Posts

Internship Post #4

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An example of GIS use in Archaeology:

Internship Post #3

 Internship Update: I am expected to perform multiple tasks with little supervision at this point in my internship. When collecting survey data for my project or that of my peers, if we have been previously trained and have the appropriate amount of volunteers, we are expected to collect the data with no higher supervision. Regarding my own project, I have made great progress this semester.  I have finished the initial survey of my three survey areas, and have nearly finished processing the data collected from them. I have also been aiding another research associate with their survey project for which the data collection should be finished in the next couple of months.  After processing the initial data for my project is completed, I will be moving on to applying for a permit with the state to conduct a high-resolution survey and collect core samples. I have also been working on the report for this project simultaneously for time-saving purposes, which will be beneficial ...

Internship Post #2

  Key Takeaways from GIS Job Search - Maintain knowledge of State and Federal regulations concerning historic preservation, environmental protection, and the identification, evaluation, and protection of archaeological resources - Maintain status as a scientific diver - Continue accumulating knowledge of geophysical survey data processing methods and digital mapping applications, such as ArcGIS and QGIS

Internship Post #1

The internship that I secured for the requirements of this course is out of the University of West Florida Archaeology Institute as a Research Associate under the direction of the Marine Archaeologist Will Wilson. This internship began at the beginning of May last year. I will be continuing this work until the end of this summer. The work required of me includes the following: Conducting remote sensing surveys of submerged archaeological sites or areas of interest (using subbottom profiler sonar, side-scan sonar, and/or magnetometer) Creating maps of sites, coring locations, and data overlays  Editing survey data within various data processing programs (Sonarwiz, Hypack, etc.)  Taking sediment and site-specific core samples with GNSS-recorded locations  Creating reports based on findings in the field and other documentary research  In addition to performing my duties at the institute and working towards the completion of my thesis, I chose to join the North Carolina...

M3.1: Scale Effect and Spatial Data Aggregation

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This week I learned how scale and resolution can affect the interpretation and analysis of data and how to utilize the Polsby-Popper score to determine which voting districts are less than ideal when looking at their compactness and the dividing of counties. Scale effects on vector data involve the level of detail in spatial features: at large scales (high detail), features like rivers and city boundaries are depicted with more precision, while at small scales (low detail), features are simplified, leading to potential data generalization.  Resolution effects on raster data refer to the size of cells: higher resolution provides finer detail, while lower resolution leads to loss of detail, affecting analyses like land cover or terrain modeling. When resampling LiDAR data, you need to consider what analysis you will perform to determine which technique is best to use. I chose bilinear interpolation since we were using the data for a DEM of a watershed area. The lowest and highest-res...

M2.2: Interpolation

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 This week  I learned that different interpolation techniques can produce varied results depending on the frequency of the data points and the contents of that data. A  single instance of coinciding data points can throw off the results of the analysis greatly when using spline interpolation. W hen working with continuous data with gradual changes spline generates a smooth spatial pattern that more accurately represents the data. Where preserving exact values is necessary IDW shows sharp transitions between data points. Thiessen represents the data as various zones using TINs.  Spline (regulated) Spline (tension) IDW Thiessen