FACT: A Framework to Comprehensively Evaluate, Distribute and Catalog Geospatial Data Sources Used in the Study of the Food Environment

FACT: A FRAMEWORK TO COMPREHENSIVELY EVALUATE, DISTRIBUTE AND CATALOG GEOSPATIAL DATA SOURCES USED IN THE STUDY OF THE FOOD ENVIRONMENT

Sponsoring Institution

National Institute of Food and Agriculture

Project Status

ACTIVE

Funding Source

AFRI COMPETITIVE GRANT

Reporting Frequency

Annual

Accession No.

1025596

Grant No.

2021-67021-34152

Cumulative Award Amt.

$364,500.00

Proposal No.

2020-08825

Multistate No.

(N/A)

Project Start Date

Feb 15, 2021

Project End Date

Dec 14, 2024

Grant Year

2021

Program Code

[A1541]- Food and Agriculture Cyberinformatics and Tools

Project Director
Mulrooney, T.

Recipient Organization
NORTH CAROLINA CENTRAL UNIVERSITY
1801 FAYETTEVILLE ST
DURHAM,NC 277073129

Performing Department
Env., Earth and Geo. Sciences

Non Technical Summary
It is difficult to comprehensively explain the nexus at food-needy regions, spending patterns, health outcomes and explanatory factors behind them. Quantitative methods explore numerical relationships between food availability, food access and food utilization. They help, though not fully explain it using a variety of metrics such as proximity, race/ethnicity, poverty status and access to transportation, among other things. A Geographic Information System (GIS) serves as a powerful tool to examine quantitative spatial relationships that exist between and among the various agents within the food environment. These agents may include source locations (where people are traveling from) and destinations (where people are traveling to) in order to procure all forms of food, both healthy and unhealthy, as well as those aforementioned socio-economic variables. However, little work has been performed to measure the quality of data used in these analyses. This project presents a framework to quantitatively assess, evaluate, deliver and catalog GIS data sources used in food environment research. The results can have a profound impact on the spatial representation of food deserts and food swamps versus those who are truly food-needy. This problem symbolizes a need for expanding the use of geospatial, information and statistical technologies to relatable social phenomena that disproportionately affects underrepresented segments of the population. These underrepresented populations compose a large portion of the student body at the proposed research institution and this work will facilitate statistical and information literacy, as well as the soft skills and field training necessary to be successful in the workforce.

Animal Health Component

50%

Research Effort Categories

Basic

50%

Applied

50%

Developmental

(N/A)

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
609	7299	2060	50%
609	7299	2090	20%
609	7299	3030	30%

Knowledge Area
609 - Economic Theory and Methods;

Subject Of Investigation
7299 - Research equipment and methods, general/other;

Field Of Science
2090 - Statistics, econometrics, and biometrics; 2060 - Geography; 3030 - Information and communication;

Keywords

data analysis

data quality tools

geographic information systems

research data

Goals / Objectives
Provide resources and develop frameworks for the development, use and validation of high-quality geospatial data to be used in food environment research.Provide students with the opportunity to develop workflows and models to assess the validity of geospatial data sources.Provide students and researchers with the opportunity to solve large-scale problems that marry technical and non-technical problem-solving skills.Develop forward-thinking solutions in a field of study that has been largely unexplored in the GIS community and provide students and researchers to be trendsetters in this field.Provide education resources, both formal (classroom and tutorial) and informal (workshop, field work, outreach) to students, faculty and the community about the use and application of geospatial technologies to QA/QC analysis and food environment outcomes.Understand concepts of statistical testing, including margins of error, sample sizes, significances, error, MAUP (Modifiable Areal Unit Problem) and null hypotheses, and how they apply and interact with the real-world field verification of food environment data.Create a platform in which corrected geospatial data can be distributed to the GIS-user community using FAIR (Findable, Accessible, Interoperable and Reusable) principles.Create a means to catalog data collected during this research using existing ISO-based data standards and how these standards can be applied to corrected and evolving data.In support of these goals, the following are the objectives for this proposal.15 Students (4 in first year, 5 in second year, 6 in year 3) will earn stipends by identifying and addressing a research problem related to this proposal that requires the use of GIS and employs GIS skills to solve this research problem as it relates to the food environment.5 faculty will apply GIS QA/QC and field-based methods into their teaching to facilitate problem-based learning to encourage critical thinking, data integration and problem solving among their students in topics related to the assessment and evaluation of the food environment.20 faculty and students will obtain competence in GIS methods of data collection, analysis, and presentation through coursework, off-site training and assistantships.4 graduate students (1 assistantship per academic year with 2 during the second year) will be supported in order to develop workflows, mentor undergraduate students and present research in topics related to the technologies revolving around this research proposal.6 students (2 internships per summer - 1 graduate and 1 undergraduate) will be supported in order to perform work in which they address larger problems related to the QA/QC of the digital representation of the food environment and its delivery to the larger user community.At least 20 students and faculty will be provided with travel and presentation opportunities at forums such as the Association of American Geographers Annual Meeting, the North Carolina GIS Conference, the Applied Geography Conference, the North Carolina Geographical Society Meeting and the Applied Economics and Agriculture Annual Meeting.At least 15 new data layers attached to this project will be catalogued and served to the larger GIS user community for the seamless access of data for use in their research or courses taught by the PI or co-PI at NCCU.

