Innovation [X] Program Results

The School of Innovation is proud to announce the following recipients of the inaugural Innovation [X] Program:
 

  • Dr. Muthukumar Bagavathiannan, College of Agriculture and Life Sciences
  • Dr. Theodora Chaspari, College of Engineering
  • Mr. Dustin Kemp​, LAUNCH
  • Dr. Leslie Ruyle, Bush School of Government and Public Service
  • Dr. Yangyang Xu, College of Geosciences
  • Dr. Lei Zou, College of Geosciences


Student Application for Participation in an Innovation [X] Project
We encourage students interested in being a part of one of these year-long projects to complete the online application for consideration.

Learn About the Innovation [X] Program
Proposal Guidelines and Selection Criteria

Questions About a Project?
Please feel free to contact the leaders of the individual projects (see below).

Innovation [X] Project Description

Name: Dr. Muthukumar Bagavathiannan 
Email: muthu@tamu.edu
Phone: 979-845-5375

Team Leaders:
Dr. Muthukumar Bagavathiannan, Assistant Professor (Weed Science), Department of Soil and Crop Sciences, School of Agriculture and Life Sciences
Dr. Vijay Singh, Assistant Research Scientist (Weed Science), Department of Soil and Crop Sciences, School of Agriculture and Life Sciences
Prof. Stavros Kalafatis, Professor of Practice, Department of Electrical and Computer Engineering, School of Engineering
Dr. John Lusher II, Associate Professor of Practice, Department of Electrical and Computer Engineering, School of Engineering

Team Contributors:
Faculty from School of Engineering and School of Agriculture and Life Sciences

Units Represented: Department of Soil and Crop Sciences, School of Agriculture and Life Sciences, Department of Electrical and Computer Engineering, Mechanical Engineering, Electrical and Communication Engineering, Industrial Engineering

Background: Weeds are the major pests of crop fields and herbicides have been the most preferred tool for weed management. Along with the benefits of herbicides, comes the drawbacks such as contamination of water bodies (Hallberg 1987) and residues in food produces (Zilberman et al. 1991). 

These health and environmental concerns have promoted organic farming as an alternative agricultural system. Organic crop acreage has increased to 5.0 million from 1.3 million between 2002 and 2016 (USDA-NAAS 2017). However, organic culture has many challenges regarding pest management, which needs to be addressed. 

A survey conducted by the United States Department of Agriculture in 2014 had identified weed management among the top challenges facing organic farming, and insufficient weed control options is a commonly cited reason behind slow adoption of organic agriculture in the U.S. (McBride and Greene 2015). 

Lasers have been suggested as a useful non-chemical weed control tool under laboratory conditions (Methiassen et al. 2006). However, killing several weed plants with a single laser is not feasible under field applications and improvements are necessary in this regard.

Goals: The overall goal of this project is to design a laser-based weed control system by utilizing machine learning-based algorithms to detect weed plants, make real-time weed management decisions on pre-established criteria, and execute precision laser applications using a robotic platform. The major objectives of the proposed research are to 1) evaluate and standardize lasers for weed control under field conditions, and 2) develop and test a robotic laser system prototype for automation of weed control in row crops. This project will involve students/researchers from different departments across Texas A&M University, including the Department of Soil and Crop Sciences and Electrical and Electronics Engineering, with specialization in areas such as weed science, plant physiology, computer science, programming, image analysis, robotics and hardware engineering.  

We conducted a preliminary study during fall 2018 on evaluation of the impact of laser exposure timings on eight different weed species (broadleaves and grass weeds) during the fall of 2018, in collaboration with a group of four undergraduate engineering students as a semester-long capstone project. Plants were grown in a greenhouse and were exposed to a red laser beam (2.5 W) at 2-to 3-leaf stage (5-10 cm tall) for 3 and 5 secs. We observed that laser exposure of 2-3 secs was sufficient to kill grass weeds. However, broadleaf weeds could be controlled only at 5 secs. Some of the weeds, such as giant ragweed (Ambrosia trifida) could not be controlled even at 5 secs exposure. Differential response of different weeds has suggested that we need to test high powered (>5 W) lasers for broadcast exposure to control all types of weed species. 

