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2010 Winners of the MN GIS/LIS Consortium Scholarship abstracts and bios
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Brian Barklind - Saint Mary's University of Minnesota – Grad
Michael Campbell - St. Cloud State University – Grad
Gail Evans - Fond du Lac Tribal and Community College
Ashley Keul - Minnesota State University, Mankato – Undergrad
Colin Lee - University of Minnesota, Twin Cities – Undergrad
Katie Leonard - Minnesota State University, Mankato – Grad
Maggie Pearson - Macalester College – Undergrad
Paul Reamer - Bemidji State University – Undergrad
Margaret Voth - University of Minnesota, Twin Cities – Grad
Jack Westman - St. Thomas University – Undergrad
Scott Wirta - Itasca Community College

Undergraduate:
 
 
The Southern Utah Wilderness Alliance (SUWA) is a coalition of concerned citizens seeking wilderness designation for a large swath of public land vulnerable to resource development in southern Utah. This project will create an interactive web-based map application to be embedded on the homepage of the non-profit organization’s website to illustrate the areas covered under their proposed legislation, America’s Red Rock Wilderness Act of 2009. Detailed descriptions of regional units will be linked with pop-up photos to demonstrate the immediacy of preserving these pristine wilderness-quality lands for future generations.
 
 
The use of Airborne LiDAR as a supplement and sometimes replacement to conventional photogrammetry is a growing trend. Quick turnaround and high accuracy make LiDAR derived terrain data an appealing alternative to conventional photogrammetry. However, there are major differences that set these two methods of topographic mapping apart. The difference I am most interested in is the generation of contours. Often times the usefulness of contour mapping relies on the aesthetics that breaklines from conventional photogrammetry introduce. The bare-earth point dataset provided by LiDAR contains no breaklines. This makes it difficult to create topographic maps of photogrammetric accuracy and usefulness (0.5’ to 1’ contours)(Kelly & Loecherbach, 2006). Here lies my first challenge. Can breaklines be added to a LiDAR point dataset in a way that is cost effective while retaining a high level of accuracy relative to the initial accuracy of the LiDAR dataset?
LiDAR produces massive volumes of data and very large files sizes that can slow even the fastest computing systems down. I believe this issue is inherently tied to the creation of breaklines. The introduction of breaklines should allow for a mass thinning of unnecessary points within the LiDAR dataset. In this way I hope to reduce file sizes and improve workflow.
In order to answer these questions I will employ a number of software programs. LP360 extension to ArcMap will be used to reproject and export bare-earth point files derived from LiDAR datasets. The Geopack extension to Bentley's MicroStaion will be used to filter the pointfiles in an attempt to reduce the file size. Pseudo stereo pairs created from .las intensity files viewed in Summit’s Evolution software may allow me to create breaklines. My goal is to reduce the file sizes and produce a more aesthetically useful contour map without compromising accuracy.
 
 
The Katherine Ordway Natural History Study Area is a 280-acre nature preserve owned by Macalester College located in Inver Gove Heights, Minnesota. In the summer of 2010, a team of student researchers worked alongside faculty advisors to study vegetation at the site. We began the summer with the installation of a 20m by 20m research grid based on UTM coordinates. We installed 328 stakes for the grid this summer; when completed, this grid will allow research to be easily continued into the future and integrated into our digital database. Once we established our grid, we chose 10 cells for in depth research of the nonnative species garlic mustard (Alliaria petiolata), with the goal of understanding why garlic mustard grows in some parts of the forest and not others. As we collected garlic mustard data, GIS users integrated the data into our GIS database for the nature preserve. Once all field data was collected, we used GIS to find other environmental factors, such as elevation, that may influence where garlic mustard grows. To conclude our summer we made a series of maps for our primary and secondary data to aid in the explanation of the research results.

 
At Bemidji State University (BSU), providing affordable and efficient public transportation for students has been a difficult challenge. To address key issues of routing and usage, BSU partnered with Paul Bunyan Transit Service to provide BSU students with low cost and free transportation service in and around the greater Bemidji Area.
As part of this endeavor, much of the traditional methods of recording and assessing transportation usage had to be revised. This project demonstrates both research and application development of a new system that has created efficiencies in transportation route selection. To these ends, it utilizes a series of GIS maps, GIS analysis, and raw field data collected in the Fall of 2009. These data revealed correlations between BSU student arrival and departure times and locations which exposed a number of efficiencies in the current system. The input of the raw field data was interfaced directly into the ArcGIS geodatabase through a custom VB.Net application interface that provided relevant GIS Map output.
From this analysis a revised and more automated public transportation route system was derived which better serves the BSU community.
 

The goal of this project is to model various levels of flooding in the Fargo/Moorhead area, on the Red River of the North. As an employee of the US Army Corps of Engineers' GIS Center for the past year and a half, I have access to a wealth of LiDAR data that would be instrumental to an accurate hydrographic modeling of the target area. One of the Corps' primary responsibilities is monitoring and protecting against flooding, especially along the Red River between North Dakota and Minnesota. In recent years, flooding on the Red River has captured national attention, as it has impacted thousands of lives and millions of dollars worth of property and infrastructure, so modeling is a very important undertaking for those involved in flood protection.
By modeling flooding for different variables, such as water levels and surface permeability, one can obtain results that show areas in need of additional flood protection, such as levees and revetments. Not only does this project seek to identify areas of concern, and to determine impacts that various levels of flooding might have on the area, it also attempts to give people an idea of how the modeling process actually works, and explain the variables that go into modeling, the statistical process, and what the various outputs mean. In my analysis, I plan to make use of LiDAR data in conjunction with software, such as ArcGIS, Global Mapper, and extensions, such as HEC-RAS or TUFLOW, as well as other data and programs as needed.
 