Project Methods
In this project, the research team proposes to expand upon the pilot project and perform QA/QC and subsequent analysis on six different regions throughout the state of North Carolina to determine the veracity of data. These regions include various regions to include highly urbanized regions, as well as rural areas amongst different socio-economic groups. For each study area, 400 points will be randomly selected. Research will encompass the following: (1) acquisition of datasets; (2) domain field development, database development and random sampling of points (3) algorithm to visit points in data set (4) ground-truthing of datasets; (5) test hypotheses; (6) identification of correlations (7) sharing and (8) finally cataloguing of data.(1) Acquisition of Datasets: As with this and other GIS-based studies on the food environment, analysis must be based on data developed from scratch or provided as commercially available business (CAB) data. The creation of both, regardless of data developer, can be expensive and/or prone to all types of error. These data were provided as point locations by InfoUSA for the year 2018 and updated yearly. Other data regarding the food environment will be acquired, such as the Dun and Bradstreet database (which was used as a basis for the ESRI dataset in 2014) and NC FarmFresh, a database containing the locations of all farmers' markets in the state. (2) Database Development and Random Sampling: Using the Select by Attributes functionality, food sources will be selected according to their NAICS (North American Industry Classification Standard) code, a multinational (United States, Canada and Mexico) standard which classifies business establishments by their primary economic activity. Six different cohorts include: 1) Superstores that provide food 2) Fruit and Vegetable Markets 3) Supermarkets and Other Groceries 4) Convenience Stores 5) Fast-Food Restaurants and 6) Limited Service Restaurants. These cohorts were further classified as "healthy" and "unhealthy" food sources, where that supermarkets and other groceries, fruit and vegetable markets and superstores that provide food are defined as "healthy" food while "unhealthy" food is represented by convenience stores, limited service restaurants and fast-food restaurants.For each study area, 400 randomly selected food sources will be divided between each of the two major divisions of food ('healthy' vs. 'unhealthy') within urban and rural food sources. In order to maintain consistency in field verification for hypothesis testing, 100 urban healthy (UH) sources will be randomly selected, as well as 100 rural healthy (RH), 100 urban unhealthy (UU) and then 100 rural unhealthy (RU). As a result, 200 urban features within the GIS database will be field checked against 200 rural food sources in the same database. 200 healthy sources will be checked against 200 unhealthy counterparts. (3) Algorithm to Visit All Points in Dataset: Using the ArcGIS Network Analyst tools, the New Route command determines the fastest route between a set of locations. For each study area, the 400 points will be placed into manageable subsets (counties) for each of the field verification teams. Using GIS data provided by the North Carolina Department of Transportation (NCDOT), each team will be assigned a subset, calculate the quickest route and visit the field. (4) Ground-Truthing of Datasets: For each study area, all 400 points will be randomly selected and placed into a database for field verification. The goal of field verification will be to determine 1) if the business was actually located where the GIS database dictates 2) if the business was still in operation 3) if the business activity (fast food, for example) is correct.(5) Test Hypotheses: Using the test of two proportions (Equation 1), various Null hypotheses (some shown in Table 2) will be tested to determine if differences exist between the accuracies of field-verified features for various cohorts. Not only will regions be compared to each other (Study Area #1 vs. Study Area #4), but accuracy will be agglomerated for each cohort. For example, the research team may want to see if the accuracy rural farmers' market is equal urban farmers' markets across all study areas.(6) Geostatistical Analysis of Results: GIS analysis, geostatistical and ESDA techniques will be performed to measure spatial autocorrelation, the degree to which attributes (accurate or inaccurate) are related to those around it. Spatial autocorrelation techniques include: Average Nearest Neighbor Analysis, Anselin Local Moran's I, Moran's I, Getis-Ord General G, Ripley's K, Optimized Hot-Spot Analysis, Mean Center and Directional Distribution.Once these steps have been completed on the dataset, the research team will perform the following steps on the entire dataset or portions of the dataset developed as part of this research.(7) Using cloud-based technologies, the research team will provide corrected data to the GIS user community through a web portal such as ArcGISOnline. Students will explore ways in which datasets of this size can be optimally delivered to the GIS user community. (8) In addition to the delivery of geospatial data, these newly-corrected data will be catalogued using the North Carolina State and Local Government Metadata Profile. This profile is based off the ISO-19115 metadata format and is an accepted standard for use in North Carolina.