This small preliminary study conducted this past fall has allowed us to understand the potentials and limitations of laser-based weed control and provided us directions as to what the focal areas should be. It also allowed us to experiment and be comfortable with the system. We developed this Innovation [X] proposal to test the hypotheses we developed during this past fall in order to generate robust preliminary data, which will be instrumental for federally-competitive grants. 

Within the scope of this Innovation [X] grant, we will specifically focus on the following improvements: 1) safe integration of high-powered lasers in the subsystem, 2) use of real-time weed tracking system instead of image-based classification, 3) increasing the computing power of the system, 4) integration of multiple lasers in the system for uniform coverage, and 5) develop a prototype robotic platform for effective delivery of the laser system. These improvements will be vital to convince federal funding agencies in order to develop a robust laser system with field applications.

Projected Outcomes: The proposed research project has tremendous national and international importance, especially in organic agricultural systems as well as in conventional systems where proliferation of herbicide resistant weeds is an emerging concern. It is anticipated that this work would gain enormous national and international attention, with great opportunities for IP generation and commercial applications down the road. We anticipate that the project will produce at least one patent application and two peer-reviewed international journal articles. Additionally, the robust set of preliminary data expected to be collected from this research will pave the way for further research supported by federal grant funds.

Name: Dr. Theodora Chaspari
Email: chaspari@tamu.edu 
Phone: 979-458-2205

Team Leaders: 
Dr. Theodora Chaspari, Assistant Professor, Computer Science & Engineering
Dr. Anastasia Muliana, Professor, Mechanical Engineering
Dr. James E. Hubbard Jr., Professor, Mechanical Engineering

Team Contributors: 
Dr. Winfred Arthur, Professor, Psychology
Dr. Youngjib Ham, Assistant Professor, Construction Science
Dr. Jennifer Ganz, Professor, Educational Psychology
Dr. Negar Kalantar, Assistant Professor, Architecture
Dr. Dongying Li, Assistant Professor, Architecture

Units Represented: Computer Science & Engineering, Mechanical Engineering, Psychology, Construction Science, Educational Psychology, Architecture

Background: Light, colors, smells, and noises are several of the environmental factors that consciously or unconsciously affect our mood, cognition, performance, or even physical and emotional health. Prolonged thermal discomfort is associated with “sick-building” symptoms (e.g. dry throat), as well as serious health implications (e.g., hypothermia, loss of concentration, fatigue). Ambient light can moderate stress responses: warm-tone light is associated with increased alertness which might increase stress levels in comparison to cool-tone light. Exposure to prolonged noise can cause a range of health problems (e.g., stress, productivity loss, cardiovascular diseases). For individuals with neurological abnormalities, such as children with autism spectrum disorders (ASD), environmental discomfort yielding from noises, scents, light, and heat, can feel like a continuous bombardment. The inherent individual differences escalate these challenges. The environmental sensation is different for each person and a single condition cannot fit all individuals, therefore outlining the need of personalized solutions.
 
Goals: The team proposes an intelligent and adaptive indoor living space which can continuously and unobtrusively “sense” each individual’s neuro-physiology, and then seamlessly and intuitively adjust the local environment (e.g., temperature, light) in a unique and personalized way to mitigate negative outcomes (e.g., increased stress). This effort relies on a cross-discipline between architecture, material science, construction science, psychology, and computer science, and consists of the three interconnected objectives.

Aim 1. Leveraging neuro-physiological indicators to identify individuals’ stress. A series of experiments will be undertaken to examine the relationship between neuro-physiological signals and human stress. Data collection will include 44 participants (18-30 years)–a sample size calculated by power analysis–, who will complete a series of cognitive tasks (e.g., proof-reading, online orders, email responses). A between-subjects design will be followed according to which each participant will be randomly assigned to one of the following conditions: (i) neutral, participants perform the assigned tasks at their own pace; (ii) time pressure, participants are given a reduced amount of time for the same tasks. In addition to retrospective self-reported stress levels, physiological responses (e.g., heart rate) and brain signals will be collected through commercially available wearable devices. Data analysis will identify significant neuro-physiological differences between the neutral and stress conditions.

