Museum Collections Management with Google Earth and GIS by John
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Museum Collections Management with Google Earth and GIS by John-Henry Voss, B.A. A Thesis In Museum Science Submitted to the Graduate Faculty of Texas Tech University in Partial Fulfillment of the Requirements for the Degree of MASTER OF ARTS Approved Dr. Sankar Chatterjee Chair of Committee Dr. Hyojung Cho Dr. Stance Hurst Dr. Mark Sheridan Dean of the Graduate School December, 2018 Copyright 2018, John-Henry Voss Texas Tech University, John-Henry Voss, December 2018 Table of Contents Abstract iv List of Tables v List of Figures vi 1. Introduction 1 Museum Collection Management 2 Geographic Information Systems (GIS) 6 Satellite Remote Sensing 9 Research Question 11 Problem of Study 11 Need of Study 12 Goals and Objectives 12 Significance 12 Case Study: Mapping and Documenting Triassic Fossil Localities in Northwest, Texas 13 2. Methodology 17 3. Results 22 Borden County 23 Garza County 30 Crosby County 35 Mitchell County 37 Scurry County 38 4. Discussion 40 ii Texas Tech University, John-Henry Voss, December 2018 5. Conclusion 43 References 44 iii Texas Tech University, John-Henry Voss, December 2018 ABSTRACT Museums serve their public by educating them with objects from their collections. Collections management is taken very seriously in this endeavor. Tools used to achieve proper collections management vary but databases serve as the most important tool for museums. Museum databases though are great for maintaining information. They lack the ability to support and use georeferenced data. This thesis will implement a database that can and use a goal and objectives to test its abilities. A case study is also being implemented with this thesis to exhibit the abilities of a geospatial database that can surpass modern museum databases. The case study will support the Paleontology division of the Museum of Texas Tech University in its efforts to find more Triassic river channels within the Dockum Group of West Texas. The results of the thesis with the case study will determine if a geospatial database can improve upon database practices for museums. iv Texas Tech University, John-Henry Voss, December 2018 List of Tables Table 1: Table of all sites from Borden County denoting area in square meters and date of visit. 23 Table 2: Table of all sites from Garza County denoting area in square meters and date of visit. 31 Table 3: Table of all sites from Crosby County denoting area in square meters and date of visit. 36 Table 4: Table of all sites from Mitchell County denoting area in square meters and date of visit. 37 Table 5: Table of all sites from Scurry County denoting area in square meters and date of visit. 38 v Texas Tech University, John-Henry Voss, December 2018 List of Figures Figure 1: Research area overlaid on top of DEM. The colors of this map denote changes in elevation. Elevation changes from high (darker colors) to low (lighter colors). In this DEM each pixel is 90m2 and contains an average elevation over that area. 7 Figure 2: Satellite image by Google Earth. 9 Figure 3: GIS map that labels the Southern High Plains, the Dockum Group, and the counties of west Texas. 14 Figure 4: Generalized sequence of the Upper Triassic Dockum Group formations, separated by unconformities in eastern New Mexico (left) and West Texas (right) (after Lehman & Chatterjee, 2005 and Sarigul, 2014). 15 Figure 5: Greenish-white siltstone associated with the axis of ancient Triassic-age river channel at locality MOTT VPL 3869. 16 Figure 6: The 21 counties containing outcrops of the Dockum Group that were examined for the case study. 17 Figure 7: Google Earth image with red arrow expressing the lack of dense vegetation on the buried river channel. 19 Figure 8: Google Earth image with red arrows highlighting the discoloration of the river channel and flood bank deposits with the rest of the surrounding area. 20 Figure 9: Land ownership map. Midland Map Company, 2003. 21 Figure 10: Location of all 20 possible Triassic sites from Google Earth Survey. 22 Figure 11: Google Earth image of MOTT VPL 3629 and 3632. The black rectangles outline the floodplains and the red lines trace the Triassic-age river channel. 25 Figure 12: Google Earth image of MOTT VPL 3958. The black rectangles outline the floodplains and the red lines trace the Triassic-age river channel. 26 Figure 13: Google Earth image of MOTT VPL 3965. The black rectangles outline the floodplains and the red lines trace the Triassic-age river channel. 27 Figure 14: Google Earth image of MOTT VPL 3960. No Triassic-age river channel deposits were found. 28 vi Texas Tech University, John-Henry Voss, December 2018 Figure 15: Map of the extent of Triassic-age river channel deposit and found localities (MOTT VPL 3958, 3629, 3965, 3632, and Borden 3) from Google Earth Survey. The black line depicts the location of the Triassic river channel. 