Graduate:
 

Improving the methods for determining which areas should be prioritized for conservation efforts may be accomplished by using indicators such as biodiversity. The data provided by the United States Geological Survey’s Breeding Bird Survey (BBS) has made calculating changes in biodiversity over a specified time frame possible. By using the bird survey data available for the state of Minnesota, analysis was performed to determine the levels of biodiversity in each area of the state during various time periods. Along with spatial analysis, statistical analysis was performed on the data by using the Statistical Package for Social Sciences (SPSS). Results of the analysis indicated that there was a significant (P < 0.05) correlation between the proportion of natural land cover and the amount of avian diversity. Future studies may be able to develop predictive models using this and other correlatives. By predicting richness levels, priority may be placed on specific areas within the state for conservation efforts.
 
 
This study focuses on using LiDAR derived DEMs from Crow Wing County to analyze the relict shorelines of the southeastern end of Glacial Lake Aitkin. The main purpose of this study is to test the feasibility of using LiDAR derived DEMs to provide high spatial resolution imagery for analyzing large scale areas to provide a basis for using a similar technique on larger glacial features. The LiDAR DEMs will be ground tested and also compared to existing DEM datasets at coarser resolutions.
 

The Lake Crystal Area Recreation Center (LCARC) services a wide range of people and multiple communities providing a safe and fun family health facility. Through this study a graphical representation of the members of LCARC will be created, with this map of its members and through spatial analysis, data will be gathered on rates of member check ins, distance traveled by members, and information about general demographic patterns. Analysis will be completed to determine relationships between distance traveled and membership numbers or types as well as ideal advertising locations for each demographic groups. This information will then be put to use by the LCARC board of directors in hopes of creating and implementing more effective marketing strategies as well as better ways to serve its members.
 

According to the Clean Water Act, Minnesota must publish a biennial report assessing water quality trends in Minnesota’s public lakes and navigable waters. Though phosphorus concentration, suspended sediment, and chlorophyll concentration are the major factors in determining water clarity, such measurements are prohibitively time consuming and expensive when considering Minnesota’s nearly 12,000 lakes. Secchi disk transparency sampling provides a cheap, easy, and repeatable measure of water transparency, though it still requires in-situ data collection that is not feasible in the remote and sparsely populated areas of the state. Though state agencies employ both state-funded and volunteer programs to collect secchi disk transparency measurements, only a fraction of Minnesota’s lakes are sampled in any given year. Previous researchers have also speculated that recreational and residential lakes may be overrepresented in the current secchi disk samples.
MODIS data from six dates between May and October of 2006 were calibrated using in-situ secchi disk measurements to predict per pixel water clarity for large Minnesota lakes at each image date. Secchi disk data were filtered prior to calibration to remove spectral bias due to cloud cover, lake bottom effects, and aquatic vegetation. MODIS pixel values surrounding each secchi disk point were averaged to reduce errors due to wind, water reflection, and varying lake depth. The model accuracies were generally acceptable, indicating that red and blue MODIS bands show promise for future monitoring of within-season water quality trends, particularly when investigating sources of water quality problems such as turbidity or algae blooms. Spatial patterns in Minnesota’s lake clarity and their similarity to previous Landsat studies will also be examined.
 
Community College Student Competition
 
My project will introduce you to a disease that you may have heard of but many people cannot explain what it really is. Lupus is an autoimmune disease with a wide variety of clinical manifestations. It is a disease that affects women primarily, between the ages of 15 and 45. Different races are affected more than others. Death from Lupus has increased from 879 in 1979 to 1,406 in 1998. There are four types of Lupus which I will give information on. There are risk factors that I will introduce along with symptoms, causes and complications. I will also attempt to use the risk factors and census data to create a map of the possible cases of Lupus out there and why there is a need for more research and awareness for this disease. I will try to investigate possible high-risk populations for Lupus.

Wetlands: Gaining or Losing Ground?
Scott Wirta, Itasca Community College
 
In 1991 the Minnesota Legislature passed the Minnesota Wetlands Conservation Act. A key point of this legislation was that there should be no "net-loss” of wetlands. In 2000, revisions to the Public Waters Inventory, made a consistent statewide definition of wetlands. Wetlands in Minnesota are categorized into 8
types: seasonally flooded basin or flat, wet meadow, shallow marsh, deep marsh, shallow open water, shrub swamp, wooded swamp and bog. Wetlands play a vital role in their surrounding environment and are homes to a great number of species of plants and animals.
Taking a look at a few local wetlands, I hope to get a sense of whether they are shrinking, holding steady, gaining in size, or possibly even disappearing.
Comparing this year’s (2010) aerial photography two years previous, I hope illustrate the changes in area. Running an NDVI (Normalized Difference Vegetation Index) analysis of the wetland and surrounding areas will give a slightly better picture of the relative health of the green vegetation. I will also be comparing images from this year to National Wetlands Inventory data.
These three general measurements should give us a better sense of the growth and health of the studied wetlands.
 
 
Our congratulations go out to all of the recipients for a job well done!
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