Directory   |   Access Plus   |   CyBox   |   Privacy Policy
Loading Events

GIS Graduate Seminars: Ahmed Abdelaty, Kurt Wilson, James N. Dupuie Jr., & Rachana Awale

May 3, 2017 @ 2:00 pm - 4:30 pm

Event Navigation

An Enhanced Framework for Dynamic Segmentation of Pavement Sections Using Python

Ahmed Abdelaty, GIS Certificate Candidate, Department of Civil, Construction and Environmental Engineering

Adviser: Brian Gelder


Highway agencies used automated data collection methods such as laser scanning, which resulted in the collection of an enormous amount of high-density pavement condition data. Hence, aggregating homogenous pavement segments based on the existing conditions is needed to accurately represent the overall network performance as well as making maintenance and rehabilitation decisions. This study proposes a new segmentation framework for pavement sections in Iowa that finds homogenous segments by considering multiple pavement distresses. The framework uses the affinity propagation clustering technique and heuristic rules. However, the clustering technique does not respect the spatial nature of pavement sections. As such, heuristic rules are formulated to overcome this limitation and identify homogenous pavement segments. A Python script will automate the segmentation process and produce maps of the segmented network. The script will create arrays from the pavement condition geodatabase file by using pavement condition indicators such as ride quality, rutting, and cracking data. Then the affinity propagation and heuristic rules will be implemented to create condition-based homogenous sections. Finally, the script will create polylines by using the coordinates to generate maps. The proposed segmentation framework will improve the representation of pavement condition data, and formulation of pavement maintenance and rehabilitation strategies.

Investigating Mammoth and Mastodon Range Expansion and Contraction in the Midwestern U.S.

Kurt Wilson, GIS Certificate Candidate, Department of Anthropology

Adviser: Matthew Hill


This research intends to use spatial patterning to answer three main questions.  Do mammoth and mastodon ranges expand or contract to certain zones in the Midwest region of the U.S. over time?  How might expansion and contraction patterns, or lack thereof, relate to the extinction of these mammals?  What patterns in the δ13C value of the mammals appear over space or time that may relate to extinction? To investigate I will use a data set comprised of the 92 mammoth and mastodon specimens from the Midwest that have been 14C dated and the geographic location of their recovery.  Possessing point data containing the radiocarbon age of each specimen will enable me to utilize isoline cartography to create isometric lines of ranges based on ages of the specimens.  I will then generate additional isoline maps of δ13C values over the spatial extent of the ranges to determine if there are regional or temporal variations in food content consumed.  Understanding range expansion and contraction along with diet variation will determine if spatial patterns show new possible factors in mammoth and mastodon extinction.

Distribution and Resiliency of Ring-necked Pheasants in Iowa

James N. Dupuie Jr., GIS Certificate Candidate, Department of Natural Resource Ecology and Management

Advisers: Stephen J. Dinsmore and Julie A. Blanchong


The Ring-necked Pheasant is an economically and recreationally important Iowa gamebird. Pheasants are on a long-term decline in Iowa. In an effort to understand how to manage pheasant populations in Iowa’s altered landscape, I will: 1) examine current pheasant spatial distributions on central Iowa windfarms; and 2) look at factors affecting resiliency in local pheasant populations through time across Iowa. For the first part, I will be using GIS to analyze a data set of male pheasant crowing surveys from 2015 and 2016. Using spatial analysis, python, and survey data I will automate the estimation of pheasant locations for use in habitat selection analysis. I will also create a pheasant density map for four central Iowa wind farms using the geostatistical method of kriging. For the second part, I will use a fifty year dataset of roadside surveys from the Iowa Department of Natural Resources (DNR). I will be using GIS to determine the factors affecting local population resiliency, including locations of wind turbines and available habitat. I will also be able to interpolate a map of pheasant population resiliency across the state. This analysis should be useful to the Iowa DNR when making pheasant management decisions.

Open Space and Social Equity: A study of Des Moines, Iowa and Fort Worth, Texas

Rachana Awale, GIS Certificate Candidate, Department of Community and Regional Planning

Adviser: Biswa Das


Open spaces are significant aspects of cities which contribute to their character. Open spaces add benefits in various factors like ecological, recreational, social and economic. The project uses residential property values as a proxy to compare the willingness of homebuyers to pay for single-family homes near to and away from open spaces in Des Moines, Iowa and Fort Worth, Texas in 2010. This project studies about access of open spaces in both cities. First of all, home sales price will be geocoded in GIS to create point shape file. Then, kernel density will be performed to show the density of population and open spaces in both cities. Equity mapping will be performed to show information on proximity and access to open spaces. By overlaying the results, it will help to visually inspect the difference of residential properties values with respect to socioeconomic profile and proximity to open spaces. Finally, interview with the planners will be carried out to have their insight in planning of open spaces and social justice. This project will provide recommendations for making open spaces accessible to all the people and helps planners to allocate preferred areas for residential purpose.

Share our news


May 3, 2017
2:00 pm - 4:30 pm
Event Category:


526 Design
715 Bissell Road
Ames, IA 50011 United States
+ Google Map