Progress 02/15/23 to 02/14/24

Outputs
Target Audience:This proposal has mainly focused on researchers and the community on the efficacy of using ground and cloud-based technolgoies to assess and evaluate data related to the food environment. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?The following master's theses/projects were successfully defended during this assessment period supported or partially by this grant. Mike Wallace, COVID-19Rates and Proximity to Meat and Poultry Processing Plants in North Carolina(Graduated Spring 2023) Quinton Butler,Low-Income and Minority Communities Access to Grocery Stores and Convenience Stores in Durham County(Graduated Spring 2023) Isabel Gutierrez,Utilizing Field Apps and Geospatial Statistics to Assess and Evaluate the Quality of Commercially Available Data Representing the Food Environment(Graduated Spring 2023)* Chima Okoli,Meta-Statistics Describing Social Vulnerability Indicators in the Region 7 District of North Carolina(Graduated Fall 2023)*. Samuel Akinnusi,A Comparative Geostatistical Analysis of Raster-Based Metric to Other Traditional Vector-Based Metric for Food Availability Study(Graduated Fall 2023)*. How have the results been disseminated to communities of interest?In addition to the papers and student thesis project attached this report, the following are county health reports. These and the data which compose these maps are being added to our open data hub and catalogued using ISO-based metadata standards that can be utilized in concert with food accessibility metrics. Franklin County -https://storymaps.arcgis.com/stories/72b486fc082c46b2aa97ed1587b15ace Granville-Vance Counties -https://storymaps.arcgis.com/stories/ab799b6219094062973f81afec516a30 Johnston County -https://storymaps.arcgis.com/stories/7975d21f0444427c909dca9cf4cdcb79 Nash County -https://storymaps.arcgis.com/stories/cce6b37ac52347d7873709b1d93a44f3 Wake County -https://storymaps.arcgis.com/stories/284f80e086f947c2a95b7a4eb4c118e1 Warren County -https://storymaps.arcgis.com/stories/e1c65ffdb0444961be5f659b0b7b3c46 Wilson County -https://storymaps.arcgis.com/stories/fdc8b7a93a204801a5a0c025e65f6387 We have data analytics attached to these pages so the team can see which county and which metric has the most views. At the time of this writing, Wilson County has the most number of viewers with metrics related to race/ethnicity were viewed the most across all counties. What do you plan to do during the next reporting period to accomplish the goals?As we finish this paper, our major goalis to consolidate and build our data hub to incorporate all projects, papers and resources. We would like usership to go from the hundreds to tens of thousands in the future (Goal #7)

Impacts
What was accomplished under these goals? The automation of techniques and development of programming scripts to convert services, stand-alone tables, social media and citizen-provided data into a GIS-compatible format that can be utilized by researchers. Data created from various sources are referred to ascompiled data. Advancement of theory and methodology include the exploration of various types of citizen science-created information (public participation GIS, social media, public-volunteered), an assessment of these data and methodology of how this information can be converted into a systematic format that can be integrated into research.?