Aim 2. Designing intelligent responsive and reconfigurable panels to achieve personalized environmental conditions. We will engineer responsive panels that can vary in size and can be effortlessly installed in stationary cubicles, furniture, or portable interior walls. Temperature and cool-light conditions will be manipulated through the panels, since these are the most relevant to mitigating stress. The panel’s basic elements are adaptive cells with multiple reconfigurable segments and imprinted apertures. Manipulation of the environmental conditions will be performed by the closing and opening of the apertures of the responsive panel, which will be connected to inlet and outlet of air circulating and cool-lighting systems.Aim 3. Assessing the ability of the adaptive-responsive environment to mitigate individuals’ stress response. The proposed responsive panels will be deployed with a new set of 44 participants, engaged in the same series of cognitive tasks as in Objective 1. The target degree of aperture opening will be based on the estimated/predicted level of stress (e.g., high stress will lead to increased aperture opening in order to reduce temperature and increase cool light conditions). Statistical analysis will identify whether the deployment of responsive architectures can significantly mitigate participants’ stress levels, as quantified by neuro-physiological and self-reported measures.
 
Projected Outcomes: The expected outcomes of the proposed work include: 1) research publications in high-impact conference and journals (e.g., IEEE Transactions on Affective Computing, International Journal of Non-Linear Mechanics); 2) a publicly available multimodal corpus to promote research on human-building interaction; 3) research findings regarding the interaction of humans with the surrounding environment, which will be used to pursue federal and industrial grant opportunities (e.g., NSF Smart & Connected Health, Department of Energy, Department of Education); 4) development of publicly available online repository of the proposed algorithms and structural design; 5) Master’s and undergraduate honor students’ theses. In the long-term, the findings from this work will be institutionalized creating novel modules in the PIs’ undergraduate and graduate classes (e.g., Machine Learning, Engineering Mechanics, Studio Design).

Name: Mr. Dustin Kemp
Email: dkemp@tamu.edu 
Phone: 979-845-1031

Team Leaders: 
Mr. Dustin Kemp, Capstone Program Assistant for LAUNCH
Dr. Sarah Gatson, Associate Professor, Sociology
Dr. Suma Datta, Professor, Biochemistry & Biophysics, Assistant Provost for Undergraduate Studies, Executive Director for LAUNCH
Ms. Kelsey Hirsch, Constellation Learning Community Program Coordinator, LAUNCH 

Team Contributors: 
Dr. Joe Sharkey, Professor, Health Promotion and Community Health Sciences, School of Public Health
Ms. Lisette Templin, Instructional Assistant Professor, Health and Kinesiology
Dr. Craig Coufal, Associate Professor and Extension Specialist, Associate Department Head for Extension, Poultry Science

Units Represented: LAUNCH, Sociology, Biochemistry & Biophysics, Constellation Learning, School of Public Health, Health and Kinesiology, Poultry Science

Background: 36% of students are food insecure—they worry about having enough food, skip meals or cut down on meal quality and size due to lack of funds.  Food-insecurity correlates with higher stress, worse sleep, and poorer grades and is most common among underrepresented (UR), low income (LI), or first generation (FG) students, categories that encompass 25% of TAMU students, especially those that lag in retention and graduation rates.  Texas Census data predict this group will only increase.  Food insecurity is real on our campus, and resonates as an important issue with our students, staff, and faculty.

LAUNCH is organizing “The Hunger Consortium” as a highly visible way for organizations, faculty, students, and staff with an interest in food insecurity to find collaborators and opportunities. Our goal is to provide a place for students, staff, and faculty to find resources to address the problem through research, teaching, and service. 
Part of the Hunger Consortium is LAUNCH’s First Year Eats pilot which started in Fall 18 for UR, LI, FG freshmen with “Eating on a Budget”, online bilingual resources for cooking cheap, nutritious meals, and “Mug Meal” cooking workshops.

