FieldWork 2016
This page should focus only on what students and Dr. Carter did during the 2016 iteration of Field Archaeology. Content about charcoal, etc. should be on other pages.
Possible headers:
Purpose of the work
In 2016 during the fall semester, the Muhlenberg College Field Archaeology class conducted fieldwork on Pennsylvania State Game Lands 217 under the direction of Dr. Benjamin Carter, Associate Professor of Anthropology and Department Chair and an archaeologist at Muhlenberg. By utilizing LiDAR data, pedestrian survey, and shovel test pits, the class intended to demonstrate the presence of the charcoal industry and the colliers and the way colliers used the landscape. By initiating this research, the group wanted to address possible reuse of pits, the area of timberland needed for each charcoal pit, and the possible existence of a temporary living 3 structure for the colliers. Through this research in this area, the goal was to illuminate the role of colliers in Lehigh Valley industry and provide some insight into their lives.
Plan
To further students understanding of charcoal pits, the Muhlenberg Field Archaeology class studied the Blue Mountain land owned (at least partially) by the Balliets and was used for charcoal and iron production. During field work different methods were utilized, including examination of LiDAR maps, pedestrian survey, shovel test pits, and metal detecting.
First, possible charcoal pits were identified using LiDAR (Light Detection and Ranging). LiDAR is a form of remote sensing that measures the height of the land surface and vegetation across an area using a plane containing a combination of GPS, sensors/lasers, and an IMU (inertial measurement unit). Following a workshop on LiDAR run by NEON and Open Topography, Dr.Carter was able to construct a DEM using the original LiDAR data (also available on PASDA Imagery Navigator) by using the Class 2 points, which are all of the ground (or “last return”) points. This allowed him to create a more complete hillshade and slope analysis that showed charcoal pits in greater detail and identified more pits than the initial PASDA LiDAR data. The next step was to confirm that the anomalies identified in the LiDAR data are the remains of charcoal pits. We utilized a GPS-guided pedestrian survey (Burke, Smith, and Zimmerman 2009; 70). The first day in the field, we used GPS on a combination of iPads and Android devices in order to see how well the LiDAR matched with charcoal pits. Locations identified as charcoal pits in the LiDAR were loaded onto the devices. Using the GPS (Android devices had internal GPS, but external Bluetooth GPS units were needed for the iPads), we were able to walk to these locations to assess if they were charcoal pits. In two days of work we were able to locate and assess 12 LiDAR-identified pits (31, 39, 58, 40, 41, 15, 16, 17, 18, 8, 9, 3). Two to three additional charcoal pits were also identified (1000, 1001, possibly, 1002) were identified that were not present in the LiDAR data. In order to complete the survey, we used a web-based form through Kobo Toolbox. Using the form, we recorded: 1. Recorder; 2. Number from the LiDAR identifications; 3. Whether or not it was a likely charcoal pit; 4. Condition of the pit; 5. Location (GPS); 6. Size and orientation of the pits; 7. Presence or absence of a path/ road; 8. Presence or absence of ferns (this was originally thought to be an important signifier- it is not); 9. Any additional notes.
Fieldwork
During our field work we utilized several different methods including the examination of LiDAR maps, pedestrian survey, shovel test pits, and even metal detecting. In order to identify charcoal pits not identified in the LiDAR, an area was chosen that was accessible and lacked LiDAR. In order to locate these pits, we performed a systematic transect survey (a survey done by walking in lines across the area of interest). The general area in which we were working with consisted of two main parts: an upper portion of the mountain characterized by steep, rocky slopes, and a lower area that was wooded with fairly dense vegetation. Two of the locations identified in the systematic pedestrian survey were chosen for further investigation, this included detailed mapping, shovel test pits and a metal detecting survey.