Publications

Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Mulrooney, T. and Gutierrez, I. 2023. Revisiting Food Deserts in North Carolina, USA, Using a Cloud-Based Real-Time Quality Assurance/Quality Control (QA/QC) Tool. In Proceedings of the 9th International Conference on Geographical Information Systems Theory, Applications and Management, ISBN 978-989-758-649-1, ISSN 2184-500X, pages 115-122. DOI: 10.5220/0011713500003473
Type: Journal Articles Status: Published Year Published: 2024 Citation: Mulrooney, T., Akinnusi, S., McGinn, C., Esimaje, T and Okoli, C. 2024. A Comparison of Raster-Based Point Density Calculations to Vector-Based Counterparts as Applied to the Study of Food Availability, Agriculture and Food Security. 13,5. DOI: https://doi.org/10.1186/s40066-023-00455-z
Type: Other Status: Other Year Published: 2023 Citation: Utilizing Field Apps and Geospatial Statistics to Assess and Evaluate the Quality of Commercially Available Data Representing the Food Environment, Isabel Gutierrez, North Carolina Geographical Society Meeting, March 2023. (student presentation)
Type: Other Status: Published Year Published: 2023 Citation: COVID-19 Rates and Proximity to Meat and Poultry Processing Plants in North Carolina, Mike Wallace, North Carolina Geographical Society Meeting, March 2023. (student presentation)
Type: Other Status: Published Year Published: 2023 Citation: Measuring Low-Income and Minority Communities' Access to Grocery Stores and Convenience Stores in Durham County, Quinton Butler, North Carolina Geographical Society Meeting, March 2023. (student presentation)
Type: Other Status: Published Year Published: 2023 Citation: "Metastatistics Describing Social Vulnerability Indicators in the Region 7 District of North Carolina", Chima Okoli, SEDAAG Conference, November, 2023. (student presentation)
Type: Other Status: Published Year Published: 23023 Citation: "A Comparative Geostatistical Analysis of a Raster-Based Metric to Other Traditional Vector-Based Metric for Food Availability Study", Samuel Akinnus, SEDAAG Conference, November, 2023. (student presentation)
Type: Other Status: Published Year Published: 2023 Citation: Mapping the increase of egg prices across the United States, Getanew Lemons, North Carolina Geographical Society Meeting, March 2023. (student poster presentation)
Type: Other Status: Published Year Published: 2023 Citation: Mapping the Effects of Covid-19 Virus on Cattle by County in North Carolina, Michael Berryann, North Carolina Geographical Society Meeting, March 2023. (student poster presentation)
Type: Journal Articles Status: Published Year Published: 2023 Citation: Mulrooney, T., Liang, K., Kurkalova, L., McGinn, C. and Okoli, C. 2023. Quantitatively Defining and Mapping Rural: A Case Study of North Carolina. Journal of Rural Studies, 97: 47 56.
Type: Other Status: Published Year Published: 2023 Citation: A Study of Food Distribution Service Range by Block Group in Durham County, Benjamin Williams, North Carolina Geographical Society Meeting, March 2023. (student poster presentation)
Type: Theses/Dissertations Status: Published Year Published: 2023 Citation: Mike Wallace, COVID-19 Rates and Proximity to Meat and Poultry Processing Plants in North Carolina (Graduated Spring 2023)
Type: Theses/Dissertations Status: Published Year Published: 2023 Citation: Quinton Butler, Low-Income and Minority Communities Access to Grocery Stores and Convenience Stores in Durham County (Graduated Spring 2023)
Type: Theses/Dissertations Status: Published Year Published: 2023 Citation: Isabel Gutierrez, Utilizing Field Apps and Geospatial Statistics to Assess and Evaluate the Quality of Commercially Available Data Representing the Food Environment (Graduated Spring 2023)
Type: Theses/Dissertations Status: Published Year Published: 2023 Citation: Chima Okoli, Meta-Statistics Describing Social Vulnerability Indicators in the Region 7 District of North Carolina (Graduated Fall 2023)
Type: Theses/Dissertations Status: Published Year Published: 2023 Citation: Samuel Akinnusi, A Comparative Geostatistical Analysis of Raster-Based Metric to Other Traditional Vector-Based Metric for Food Availability Study (Graduated Fall 2023)