Goals: The primary goal of this proposal is to increase student success through increased education and skill building about food and use of food provided through the LAUNCH program First Year Eats (FYE), thereby helping to close the achievement gap between FG, LI, or UR freshmen and others.  We will increase success through a “proof of principle” FYE pilot to address food insecurity in Constellation, a freshman living learning community for FG, LI, UR students. We will use a multi-pronged attack on food insecurity: Everybody Eats (vegetable/herb grow bags for student rooms), Vertical Tower Gardens (education and access to vertical tower gardens), and Cooking with Constellation (cooking lessons/events, collaborations to generate sustainable sources of ingredients and “grab-and-go” food items, and shopping/budgeting/nutrition workshops).  The fourth team, Freshman Food Insecurity, will assess food insecurity among Constellation freshmen. For each of the first three approaches in FYE we will evaluate activities through process and outcome assessments of 1) overall student engagement, 2) approach-specific student preferences, 3) timeline of student engagement, and 4) sustainability of student interest.  To determine if our overall FYE plan works, we will assess levels of food insecurity, retention and GPR for students in Constellation compared to control groups.

Our FYE programming for decreasing food insecurity will be available to all students living in Clements Hall, rather than focusing only those in Constellation or self-identifying as food-insecure, a principle known in sociological terms as “targeting within universalism”.  Engaging all students in Clements will help prevent students in need from avoiding FYE resources due to the stigma of being identified as food-insecure, a stigma so strong that 50% of students nationwide who identify as food-insecure will not use a food bank when available.

Our secondary goal is the creation and documentation of sustainable structure, programming, collaborations, and resources for FYE with an eye towards continuing and improving FYE in coming years and expanding it to other living learning communities.  FYE began as a series of “one-off” events in response to student disclosures that they had used up their meal plans (sometimes as early as October) and were going hungry, even as the popular press began publicizing hunger on college campuses. A survey of freshmen in Clements hall, which houses Constellation, showed that as early as September our Regents Scholars were already identifying as food-insecure.  The data we collect over the course of the year will show us which FYE approaches are successful in drawing student interest, are used throughout the year, and for individual approaches what specific ingredients, recipes, events, and educational workshops students are drawn to.

Projected Outcomes: We anticipate four major outcomes based on documentation of FYE structure, programming, and results: 1) professional publications/presentations, 2) development of a compelling story that provides a basis for soliciting additional collaborations and donations, 3) evidence that encourages wider adoption of FYE at TAMU and other institutions, and 4) preliminary results to support grant proposals to foundations and relevant government entities.

Given the enthusiasm with that FYE and our “one-off” events produced around campus, we expect that data which link addressing food-insecurity to greater academic success of FG, LI, or UR freshmen at TAMU will create more opportunities for research, service, and teaching by faculty, staff, and students.

We hope that teaching freshmen to cook Mug Meals and Crockpot Cuisine will have impact far beyond their freshman year, especially as they move off campus and become more responsible for their diet and nutrition within a limited budget.

Name: Dr. Leslie Ruyle
Email: ruyle@tamu.edu
Phone: 979-862-3469

Team Leaders:
Dr. Leslie Ruyle, Associate Research Scientist and Assistant Director, Scowcroft Institute of International Affairs, Bush School of Government and Public Service
Dr. Cecilia Giusti, Associate Dean for Outreach and Diversity, College of Architecture
Associate Professor, Department of Landscape Architecture and Urban Planning

Team Contributors:
Dr. Richard Lester, Clinical Professor, Executive Director of the McFerrin Center for Entrepreneurship, Mays Business School
Dr. David Flint, Clinical Professor, Mays Business School
Dr. Brian Colwell, Professor, Department of Health Promotion & Community Health Sciences, School of Public Health
Dr. Christine Blackburn, Assistant Research Scientist, Scowcroft Institute of International Affairs, Bush School of Government and Public Service
Dr. Catharina Laporte, Instructional Assistant Professor, Department of Anthropology, College of Liberal Arts

