Master’s Project Presentations

                                                                      Fall 2018           

When: December 10, 2018

Where: UA’s ENR2 Building, Room S107






Programming in GIS: Geospatial Software Development


Quyen Ha


Mobile GIS: Developing a Workflow for Electric Asset Inspection


Mohamed Mohamed


Collecting and Displaying Available Commercial Properties in Downtown Tucson Using Mobile and Web Applications


Jeffrey W. Breshears


Mapping Earth Fissures in Arizona Using UAV-Based Multi-Angle Photography


Bailey Bellavance





Vegetation Species Mapping on Santa Rita Experimental Range Using Hyperspectral, Lidar, and High Resolution UAV Imagery


Charles C. Conley


A Python Toolbox Tool for the Workflow Automation of Asteroid Body-fixed Coordinate Extraction, for Identified Hazards, from USGS's ISIS3 Output


Jon M. Cutts


GIS for Manufactured Housing Assessment

Taylor Handschuh






Title: Mobile GIS: Developing a Workflow for Electric Asset Inspection

Author: Mohamed Mohamed,

Key words: Web GIS, Mobile GIS, ArcGIS Online, Process integration, FME Workbench

Abstract: By upgrading to digital applications over paper forms, Sulphur Spring Electric Coop (SSVEC) will create more organized and efficient joint use inspection processes. In this project, I integrated GIS with an existing inspection workflow that manage joint use inspection in SSVEC by utilizing Web GIS. My approach was identifying systemic and workflow shortcomings, new workflow was implemented to increase system efficiency through Mobile GIS and automation. I configured ESRI field against ArcGIS Online. To do this first, I designed a workflow that tracks the data and software functions. Maps and web services were created and published in ArcGIS Online (AGOL). Inspection form was designed by Survey123, a project was created in Workforce for ArcGIS, and an Operations Dashboard was published. Automation was created with FME Workbench. As a result of this integrated approach, improvement was recorded at multiple operational stages. Reduction in data entry times were noted while overall data quality and consistency was increased. More importantly, data reporting from the field was received and interpreted in near real time, eliminating hours of preparation and debriefing time normally associated with the field-work involved. Analysis of the integrated process’ effect on workflow and systemic efficiency therefore suggests that wider implementation of this technologically-integrated approach to field-work will strengthen not only systemic efficiencies, but the quality and consistency of the results produced therein. This work demonstrates the streamlining and time-saving value of a technologically-integrated reporting process which improves end-product quality, consistency and form.



Title: Programming in GIS: Geospatial Software Development

Author: Quyen Ha,

Keywords: Web GIS, HTML, CSS, JavaScript, app development, web map

Abstract: As the number of GIS software options increases, so too does the need for GIS developers. The growing list of interactive web maps, cloud geodatabases, and field data collection mobile devices have only underscored this need in what is an increasingly cross-disciplined and multi-dimensional field. While good academic work is being done to produce this new generation of GIS developers, little has been done to research the methods, application, and production of a GIS workforce capable of both mapping and coding at the professional level. Both GIS and programming were addressed in this project by creating a central repository application for M.S. GIST alumni and students. In researching this work, casual interviews were conducted with established programmers and academics in the field in addition to extensive independent study of coding concepts, application and structures. The result is a functional, prototype networking app for students and alumni of the University of Arizona’s Science and GIS Technologies program. The app contains several interactive pages, including the map page which incorporates MapBox JavaScript API. This prototype has shed light on the possibilities which exist between the GIS and coding specialties, in addition to the viability of a collaborative, GIS-oriented networking effort which addresses the evolving nature of GIS programming employment and practice.




Title: Mapping Earth Fissures in Arizona Using UAV-Based Multi-Angle Photography

Author: Bailey Bellavance,

Keywords: Earth fissures, photogrammetry, UAV, structure from motion, aerial photography

Abstract: The semiarid valleys of southern and central Arizona have been home to a growing number of earth fissures -- large cracks in the ground caused by land subsidence related to groundwater withdrawal. As groundwater withdrawal has increased, so has the necessity for monitoring these features. Traditional field measurements are labor intensive and often only supply an estimate of fissure depth and width. This project was conducted to determine if multi-angle aerial photography from unmanned aerial vehicles (UAVs) could be used to accurately measure fissures using structure-from-motion photogrammetry. The 3km long fissure mapped is located in Pinal County, Arizona. In an effort to combat shadows within the fissure, three flights were completed using a UAV at dawn, sunrise, and noon. Over 500 images of the fissure were taken per flight, and were used in photogrammetry software to create an ultra-dense 3-D point cloud and orthomosaic. In-situ width and depth were measured at 17 different locations along the fissure via traditional collection methods for comparison with the UAV-based results. A comparison between the imagery-based and manual fissure width measurements shows an R2 value of 0.997. UAV based depth measurements could not be derived in the narrow fissures. Depth measurements taken where the width was greater than 1.8 meters has an R2 value of 0.9525. To measure a narrow fissure depth, an active LiDAR sensor would be more appropriate. The application of photogrammetry to measure earth fissures can provide accurate results of fissure location and width and provides limited information about the depth. 