Progress 02/15/22 to 02/14/23

Outputs
Target Audience:During the reporting period from 2/22through 2/23, our target audience has been reached through academic research in the form of journal articles and class presentations. Furthermore, the development of the web application to perform field research was completed as of 12/21 and the use of this tool began in 1/22 with a study area of 5 counties around the NCCU campus. It has been used for study areas across the state of North Carolina. In the interim, journal articles highlighting preliminary research on food deserts, QA/QC of existing data have been published by the research team. As part of the class titled Sustainable Food Systems (ENSC 2800), the PIs taught a class where students looked at data-driven approaches to assessing and evaluating the food environment. These projects are highlighted in the products produced from this project. Changes/Problems:There are no problems or issues to report. What opportunities for training and professional development has the project provided?1- Development of ENSC 2800 (Sustainable Food Systems) class which was offered in the Fall of 2022 as a direct result of this grant project. It was taken by 16 students and will be offered again. 2- Deliveryof GEOG 4950(Field Mapping) class which was offered in the Summer Intersession of 2022 as a direct result of this grant project. Students learned skills in app develoment, field surveys and on-the-fly maps. It was taken by 14 students and will be offered again. 3 - Developing of training materials through YouTube Page. How have the results been disseminated to communities of interest?1- Development of ENSC 2800 (Sustainable Food Systems) class which was offered in the Fall of 2022 as a direct result of this grant project. It was taken by 16 students and will be offered again. 2- Deliveryof GEOG 4950(Field Mapping) class which was offered in the Summer Intersession of 2022 as a direct result of this grant project. Students learned skills in app develoment, field surveys and on-the-fly maps. It was taken by 14 students and will be offered again. 3 - Developing of training materials through YouTube Page. What do you plan to do during the next reporting period to accomplish the goals?1 - We will be presenting at the following forums: NC Geographical Society Symposium, GIS TAM Conference and processing all raw data collected.

Impacts
What was accomplished under these goals? 15 Students (4 in first year, 5 in second year, 6 in year 3) will earn stipends by identifying and addressing a research problem related to this proposal that requires the use of GIS and employs GIS skills to solve this research problem as it relates to the food environment. 6 students have been supported with stipends as shown through the class project and more plan to be presenting at research forums. 5 faculty will apply GIS QA/QC and field-based methods into their teaching to facilitate problem-based learning to encourage critical thinking, data integration and problem solving among their students in topics related to the assessment and evaluation of the food environment. Faculty across the Department of Environmental, Earth and Geospatial Sciences (DEEGS), Public Administration, and Kinesiology and Recreation Administration (KRA) have utilized the data for this project. 20 faculty and students will obtain competence in GIS methods of data collection, analysis, and presentation through coursework, off-site training and assistantships.17 students and faculty have gained competence in field data collection and analysis. 4 graduate students (1 assistantship per academic year with 2 during the second year) will be supported in order to develop workflows, mentor undergraduate students and present research in topics related to the technologies revolving around this research proposal.2 graduate students were fully supported during this time period. 6 students (2 internships per summer - 1 graduate and 1 undergraduate) will be supported in order to perform work in which they address larger problems related to the QA/QC of the digital representation of the food environment and its delivery to the larger user community.1.5 internships were provided for students related to theQA/QC of the digital representation of the food environment and its delivery to the larger user community. At least 20 students and faculty will be provided with travel and presentation opportunities at forums such as the Association of American Geographers Annual Meeting, the North Carolina GIS Conference, the Applied Geography Conference, the North Carolina Geographical Society Meeting and the Applied Economics and Agriculture Annual Meeting.17 students and faculty have been providedwith travel opportunities at forums such as the North Carolina Geographical Society Symposium, Southeast Geography Conference, GIS-Transportation and Transportation Research Board. At least 15 new data layers attached to this project will be catalogued and served to the larger GIS user community for the seamless access of data for use in their research or courses taught by the PI or co-PI at NCCU. Many data layers have been created in support of this project which reside at:https://services5.arcgis.com/FmxVFcLfGZgh8t6m/arcgis/rest/services

