Associate Professor
Department of Community
and Regional Planning

Email: haddad@iastate.edu
Phone: 515.294.8979
Office: 583 College of Design

Resume Teaching Students GIS Seminar Iowa State University GIS Certificate Program GIS Links GIS Workshops
 

GIS Seminar

The seminar starts promptly at 12:10 p.m. and ends around 1:00 p.m. - located in the GIS Lab, Room 526 at the College of Design.


February 13, 2017 12:10 pm
Chris Seeger, Professor, Dept. of Landscape Architecture, ISU Extension

Field data collection with Fulcrum


February 20, 2017 12:10 pm
Chris Harding & Franek Hasiuk, Department of Geology, ISU

TouchTerrain - 3D printing elevation models using a Web application

Abstract: Commodity 3D print technology (~$2000) can print small (10 cm x 10 cm) 3D terrain "maps" reliably and cheaply. Such touchable 3D maps may augment digital maps when learning about landscape forms, geologic features, human impact, etc. However, the primary issue now is the creation of the to-be printed 3D digital models and the need to create pysically larger maps. To hand-craft a 3D map of an area, knowledge of GIS (such as ArcGIS) and/or a 3D modeling package (such as Blender or Rhino) is usually required. Our project aims to radically simplify the creation of high quality physical terrain models to enable teachers with access to a 3D printer to easily create and incorporate 3D printed terrain maps in their lesson plans. The TouchTerrain project offers a simple Web interface to select an area on a Google map and then creates downloadable 3D model files (Obj or STL format) of this area's Digital Elevation Data, either worldwide at a 90 m resolution (SRTMv4) or US-wide at a 10 m resolution (USGS/NED). The 3D print resolution (typically 0.1 to 0.5 mm) of the specific printer model can be set, thus avoiding downloading needlessly large models that cannot be printed adequately by a given 3D printer. Physically large models can be created by tiling the area, e.g. into 4 by 4 tiles, printing each 10 x 10 cm tile separately and then assembling them into a 40 x 40 cm map. Processing, such as projection to UTM, is done in Python via Google's Earth Engine API.

To try out an experimental prototype of the TouchTerrain Web application go here: http://www.public.iastate.edu/~franek/TouchTerrain/ We are currently looking for feedback on the application and for help with deploying 3D terrain maps in the classroom and measuring their teaching impact.


February 27, 2017
12:10 pm

Shawn Blaesing Thompson, Iowa Department of Transportation

Success and Challenges of the Geospatial Professional.


March 6, 2017
12:10 pm

Helina Sarkodie-Minkah, GIS Certificate Candidate, Department of Community and Regional Planning

Poverty Suburbanization in the United States: The Case of Dallas Fort-Worth, Texas

Adviser: Dr. Monica A. Haddad

Abstract: Poverty is suburbanizing in metropolitan areas of the United States, and the experience in the Dallas Fort Worth Metropolitan Area (DFWMA) is no exception to this trend. 2 | Page The number of people living below the federal poverty line in the suburbs exceeds that of the central city. Within this context, this study seeks to examine the spatial distribution of poverty in the DFWMA and to understand the policies and programs being implemented - at the local level - for alleviation of poverty in the DFWMA. The study employs Exploratory Spatial Data Analysis to identify clusters of poverty in the DFWMA in 2000 and 2010. Additionally, I also examine the spatial distribution of percentage white and percentage receiving Supplementary Nutrition Assistance Program. My spatial unit of analysis is the census tracts. After identifying the clusters of high poverty located in the suburbs of DFWMA, I interview planners to understand the policies and programs that are being implemented at the local level to alleviate poverty. The study will shed some light on the need to address the increasing trends of poverty in the U.S. suburbs, and on the need to understand strategies to alleviate poverty in these suburbs.