29 Figure 16: Map of the extent of Triassic-age river channel deposit and found localities (Borden 1 and 2). The black line depicts the location of the Triassic river channel. Though Borden 2 seems to be in Garza County it is in fact in Borden County and is an error on the map. 30 Figure 17: Google Earth image of MOTT VPL 3869. The black rectangles outline the floodplains and the red lines trace the Triassic-age river channel. 32 Figure 18: Google Earth image of MOTT VPL 3874. The black rectangles outline the floodplains and the red lines trace the Triassic-age river channel. 33 Figure 19: Google Earth image of MOTT VPL 3956. Triassic-age river channel sediments were not found at this locality. 34 Figure 20: Map of the extent of Triassic-age river channel deposit and found localities (MOTT VPL 3869 and Garza 1). The black line depicts the location of the Triassic river channel. 35 Figure 21: Google Earth image of MOTT VPL 3957. Triassic-age river channel deposits were not found at this locality. 36 Figure 22: Google Earth image of MOTT VPL 3959. The black rectangle outlines the Triassic-age floodplains. 39 vii Texas Tech University, John-Henry Voss, December 2018 Chapter 1 Introduction A museum collection consists of objects and their associated documentation. A primary concern in the field of museum science is developing best practices and standards that maintain contextualized information between objects and their place of origin (Beaudoin, 2012). Museums today are faced with how to integrate evolving digital technologies to best manage their collections and maintain informational links between a variety of sources (IMLS, 2009). Museums as a field use this technology to not only stay relevant with the current trends but also to create meaningful practices and standards. Museums strive to create and prepare documentation for managing their collections. This documentation is derived from many sources that provide contextualized information about objects within a collection (Beaudoin, 2012). A particularly important source of information is their spatial contexts. This context pertains to the environment in which an object was. Understanding these environments creates a broader picture about the object. Geographic Information Systems (GIS) is software that allows users to visualize, analyze, interpret, and manage spatial information (Yeung & Hall, 2007). With advancements in computer processing power over the last 30 years, GIS has become the standard by which organizations manage their spatial data (Yeung & Hall, 2007). Spatial information is typically acquired via Global Positioning Systems (GPS) with users using devices in the field to acquire data. Remote sensing, the acquisition of data about objects and landscapes through indirect observation, is increasingly being used with advancements in satellite technology and software that is making this technology more 1 Texas Tech University, John-Henry Voss, December 2018 accessible to even the public (Yeung & Hall, 2007). The integration of GIS, GPS, and remote sensing allows organizations to gather, analyze, manage, and maintain spatial information. This thesis will investigate how remote sensing and GIS is applicable for contextualizing and maintaining documentation from the field to storage within museum collections. This study will combine both forms of technology with a case study chosen to examine their use within a field and museum setting. In this research GIS and remote sensing were used to survey and document fossil finds associated with Late Triassic-age (237-201 mya) sedimentary river beds within the Dockum group of northwest Texas. The Dockum group contains world-renowned tetrapod assemblages (e.g., Lehman and Chatterjee 2005). Satellite imagery reviewed within Google Earth software was used to locate river channel sedimentary rock layers often associated with fossil finds within the Dockum Group (Mueller, 2016). The GIS capabilities of Google Earth in combination with QGIS GIS software was used to record and manage the spatial contexts of field research and maintain these contextual associations from the field to the museum. Museum Collection Management The three aspects of collection management delineated by the International Council of Museums are: acquiring, conserving, and research of objects and their environment (ICOM, 2017). Museums collect to preserve aspects of humanity and to present these objects in exhibits to engage with communities (ICOM, 2017). Museums come in different varieties (e.g., natural history, art) and collect many types of objects 2 Texas Tech University, John-Henry Voss, December 2018 from art to fossils. Museums acquire objects through donors (gifts, bequests, field research), and from loans and purchases (Alexander & Alexander, 2008, ICOM, 2017). Museums that acquire new objects are guided by their collections management policy and collection plan (Anderson, 2012). The collections management policy creates a document that develops the museum’s mission and purpose. It outlines how to manage the collections and assigns responsibilities to staff positions to properly care for the collections (e.g., AAM, 2012).