Publications

Type: Journal Articles Status: Published Year Published: 2023 Citation: Mulrooney, T., Liang, K., Kurkalova, L., McGinn, C. and Okoli, C. 2023. Quantitatively Defining and Mapping Rural: A Case Study of North Carolina. Journal of Rural Studies, 97: 47 56.
Type: Conference Papers and Presentations Status: Accepted Year Published: 2023 Citation: Mulrooney, T. and Gutierrez, I. 2023. Revisiting Food Deserts in North Carolina, USA, Using a Cloud-Based Real-Time Quality Assurance/Quality Control (QA/QC) Tool. Proceedings of the GIS-TAM (Technology, Applications, Management) Conference (accepted, awaiting publication).
Type: Other Status: Accepted Year Published: 2022 Citation: Okoli, Chima. 2022. Defining and Mapping Rural: Comparisons of Political, Demographic, Economic and Health Phenomena using varying definitions of Rural in North Carolina. North Carolina Geographical Society Annual Meeting. Greensboro, NC, March 18th.
Type: Other Status: Published Year Published: 2022 Citation: Radel, Sarah. 2022. Using Spatial Analysis and Density Techniques to Show the Correlation Between Cancer Mortality and Active Superfund Sites in North Carolina. North Carolina Geographical Society Annual Meeting. Greensboro, NC, March 18th.
Type: Other Status: Accepted Year Published: 2022 Citation: Okoli, Chima and Akunnusi, Samuel. 2022. Spatial-Temporal Analysis of COVID-19 Between Urban and Rural Regions over the Course of the Pandemic. Southeast Division of the Association of American Geographers Annual Meeting. Atlanta, GA, November 21st.
Type: Websites Status: Published Year Published: 2022 Citation: Brandon Codrington. Food Security in North Carolina. Semester presentation for ENSC 2800 - Sustainable Food Systems. https://storymaps.arcgis.com/stories/bcb1eba72642402388f323e601dc0a35
Type: Websites Status: Submitted Year Published: 2022 Citation: Ariel Mial. Food Access and Poverty in Durham, NC. Semester presentation for ENSC 2800 - Sustainable Food Systems. https://storymaps.arcgis.com/stories/13a07d04939f4ee191e9079d63221bbf
Type: Websites Status: Accepted Year Published: 2022 Citation: Jordan Herrington. Food Access Vs. Crime In Durham County. Semester presentation for ENSC 2800 - Sustainable Food Systems. https://storymaps.arcgis.com/stories/d173277f2ce34d5bbb311e1133c069c3
Type: Websites Status: Published Year Published: 2022 Citation: Nyanda Williams-McNatt. Food Environment/Security in Rural Sampson County. Semester presentation for ENSC 2800 - Sustainable Food Systems. https://storymaps.arcgis.com/stories/0e048a07460b4c17aede84761bc84cf1
Type: Websites Status: Published Year Published: 2022 Citation: Alana Petifer. The Food in my Neighborhood. Semester presentation for ENSC 2800 - Sustainable Food Systems. https://storymaps.arcgis.com/stories/017889deb3674482a3c04792f553d38c
Type: Websites Status: Published Year Published: 2022 Citation: Jaden McGee. Food Security in Texas. Semester presentation for ENSC 2800 - Sustainable Food Systems. https://storymaps.arcgis.com/stories/1ab6a11ee24446069ec7009722766749
Type: Websites Status: Published Year Published: 2022 Citation: Ellandra Howell. The Food Environment Between High Schools In The Same County. Semester presentation for ENSC 2800 - Sustainable Food Systems. https://storymaps.arcgis.com/stories/12c11a1ea3dc41baae2980520f05d9b5
Type: Websites Status: Published Year Published: 2022 Citation: Lauren Johnson. Charles County Food Environment. Semester presentation for ENSC 2800 - Sustainable Food Systems. https://storymaps.arcgis.com/stories/8b0956ae045d44a8abedea752a8ef5fc
Type: Websites Status: Published Year Published: 2022 Citation: Tamarr Moore. The Food Environment Around Northwood HS Pittsboro NC. Semester presentation for ENSC 2800 - Sustainable Food Systems. https://storymaps.arcgis.com/stories/f16deb96e753470784002099200c5e9d
Type: Websites Status: Published Year Published: 2022 Citation: Cambria White. A Vegetarian's Guide to Eats In and around Durham, North Carolina. Semester presentation for ENSC 2800 - Sustainable Food Systems. https://storymaps.arcgis.com/stories/9a1df510941a4eabb510b2f7bd29e710
Type: Websites Status: Published Year Published: 2022 Citation: Benjamin Williams. Alcohol and Spending. Semester presentation for ENSC 2800 - Sustainable Food Systems. https://storymaps.arcgis.com/stories/aa86e4faa3f64d33a1e5cde145f641cb
Type: Websites Status: Published Year Published: 2022 Citation: James Grace. Wildfires in the World and their Impact on Agriculture. Semester presentation for ENSC 2800 - Sustainable Food Systems. https://storymaps.arcgis.com/stories/17d2c9dab61e48f582f8cb92618d2daa
Type: Websites Status: Published Year Published: 2022 Citation: Sarah Radel. Mapping North Carolina's Climate. Semester presentation for GEOG 4950 - Field Mapping. https://storymaps.arcgis.com/stories/680271b336d745fbadba3f037b6c55e1
Type: Other Status: Published Year Published: 2022 Citation: Mike Wallace. Tracking Land Cover Change using Satellite Imagery. Semester presentation for GEOG 4950 - Field Mapping.
Type: Other Status: Published Year Published: 2022 Citation: Wallace, Mike. 2022. Geostatistical Assessment of COVID-19 Rates and Proximity to Meat and Poultry Processing Plants in North Carolina. North Carolina Geographical Society Annual Meeting. Greensboro, NC, March 18th.
Type: Other Status: Published Year Published: 2022 Citation: Rodney Hawkins. Tracking Population Change in North Carolina, 2010 - 2020. Semester presentation for GEOG 4950 - Field Mapping.
Type: Websites Status: Published Year Published: 2022 Citation: Chima Okoli. An Esri StoryMap Approach to show Healthy Food Access within the NCCU Campus Neighborhood. Semester presentation for GEOG 4950 - Field Mapping.
Type: Other Status: Published Year Published: 2022 Citation: Chima Okoli. Mapping Food Walkability around the NCCU Campus. Semester presentation for GEOG 4950 - Field Mapping.