March 20, 2017
12:10 pm

Anna Belyaeva, GIS Certificate Candidate, Department of Ecology, Evolution and Organismal Biology

Distribution and habitat characteristics of aquatic snails in the Iowa Great Lakes

Advisor: Dr. van der Valk

Abstract: The aquatic snails of the Iowa Great Lakes were first studied in 1890, and their conditions were last updated in 1980. The previously noticeable alterations in snails’ densities and composition were attributed to the changes in lakes’ water quality. The current survey of aquatic macroinvertebrates, including snails, was conducted in 2010-2012 on Big Spirit, West Okoboji, East Okoboji, and Lower Gar Lakes before the establishment of the invasive zebra mussel. This survey includes data on species composition and densities, sediment types, and sampling depths. The stratified random sampling was employed: macroinvertebrate samples were randomly collected from three lake zones that were defined a priory. Sampling locations (45 per lake) were recorded with a GPS unit, and digitized maps were used for lake contouring. The objective of this research is to examine the depth and sediment preferences of several species of snails. The regression analysis will be employed to determining within lake factors affecting the distribution of snails. The proposed GIS application is to create snails’ density maps based on 30 and 45 samples and compare their misclassification. The interpolation of the surfaces will be conducted by the original Kriging method with ArcGIS Spatial Analysist tool.

 

March 27, 2017 (two presentations, class ends at 1:30 pm)
12:10 pm

Jacob Eeling, GIS Certificate, Department of Ecology, Evolution and Organismal Biology

Analyzing, Modeling and Visualizing Submersed Vegetation inTreatment Wetlands

Adviser: Dr. William Crumpton

Abstract: Submersed vegetation has a major impact on characteristics of wetland systems. Percent cover of submersed vegetation data was collected bi-weekly at three treatment wetlands in Central Iowa. On average 150 data points were collected in each vegetation survey. ArcGIS was used to investigate normality and stationarity. There were significant issues with normality in the dataset, leading to selection of universal Kriging method as the method for spatial interpolation. GPS point data from vegetation surveys was interpolated to submersed vegetation cover surface. Autocorrelation analysis (Nearest Neighbor Analysis) was used to determine if the sampling method achieved significant dispersal of samples over the sampling area. Local Moran’s I and Getis-Ord G will be used to analyze the patterns of vegetation growth by analyzing clustering and hotspots with results from interpolated surface rasters. Kriging interpolation was done with R, which, compared to ArcGIS, allowed for greater transparency and flexibility in scripting and fitting of the model to the dataset. ArcMap 10.4 will be implemented as a visualization tool. A time series animation of interpolated surfaces will show changes in wetland vegetation from May to November. I will also use ArcScene 10.4 to model and animate the vegetation in the wetlands in 3D.

 

Angela L. Bowman, GIS Certificate Candidate, Department of Geological & Atmospheric Sciences

Hydrologic process understanding through satellite observations

Adviser: Dr. Chris Harding

Abstract: Improving the spatial and temporal representation of the surface water balance in streamflow forecasting models is critical for increasing the utility of water supply, flood and drought predictions. I am investigating the application of satellite remote sensing data in operational streamflow prediction. Specifically, the consequence of the role hydrologic model structure accuracy has on streamflow simulations through input of satellite-derived evaporation data. In my GIS application, I apply several techniques to process and analyze satellite-derived and model-simulated data. Examples include automation of geoprocesses to convert time series spatial model output to files that can then be converted to raster files; raster analysis for comparison of the model simulated data to satellite data used as a validation tool; and, upscaling or downscaling, as necessary, of the satellite data to match the scale of the model simulations. Evaluation statistics of the overall streamflow simulations show mixed results with the use of the satellite-derived data. Analysis of model states indicates the water balance components progress through the model differently while simulations of streamflow discharge do not reflect this.


April 3, 2017                                                                                                           12:10 pm
Casey Judge, GIS Certificate, Department of Ecology, Evolution, and Organismal Biology 

Spatial-Temporal Interpolation of Survey Point Data: Toolset Development for Multiple Applications using Python 2.7 and ArcGIS 10.4

Advisor: Dr. William Crumpton

Abstract: Spatial survey point data is widely collected for numerous applications (i.e. vegetation, population density, etc). Often, this point data is then interpolated to visualize the spatial distribution of the survey data. However, spatial data can be difficult and costly to gather and is often only collected intermittently. To model changes in the data over time between collection dates, a spatial-temporal interpolation is required. Temporal interpolation is not built in to ArcGIS processing tools, but can be conducted with VBA code by first exporting raster grid cell data to Microsoft Excel. However, this technique is cumbersome and time consuming. The objective of this project is to develop a script set with Python 2.7 to create an ArcGIS toolbox for conducting coupled spatial and temporal interpolations which can be used for a wide array of applications. The contained toolset will provide spatial interpolation using optimized kriging methods with the correct output format required for the temporal interpolation. Subsequent temporal interpolation will allow user specified linear or spline methods to model growth and/or decay between survey dates. An example of the toolset’s utility will be shown using submersed vegetation survey data from three Iowa wetlands collected approximately bi-weekly during the 2016 growing season.


