Master’s
Project Presentations
Fall
2018
When:
December 10, 2018
Where:
UA’s ENR2 Building, Room S107
|
Time |
Title |
Person |
|
6:00-6:20 |
Programming in GIS: Geospatial Software Development |
Quyen Ha |
|
6:20-6:40 |
Mobile GIS: Developing a Workflow for Electric Asset
Inspection |
Mohamed Mohamed |
|
6:40-7:00 |
|
Jeffrey
W. Breshears |
|
7:00-7:20 |
Mapping Earth Fissures in Arizona Using UAV-Based Multi-Angle
Photography |
Bailey
Bellavance |
|
7:20-7:30 |
BREAK |
|
|
7:30-7:50 |
|
Charles
C. Conley |
|
7:50-8:10 |
|
Jon
M. Cutts |
|
8:10-8:30 |
Taylor
Handschuh |
Title:
Mobile GIS: Developing a Workflow for Electric Asset Inspection
Author:
Mohamed Mohamed, eng.moh888@live.com
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, quyenttha@gmail.com
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, bbellavance@email.arizona.edu
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.
Author:
Charles C. Conley, charlesconley@email.arizona.edu
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, thandschuh@email.arizona.edu
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.