Progress 02/15/21 to 02/14/22

Outputs
Target Audience:During the reporting period from 2/21 through 2/22, our target audience has been reached through academic research in the form of journal articles. Furthermore, the development of the web application to perform field research was completed as of 12/21 and the use of this tool began in 1/22 with a study area of 5 counties around the NCCU campus. In the interim, journal articles highlighting preliminary research on food deserts, QA/QC of existing data have been published by the research team. At the current time, two articles are being developed by the research team. As the COVID-19 pandemic hopefully comes to an end, we plan to disseminate research results at conferences and symposium. Changes/Problems:There are no major changes or deviations to hte currently plan or approach. The field tool has been created and is ready to be used. We look foward to the results. What opportunities for training and professional development has the project provided?1. A field mapping course (GEOG 4950, EASC 5050) was offered during the intersession (mid-May) 2021 session where we developed field applications in support of this project. Students performed field work and created custom data that was intergrated into the QA/QC tool that was created for this project. 2. YouTube videos were created through the department's YouTube Site that implement techniques learned from this research at:https://www.youtube.com/user/DEEGSNCCU How have the results been disseminated to communities of interest?Two journal articles have already been published. One was to Applied Geography, a well-known geography journal while another was published to a state-level geography journal. Planned research at conferences will occur when the pandemic allows face-to-face presentations and as we agglomerate the results of our research. What do you plan to do during the next reporting period to accomplish the goals?1. Planned presentations include the GIS-Transportation Conference on travel algorithms and a student-written paper. 2. A field tool was recently completed and will be used in the field over the Spring. We anticipate results to see the difference between the database and what is found in the field. We will then move on to other study areas as dictated by our SOW. 3. Planned presentations at a Medical Geography Symposiumn and Agricultural Resarch Symposium on the implementation of the tool and preliminary results which will be ready over the summer. 4. At least 3 study areas (we are currently working on #1) will be completed by this time next year and 2 graduate students will be fully engaged.