April 10, 2017 (two presentations, class ends at 1:30 pm)
12:10 pm

Brandon Klein, GIS Certificate Candidate, Department of Community and Regional Planning

Adapting the Densify Sample Network Tool for a Site Suitability Analysis of Automatic Traffic Recorder Locations

Adviser: Dr. Carlton Basmajian

Abstract: Average Annual Daily Traffic (AADT) is a universal figure used in transportation planning to describe the average amount of daily vehicle traffic that travels on a specific roadway. This study focuses on using this variable to perform a site suitability analysis for automatic traffic recorders (ATRs), machines that continuously count traffic. This analysis will be used to answer the spatial question “what placement of ATRs will best improve the geographic distribution of non-covered roadway segments.” The study area for this analysis will be the rural primary roadway network for the state of Iowa. AADT sample points from current ATR locations will be used as the primary data set in an ordinary kriging spatial interpolation process to represent standard prediction error variability throughout Iowa. Concurrently, a weighted raster surface of Iowa will be created that represents the best possible ATR locations based on road slope, distance to intersections, and road curvature. Both outputs will be input into the Densify Sampling Network tool, which will populate the best candidate locations for new ATR sites based on suitable geographic location and the most impact on the prediction standard error.


Iftin Thompson, GIS Certificate Candidate, Department of Civil, Construction, & Environmental Engineering

Safety Effects of Access Point Density on Urban Areas

Advisor: Dr. Peter Savolainen

Abstract: Access management strategies, such as access point spacing and turning restrictions, are a complex issue and the impacts of such features on traffic crashes and injuries is in need of further research. The purpose of this study was to identify how driveway density, type, and spacing affect the rate of crashes among roadways in high-density development areas. Data was collected from twenty-eight urban and suburban corridors in the state of Iowa, which had collectively experienced significant growth in recent years. ArcGIS was extensively used in order to effectively gather information from each corridor. Methods such as table joins, digitizing, editing attribute tables, and linear referencing was executed. Driveway information was individually collected by digitizing points at each location. Crashes from 2010 to 2014 was gathered from the Iowa DOT crash database, but organized using a series of table joins and editing attribute tables. Other characteristics such as intersection density were also gathered for this study. Linear referencing was best used to determine the distance between each intersection along every corridor. A statistical analysis was conducted to better understand the relationship between driveway density and crash rates.


April 17 (two presentations, class ends at 1:30 pm)
12:10 pm

Bijan Vafaei, GIS Certificate Candidate, Department of Civil, Construction & Environmental Engineering

Installation Guidance for Centerline and Edgeline Rumble Strips in Narrow Pavements

Adviser: Dr. Peter Savolainen

Abstract: Rumble strips on two-lane rural highways are proven safety countermeasures. Placement rumble strips can usually be accommodated within wide pavements (24 ft or greater paved width) without issue. However, proper placement is less straightforward for highways with paved widths less than 24 ft. Contributing factors such as traffic volume, and roadway alignment may suggest the use of one type of rumble strip over another. This study involved an analysis of historical crash data for segments with and without rumble strip in order to assess the risk of cross-centerline and run-off-road crashes in Iowa. The research involved a series of GIS programming and automation in Python including spatial analysis, geoprocessing, and map processing to accelerate the process of data preparation, modeling and analysis. To assess the Iowa-specific effects of rumble strip installations, a data set was constructed for the two-lane, two-way primary highway network. The ultimate purpose of this study is to provide guidance based on safety analysis to assist county road agencies, as well as the Iowa Department of Transportation (DOT), in determining when to install rumble strips or and which of the two to install when the installation of both is not feasible based on various site-specific factors.


