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=Plan=
=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 which 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). 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, the class 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), the class walked to these locations to assess if they were charcoal pits. In two days of work, 12 LiDAR-identified pits were located and assessed. Two to three additional charcoal pits were also identified that were not present in the LiDAR data. In order to complete the survey, a web-based form through Kobo Toolbox was used. Using the form, the class 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.
 
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 Carter 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, the class 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), the class walked to these locations to assess if they were charcoal pits. In two days of work, 12 LiDAR-identified pits (31, 39, 58, 40, 41, 15, 16, 17, 18, 8, 9, 3) were located and assessed. Two to three additional charcoal pits were also identified (1000, 1001, possibly, 1002) that were not present in the LiDAR data. In order to complete the survey, a web-based form through Kobo Toolbox was used.  
Using the form, the class 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.
 
To further the 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 the field work the class utilized several different methods 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). A plane, whose precise location is known- thanks to the GPS (Global Positioning System) and IMU (Inertial Measurement Unit), flies over the terrain. A laser in the airplane projects a beam of light that bounces off objects. The time it takes the light to return to the sensor in the plane is used to calculate the distance the beam travelled (called a “return”). Equipment on the plane also records the location of the plane and the angle at which the beam is being shot. With all of this data, the precise location of laser “returns” can be calculated, constructing a point cloud that represents objects the lasers bounced off (NEON, 2014 “Basics”). For archaeologists, the “last” return, that is the lasers that bounce of the ground (rather than vegetation or buildings), are the most important because they can be used to provide very high resolution topography. Normally, point clouds are converted into digital elevation models (DEM), provides gridded coverage rather than a point cloud. These are normally viewed as hillshade models, which provide a view of the landscape created by applying a light source at a particular angle to the DEM (digital elevation model) (Carter 2016). Each pixel of the DEM, which originally represented height, is converted to a number dependent up the angle of the imaginary sun. This is much easier for the human eye to understand compared to the DEM. Importantly, both the DEM and the hillshade are available openly through the state of Pennsylvania on the PASDA Imagery Navigator (http://maps.psiee.psu.edu/ImageryNavigator/). The DEM was used to produce a slope analysis in QGIS. A slope analysis, looks at each pixel and, based upon the 8 pixels surrounding it, determines the slope of that pixel. The number associated with that pixel, therefore, becomes slope rather than altitude. The key is that flat areas will appear very different from slope.
 
Because charcoal pits are a round, perfectly level area approximately 10-15 meters across, they are easy to recognize in highly sloped terrains such as the slopes of the Blue Mountain. Charcoal pits are difficult to identify in areas were the slope is low, because one cannot differentiate them from the surrounding terrain. On LiDAR data, the charcoal pits appear as “eyes” or flattened ovals on sloped terrain due to the clearing and levelling of the site to make charcoal. Unfortunately, DEM provided by PASDA (and therefore the hillshade and the slope analysis) is constructed from only a sampling of last returns (“Class 8, Model Key (thinned-out ground points used to generate digital elevation models and contours.” PaDCNR n.d.), thereby reducing resolution. Following a workshop on LiDAR run by NEON and Open Topography, 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 (See Figures 9 and 10). Figure 11 shows the difference between the hillshade using Class 8 data and the slope analysis using Class 2 data.
 
Maps were able to be used to identify the furnaces.  Both historic as well as modern maps were used.  By looking at old maps the group is able to see that the furnace was called Balliet's Furnace in 1865 although now it is called Lehigh Furnace.  Although there is nothing remaining of the furnace or its associated structures, the maps are able to give the group the location of where they used to be and gives a jumping off point in where to look via LiDAR and other technological surveying devices.


=Fieldwork=
=Fieldwork=

Revision as of 20:28, 22 September 2020

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. The purpose of this research was to identify charcoal pits, the people who worked them, and the interrelationships of people and place with the industrial landscape of the Lehigh Valley’s iron industry. The aim was to provide insight into the lives of colliers working in the area, as well as, the processes for making charcoal and iron and the impact the industry had on the local community.