Title:  A Python Toolbox Tool for the Workflow Automation of Asteroid Body-fixed Coordinate Extraction, for Identified Hazards, from USGS's ISIS3 Output

Author:  Jon M. Cutts

Keywords:  OSIRIS-REx, asteroid sampling, python, automation, raster sampling, ISIS3

Abstract:  The University of Arizona’s asteroid-sample retrieval mission, OSIRIS-REx, will use spacecraft imagery of its target asteroid, Bennu, in order to map potential rocks and boulders hazardous to a sample site, but requires that these locations are identified in the asteroid’s custom 3D body-fixed XYZ coordinate-system.  This Master’s Project automates the manual workflow of XYZ-coordinate identification of these hazards.  An ArcMap Python Toolbox tool was developed to ingest: shapefiles of user-identified hazards, and a projected composite-band raster dataset from the USGS’s Integrated Software for Imagers and Spectrometers (ISIS3) that contains the necessary geometry information.  An automated workflow, using these inputs, was developed to import the shapefiles into a temporary geodatabase, extract the correct bands from the ISIS3 composite raster, calculate the footprint used for clipping extraneous data, convert applicable polyline features to point features, and extract the 3D XYZ-coordinates, latitude, and longitude, for the asteroid’s rock and boulder hazards from the raster.  These data are joined back to the hazard features and exported as shapefiles.  As a quality control check, this tool also automates the calculation of the latitude and longitude from extracted XYZ-coordinates and compares these values to the extracted latitude and longitude to ensure that all coordinate extractions occurred correctly: any result that is outside the user-defined threshold is written to a text file for further analysis by the user.  The shapefile output from this tool will be used as an input for two of the Mission’s critical maps used in sample site selection: the “Sampleability” and “Science Value” maps.





Title: Collecting and Displaying Available Commercial Properties in Downtown Tucson Using Mobile and Web Applications


Author: Jeffrey W. Breshears

Keywords: downtown Tucson, commercial properties, ArcGIS Collector, ArcGIS Online, web application

Abstract: In recent years the environment of Downtown Tucson has experienced a significant stage of urban change and redevelopment. The Downtown Tucson Partnership is a non-profit organization that seeks to enhance municipal services in the in the downtown area. One of the economic goals of the Downtown Tucson Partnership is to keep commercial properties occupied and active. This Master’s project works to assist in achieving that goal by using geospatial technology to organize and display available commercial properties in downtown Tucson. An ESRI web application was created to store geographic locations of available commercial properties along with relevant attribute information. The web application was designed to enable users to browse available properties while filtering their search by property attributes including location, square-footage, and cost. Additionally, an ArcGIS Collector form was created and linked to the web application, that allows for mobile entry of property locations, images, and attributes. The resulting applications allow for the Downtown Tucson Partnership to maintain a current inventory of available commercial properties, and for potential business owners to find suitable properties to lease or purchase in the downtown area. While these applications were designed specifically for the downtown Tucson area, they could be adjusted to apply to different locations and to collect and display different features. The web application created for this project is embedded in the Downtown Tucson Partnership webpage and functions as an ongoing tool to aid in local economic development.





Title: Vegetation Species Mapping on Santa Rita Experimental Range Using Hyperspectral, Lidar, and High Resolution UAV Imagery

Author: Charles C. Conley,

Keywords: arid lands, land cover, drone, Arizona vegetation, range land monitoring

Abstract:  In past studies, the monitoring of woody vegetation cover has been identified as a valid indicator of ecosystems’ structure, function, and services.  As a National Ecological Observatory Network (NEON) site, aerial datasets are acquired annually over Santa Rita Experimental Range (SRER) and present a unique opportunity for researchers to closely examine vegetation composition in an arid environment.  The main objective of this research was to develop innovative procedures and methods for classifying and mapping vegetation species (e.g. mesquite, creosote, and cacti) by using a small portion of the airborne hyperspectral and LiDAR datasets from NEON.  To do this, hyperspectral data were used to derive multiple spectral index layers and combined with a canopy height model layer created from LiDAR point cloud data.  Spectral indices were examined and selected to identify and highlight unique vegetation characteristics.  During this process, a new spectral index was developed; successfully identifying cacti.  The final hyperspectral and LiDAR derived image cube consisted of 26 data layers at a spatial resolution of one meter.  This image cube was complimented by in situ survey data and very high resolution digital color imagery collected from a small unmanned aerial vehicle (SUAV).  Using a support vector machine algorithm, these combined georeferenced layers were used to train, perform, and validate supervised imagery classifications of vegetation species resulting in 87% accuracy.  If these supervised classifications are continually conducted, they will allow future researchers to monitor, quantify, and report the annual composition of the dominant vegetation species that make up SRER.





Title: GIS for Manufactured Housing Assessment

Author: Taylor Handschuh,


Keywords: Mobile Homes, Manufactured Housing, Housing Insecurity, Low Income Housing, Real Estate


Abstract: Many local governments do not (publicly) present or possess data or information about the various tenures of manufactured housing within their regions, however knowledge about the quantity of these units and the living conditions which they promote is important to local decision makers, planners, and social scientists alike. GIS tools and spatial analysis methods can help to understand how this affordable housing option shapes the lives of mobile home dwellers, and the communities in which they are located. One of the unique caveats of this semi-informal housing sector is the variety of housing arrangements or tenure options that a mobile home may poses- residents may or may not own the land they live on, but also may or may not own their manufactured home, which may be either personal property or real property, and can be located within a park, co-op, subdivision, subdivided lot, or elsewhere. This paper will discuss the data acquisition and processing required for a preliminary MHU count; the methods for creating vulnerability or resilience ranking, indices, and selecting proxies; the creation and presentation of bivariate data; app-based field data collection/ground truthing; and strategizing how community stakeholders can deploy location-specific remedies to the manufactured housing sector.  The outcomes of the analysis and following community action will be discussed, and the success of these endeavors measured, as to allow for similar investigations by other metropolitans that also do not fully understand the forces at play around their MH housing sector.