Impacts
What was accomplished under these goals? Provide resources and develop frameworks for the development, use and validation of high-quality geospatial data to be used in food environment research.The framewok has been developed and will be utilized in the field beginning 1/2022. Results will be agglomerated from this field research which will take place in waves over the next 2 years. Provide students with the opportunity to develop workflows and models to assess the validity of geospatial data sources.1 graduate student has been instrumental in the development of these frameworks and another will begin in the Spring 2022 semester. Provide students and researchers with the opportunity to solve large-scale problems that marry technical and non-technical problem-solving skills.This problem has required both technology and loosely coupled research. Develop forward-thinking solutions in a field of study that has been largely unexplored in the GIS community and provide students and researchers to be trendsetters in this field.This field application is one of the first of its kind, and we will be working on the first round of results in the Summer of 2022. Provide education resources, both formal (classroom and tutorial) and informal (workshop, field work, outreach) to students, faculty and the community about the use and application of geospatial technologies to QA/QC analysis and food environment outcomes. YouTube tutorials have been created from this research and a field mapping course using the ArcGIS Collector tool that has been utilized as the QA/QC tool is used in a Field Mapping course developed by the PI and co-PI. Understand concepts of statistical testing, including margins of error, sample sizes, significances, error, MAUP (Modifiable Areal Unit Problem) and null hypotheses, and how they apply and interact with the real-world field verification of food environment data.These have been covered in detail as part of this project. Create a platform in which corrected geospatial data can be distributed to the GIS-user community using FAIR (Findable, Accessible, Interoperable and Reusable) principles.At the current time, all data are being written to the cloud that can be accessed from hand-held devices utilizing FAIR principles. Create a means to catalog data collected during this research using existing ISO-based data standards and how these standards can be applied to corrected and evolving data.We will be developing an ISO-based metadata standard once the first study area is finalized in the Summer of 2022. In support of these goals, the following are the objectives for this proposal. 15 Students (4 in first year, 5 in second year, 6 in year 3) will earn stipends by identifying and addressing a research problem related to this proposal that requires the use of GIS and employs GIS skills to solve this research problem as it relates to the food environment. Currently, 2 students have been utilized. Another graduate student will be getting onto the grant with 1 other undergraduate student earning a stipend in the Spring 2022 semester. 5 faculty will apply GIS QA/QC and field-based methods into their teaching to facilitate problem-based learning to encourage critical thinking, data integration and problem solving among their students in topics related to the assessment and evaluation of the food environment. At this time, 3 faculty have been enaged in this research, with research highlighting phone apps, field work and statistical analysis. 20 faculty and students will obtain competence in GIS methods of data collection, analysis, and presentation through coursework, off-site training and assistantships. At the time, 5 faculty and students have been directly engaged in this process while a field mapping course was taken by 6 other students. As the pandemic eases, we plan to engage more students and faculty for off-site training, assistantships, field work and presentations. 4 graduate students (1 assistantship per academic year with 2 during the second year) will be supported in order to develop workflows, mentor undergraduate students and present research in topics related to the technologies revolving around this research proposal. 2 graduate students have been engaged in this project. 6 students (2 internships per summer - 1 graduate and 1 undergraduate) will be supported in order to perform work in which they address larger problems related to the QA/QC of the digital representation of the food environment and its delivery to the larger user community. During the summer of 2021, 1 graduate student began work and we plan to have 3 students for the summer of 2022. At least 20 students and faculty will be provided with travel and presentation opportunities at forums such as the Association of American Geographers Annual Meeting, the North Carolina GIS Conference, the Applied Geography Conference, the North Carolina Geographical Society Meeting and the Applied Economics and Agriculture Annual Meeting. 1 student have been given a presentation opportunity due to the pandemic. We plan on taking 4 students to a conference in April in support of this work and another 5 students to the NC Geography Conference in March if our university allows. At least 15 new data layers attached to this project will be catalogued and served to the larger GIS user community for the seamless access of data for use in their research or courses taught by the PI or co-PI at NCCU. We are currently working on 4 new data layers, with more planned for the future.

Publications

Type: Journal Articles Status: Published Year Published: 2021 Citation: Mulrooney, T., Foster, R., Jha, M., Hashemi Beni, L., Kurkalova, L., Liang, C.L., Miao, H., Monty, G. 2021. Using Geospatial Networking Tools to Optimize Source Locations as Applied to the Study of Food Availability: A Study in Guilford County, North Carolina. Applied Geography 128: https://doi.org/10.1016/j.apgeog.2021.102415.
Type: Journal Articles Status: Published Year Published: 2021 Citation: Mulrooney, T., McGinn, C., Madumere, C. and Ifediora, B. 2021. A Comprehensive Assessment and Evaluation of the Digital Geospatial Data Sources Used in the Study of Food Deserts and Food Swamps. The North Carolina Geographer, 20: 13 -27.
Type: Journal Articles Status: Awaiting Publication Year Published: 2022 Citation: Mulrooney, T., Mulrooney, E. and McGinn, C. 2022. Exploring Rural Food Insecurity in North Carolina: Debunking an Urban Myth. Sociation - Journal of the North Carolina Sociological Association, 20(2): 40 50.
Type: Conference Papers and Presentations Status: Published Year Published: 2022 Citation: Gutierrez. Isabel. 2022. Using Travel-Time Algorithms to Measure Food Accessibility in the Research Triangle Region, North Carolina Transportation Research Board Annual Meeting. Washington D.C., January 12th.