Steven Younkin, GIS Certificate Candidate, Department of Civil, Construction & Environmental Engineering

Engaging Stakeholders in Intersection Traffic Safety in Iowa

Adviser: Christopher Seeger

Abstract: Out of the 54,589 crashes in Iowa in 2015, 34% of these occurred at intersections. In order to better address safety issues, researchers have established a clear multiple regression methodology for predicting crashes based on intersection attributes. Mature crash and intersection databases are currently available along with traffic volumes for utilization as variables in a multiple regression negative binomial model. The main purpose of this project is to develop a webmapping tool to analyze which intersections are safer or more dangerous than similar intersections in different jurisdictions as well as compare within jurisdictions to find the sites with top potential for improvement. Applications used to develop this will be ArcMap for near analysis combining traffic data to intersection database, R for statistical modeling and several leaflet/javascript webmapping libraries to cluster map data, filter queries, and produce charts and figures in a responsive and user friendly environment. This tool should allow city managers, county engineers, and other stakeholders to make better decisions with available funds and improve engagement with the public in their decision making process.


April 24, 2017 (two presentations, class ends at 1:30 pm)                                         12:10 pm

Anna Nesterovich, GIS Certificate Candidate, Department of Geological and Atmospheric Sciences / Environmental Sciences

The spread of under-ice algal blooms in Bering and Chukchi seas as opposed to marginal ice blooms.

Adviser: Dr. Beth Caissie

Abstract: The prevalence of under-ice diatom blooms in the Chukchi Sea, as opposed to the mainstream concept of marginal ice blooms as a basis for Arctic marine ecosystems, was recently postulated. The goal of my PhD project is developing a diatom-based proxy for sea ice extent in the North Pacific; it depends on the idea of marginal ice blooms as ‘savings accounts’ for benthos: marginal ice blooms are massive and the most represented in sediments, which makes it possible to reconstruct sea ice concentrations. However, if a preceding under-ice bloom depletes the nutrients in the water, the marginal ice bloom will be small and the sediments will reflect winter instead of spring ice conditions, which will affect the proxy. The problem of prevalence of those two bloom types will be a chapter in my dissertation. I will download satellite data for daily sea ice and phytoplankton concentrations in the Bering and Chukchi seas (as georeferenced TIFFs). For each pixel (25x25 km) I will extract information of chlorophyll concentrations’ changes at the ice retreat initiation and later on in the season. I will then map under-ice (a bloom never happens in open water) and marginal ice (starts after ice retreat) blooms.

 

Abatan Akinfolarin, GIS Certificate Candidate, Department of Civil, Construction & Environmental engineering

A spatial detection methodology for roadway crashes around interchanges

Adviser: Dr. Peter Savolainen

Abstract: Crash rates are significantly elevated in the immediate vicinity of interchanges due to increases in traffic conflicts. To this end, the objective of this study is to develop a methodology to observe safety performance within the immediate vicinity of interchanges in the state of Iowa. The study involves the integration of traffic crashes (point features), volume and roadway geometry (polyline features). Buffers were created 1500 feet around each interchange in ArcGIS to select only roads that were 1500 feet from the interchange ramp terminal. In the case that interchanges were so close to each other, the problem of which interchange got the road segments attached to it up to 1500 feet was resolved by using an arc tool “create points from lines” to convert the road polylines to point features. Using the “Generate near table” tool, a near table was then created for the number of points closest to each interchange. A select by location scheme was used to associate crashes to each segment of the roadway for crashes up to 100 feet from each interchange segment. A heat map showing the high-risk areas based on crash rates on each interchange type will be created from this crash detection process.


 

May 3, 2017 (three presentations during Finals Week)
2:00 to 4:30

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

An Enhanced Framework for Dynamic Segmentation of Pavement Sections Using Python

Adviser: Dr. Brian Gelder

Abstract: 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.

 

Kurt Wilson, GIS Certificate Candidate, Department of Anthropology

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

Adviser: Dr. Matthew Hill

Abstract: 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 d13C 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 d13C 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.

 

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

Distribution and Resiliency of Ring-necked Pheasants in Iowa

Advisers: Dr. Stephen J. Dinsmore and Dr. Julie A. Blanchong

Abstract: 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.

 

 

 

 


 
 
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Department of Community and Regional Planning, College of Design, Iowa State University, Ames, Iowa 50011-3091



Monica A. Haddad