By initiating this research, the class wanted to address possible reuse of pits, the area of timberland needed for each charcoal pit, and the possible existence of a temporary living structure for the colliers. By attempting to identify and study charcoal pits in this area, the class hoped to illuminate the role of colliers in Lehigh Valley industry and provide some insight into their lives. By utilizing LiDAR data, pedestrian survey, and shovel test pits, we attempt to demonstrate the presence of the charcoal industry and the colliers and the way colliers used the landscape

Plan

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). 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, the class 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), the class walked to these locations to assess if they were charcoal pits. In two days of work, 12 LiDAR-identified pits were located and assessed. Two to three additional charcoal pits were also identified that were not present in the LiDAR data. In order to complete the survey, a web-based form through Kobo Toolbox was used. Using the form, the class 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, several different methods, including the examination of LiDAR maps, pedestrian survey, shovel test pits, and even metal detecting were utilized. 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, a systematic transect survey (a survey done by walking in lines across the area of interest) was performed. Once the locations were chosen, the site was cleared using a combination of rakes, clippers, and a machete. The debris was then placed several meters away from the pit so that it would not interfere with future STPs. The general area of fieldwork 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. During the survey, approximately 100,000 meters of land was covered. Four previously unidentified sites were recorded during this process. Two charcoal pits were identified (1003 and 1004) during the survey. And an additional charcoal pit (1005) was identified when a member of the team encountered it on a bathroom break(pg 19). One unusual site (2001) was also recorded and due to its concave nature it was hypothesized to be a collier's hut(pg 18.)Two of the locations identified in the systematic pedestrian survey, confirmed charcoal pit (1004) and the potential colliers hut (2001), were chosen for further investigation, this included detailed mapping, shovel test pits and a metal detecting survey. On October 30th, 2016 three metal detectorists, Glen Gunther, Tim Reno, and Bob Gunther, from BRAVO (Battlefield Restoration and Archaeology Volunteer Organization), including arrived to assist the team in identifying cultural remains. The metal detectorists swept both 1004 and 2001. When they located a possible artifact, the metal detectorists dug a small hole. As they dug, they utilized a tool called a pinpointer which is a smaller metal detector with a narrower magnetic field than the full-sized metal detector. This ensured that the metal detectorist was able to hone in on the original signal.

Results

This research has produced a new understanding of the charcoal & iron industry in Lehigh and Carbon Counties of Pennsylvania. A total of four artifacts were collected at all of the sites as a collective, however the relevance of the objects to the history of charcoal production is inadequate. Three of the artifacts found, a bullet round, and two (likely) shaft fastners, were found at site 1004(pg 21). This field work has highlighted four important components. A forth object was found at site 2001 and this object was a curved piece of iron(pg 21). However these artifacts reveal little about the site and the function of the charcoal pits. First, the background research of charcoal production has revealed the many individuals and families involved in the production of iron. In particular, it has shown the power and influence of the Balliet family. Second, the class highlighted the less visible colliers, who were the backbone of the charcoal industry and, therefore, the iron industry. Thirdly, over 670 charcoal pits were identified on the slopes of the Blue Mountain and have ground-truthed some of these pits. Because of ground-truthing and the LiDAR data, it is likely that a large proportion of the identified charcoal hearths are just that. While it remains possible that there are LiDAR-recognized charcoal pits that are false positives, the vast majority of these pits are remnants of the charcoal industry. Fourth, the class tested and confirmed that the features identified in the LiDAR data are in fact charcoal hearths. However, no collier’s huts were identified.

More generally, this research has opened the avenues for further research; many questions remain. Where are the collier huts? What were the lives of the colliers like? How did roads and path connect the charcoal pits to the furnaces? Were forests managed? And if so, in what way? What additional remnants of this vast industry remain in the wild woods of State Game Lands?

Notes

References