Module 09 - Remote Sensing

 In module 9 we classified data gathered with remote sensing techniques in two ways: unsupervised and supervised.

In unsupervised classification, we let the software classify pixels into a number of predetermined classes. The downside of this type of classification is that number of categories can overlap. Also some vastly different features may be assigned into the same category, because the shade and tone of their pixels is identical, or nearly so. In case of my unsupervised classification, ArcMap combined water and smooth surfaces such as roof tops into one category.

In supervised classification, we determine a number of points on the raster image, and assign each point a predetermined category (grass, trees, pavement, etc.). We then let the software process all the pixels, and assign them into the predetermined categories. This is still not without issues, as my buildings category and pavement/bare ground categories got combined, but there was a lot less redundant classification.

Module 08- 3D Modeling

In module 8 we created a 3d image of subsurface soil horizons. This process involved interpolating depth data from the shovel test information to create raster files representing elevation of each soil horizon. Then, using ArcScene, we displayed those rasters in a 3d image. To make the image easier to read, we increased the vertical scale, this created a comfortable distance between layers.

When looking at the shovel test data, we split it into three separate layers, one for each horizon, and assigned each horizon a different color. In both Fig 2 and 3 yellow represents A horizon, green B horizon, and purple C horizon.

Figure 4 is missing A horizon because there was no data associated with the given shapefile. While surface data may be available, it would most likely be inaccurate, because the initial data was not gathered from a site datum point, but from the surface. And depending on the region, surface can quickly change for many reasons, such as weather, land usage, etc.

Fig 2. Shovel Test data, divided into soil horizons.

Fig 1. Project area boundaries, horizontal and vertical.

Fig 3. Proposed subsurface line in the project area.

Fig 4. Soil horizons: B on top, C on the bottom.

Module 7- Surface Interpolation

In the first part of module 7 we learned to import text and AutoCAD data into ArcMap. This usually involved converting the data into a correct table format, adding appropriate column headings, and assigning projection, if known.

In the second part of the module we learned to interpolate surface data based on known data points. This information can in turn be used to get an idea what the site looked like during the time period we are studying, or to narrow down good places for further studies of the site.

Module 06- Digitizing

In module 6 we learned to digitize old maps, and linking data tables to the shapefile's attribute table. 

First step in digitizing old maps is to georeference them, which was covered in module 5. The challenge in this exercise was in aligning independent site grids to a separate map showing the grid distribution. The problem was the poor quality of the grid distribution map, and parts of the grid were not visible and I had to interpolate the the full grid. In addition a lot of site grids were difficult to read, as a lot of notes on the maps were difficult to read, either due to poor hand writing or poor scan quality.

The second part of the exercise was to join a data table to the shapefile's attribute table. The challenge here is to create a data table from the old maps and reports that you are digitizing.

Module 05 - Georeferencing

In module 5 we learned to georeference images, historic maps in this case. Georeferencing means taking an image such as a historic map, aerial photo, etc., overlaying it on top of an already georeferenced map and adjusting it to correspond with georeferenced points.

Once you acquired a historic map or aerial photo, you need to import it into ArcMap. Also set up a background map to use as a reference. It may be helpful to import an additional background map, either street map or a topo map. This can make georeferencing easier. Then using Georeference Tool, link points on your image to the georeference background. The more linked points the better. These points may be topographical features such as island shores, hills, rivers. They may also be anthropological features: houses, roads, etc. You just need to keep in mind that a lot of these features may have changed over time.

Module 04 - Historic

In Module 4 we learned to find and incorporate historic data into maps. First part of the assignment was to find the historic data. While the historic map of Boston was provided by UWF, we used Ancestry.com to get census information about Paul Revere. 

Second part of the exercise focused on incorporating data into a map. This included creating internal and external links. External links hyperlink to Google Maps, the location in Boston with Paul Revere's house in. Internal links includes an image of a page from 1790 census, including entry for Paul Revere.

Module 03 - Ethics

In module 3 we covered the importance of ethics in archaeology. The reading points out that the need for codified ethics rules rose up from the wide spread of commercial archaeology. While I believe that is certainly not wrong, one cannot forget that until recently academia led archaeology was nothing more than glorified looting, to be shown off in the looter's national museums as a trophy. Any talk about ethics in archaeology cannot be focused on one aspect, such as CRM, but on all aspects. Academia is certainly not immune from people trying to profit from archaeological findings.

The lab for module 3 focused on creating shapefiles. This was done by either manually creating a point, and creating a shapefile out of it, or by importing a data table into ArcMap. The data table contained fields with site name, site description, and Lat and Long of the site. Once imported and converted into a shapefile, it displayed all the site in the database. When looking at the attached map, Petra site (in blue) is the manually created shapefile. All other sites come from a database that was converted into a shapefile.