the same area to make a 3D historic image. Tell me that doesn't pique your interest. Explore the rest of the site because I am only touching on a couple of the incredible things you can distract yourself with.

Historic Maps - Paul Revere

     Archaeologists often deal with historic maps and make use of them in their research. These maps are helpful in the reconstruction and interpretation of a landscape in that they can be integrated with GIS. This module serves as an introduction to the usefulness of historic maps as well as how to find historic map data. 

     The deliverable displays a historic map of Boston with the location of Paul Revere’s house. In addition, a portrait of Revere and an original census record listing Paul Revere are included. An incredibly brief biography helps to provide some background for the man himself. A note on design, I liked the look of the historic map of Boston and chose to highlight it in the foreground but also altered the display transparency to present it as a backdrop for the main map. I symbolized the location of Paul Revere’s house with a patriotic, red star and added callouts in an “antiqued” look to comply with the historic theme of the map. 

A map showing historic Boston and the location of Paul Revere's home.

     The data for this map came from several sources. Ancenstry.com provided the image of Paul Revere and the census record from 1790. (This data is free to access during a two week trial after which there is a monthly subscription fee). A base map of modern Boston (not displayed on the deliverable) came from some searching on arcgis.com. It is important to consider the availability of historical data. To protect the integrity and security of the locations, much historic data is not readily, freely available. The historic map was provided to us for this assignment but there are some other sources for data like the USGS which has aerial photos from the mid-twentieth century available. There is, of course, also the library. Georeferencing historic maps is covered in the next module. 

Ethics in Archaeological GIS -- Archaeological Sites in Jordan

     This week we discussed ethics in archaeology (see the section below for a brief discussion), the importance of data security, and site conservation. As looting is a significant problem in the archaeological world it is vital that steps are taken to ensure the preservation and conservation of our collective history. Certain institutions, like the Getty Conservation Institute, have created web-based systems for assessing the condition and maintenance of archaeological sites. MEGAJordan (Middle Eastern Geodatabase for Antiquities) is one such site and it uses GIS to manage and inventory archaeological sites in Jordan. There is an introductory video along with several other tutorials that discuss how to navigate and utilize the site. (It is pretty nifty. I imagine there will be similar GIS systems available for every country eventually.)
     For this week's assignment we were given a list of archaeological locations in a spreadsheet. The MEGAJordan search function was used to gather coordinates to populate the spreadsheet. This data was then imported into ArcGIS as a feature class in a file geodatabase. The map below displays these locations. I also included a screen capture of a search for the site of Petra. It shows the user interface and some of the features of the MEGA Jordan GIS.

Map deliverable showing
archaeological sites in Jordan.

A screenshot showing the UI for the MEGA Jordan site. 

     To facilitate the discussion of ethics in archaeology we read two articles. One written by Brian Fagan - "The Arrogant Archaeologist" - and another that summarized the necessity for and the development of principles in archaeology (SAA link below). In short, the need for public outreach and education concerning the treatment of not only artifacts but also place is as important now as it ever was. Thanks to social media I am able to follow several archaeological outreach programs (such as the Florida Public Archaeology Network). I try to share as many events as I can.

Some Professional Codes and Standards

• Society for American Archaeology
• Society for Historical Archaeology (navigate to the bottom of the page for links and information on other professional society statements and blogs)
• Register of Professional Archaeologists