Units Represented: Bush School of Government and Public Service, College of Architecture, Mays Business School, School of Public Health, College of Liberal Arts

Background: In 2017, we launched an entrepreneurship program in Beni, DRC coined EC3. This effort is a practical intervention for conflict mitigation as well as a way of learning how to support entrepreneurs in regions of conflict, limited connectivity (roads, electricity, internet), and conservation concern (EC3). In 2018, weeks after the launch of the 2nd cohort of entrepreneurs, an Ebola outbreak was declared in Beni. This created an unseen opportunity for learning about the impact of Ebola response on the economics of the town. Since the Ebola outbreak, foreign aid workers have converged on Beni, renting every hotel room, packing restaurants, and generally disrupting the local economy. Using data collected before the launch of EC3, we want to understand the boom and eventual bust of this relief effort on the economy. This research project will build a bridge between three TAMU programs: EC3, the McFerrin Center on Entrepreneurship, and the Pandemic Preparedness and Policy Program at the Scowcroft Institute to create a unique and impactful outcome in learning for the students, while informing international development professionals on the boom and bust economics from a pandemic.

Goals: The goals of this project are to better understand the boom and bust economics of disaster response in a region where entrepreneurship is already on fragile footing. While the original program was created to support entrepreneurs in regions of conflict, limited connectivity, and conservation concern, the Ebola outbreak brought in an additional variable of perturbation. With the expertise of the Pandemic Program at the Bush School, it seemed an ideal opportunity to learn about the effect of Ebola on the local economy while also having an appropriate audience to share final results. We were also eager to find ways to include students in real world understanding of current crises without putting them in danger. Before the EC3 Program was launched, we conducted a business climate survey to understand the dynamics of the economy. We collected data on entrepreneurs in the Program for a year before Ebola struck and continue to work with entrepreneurs during the response. Funds from this grant will allow us to measure the post Ebola economic response by expanding the expertise to a diverse faculty group, include students in real world learning, and communicate results via the Pandemic Summit and a publication. An interdisciplinary team from Architecture, Bush School, Mays, the SPH, and AgriLife will work together on drafting questions for a survey to be given to entrepreneurs in the DRC. We will recruit 4 master’s and/ or PhD students to lead the writing, analysis, and presentation of the results at the Scowcroft Summit and publication in the White Paper. We will also include 12 undergraduates from the McFerrin Center program who will work in teams of 3 along with a lead master’s or PhD student. These four teams will talk with entrepreneurs in the EC3 Program collecting anecdotal data to supplement the survey data collected during the summer. The phone call method is feasible because Dr. Ruyle maintains weekly contact with EC3 Program staff and has also engaged international mentors using this method. Entrepreneurs are familiar with the method and eager to share their stories. Students fluent in French or Swahili could serve as translators for their teams, or the EC3 Program staff can interpret on the calls. During the summer, we will travel to DRC to work with EC3 staff and enumerators to conduct the survey and bring data back to the TAMU team for analysis in the Fall before the Summit in November. Student teams will present their findings at the Summit and then prepare a submission for the White Paper which will be released at the National Press Club in May 2020. Results from the study will be used to inform the EC3 program and shared with international development professionals . Our students will interact, via Skype, with Congolese entrepreneurs surviving an epidemic and gain real world understanding of entrepreneurship, pandemic response and recovery, and the boom and bust dynamics on the economy in international development in response to Ebola.

Projected Outcomes: We see multiple outcomes from this project benefitting students, faculty, practitioners of disaster response, and people affected by pandemics. We will have at least 1 publication and a unique platform to share our work, influence policy, and further expose students to practitioners, government officials, and scholars through Scowcroft’s 2 yearly events on Pandemic Preparedness and Response. To date, the economic impact of pandemic response has not been covered. Students and faculty would have unique opportunity and platform to share their results with the impressive list of attendees at these events who include the CDC, WHO, and other high ranking members in governments, practitioners in development, and international attendees. Additionally, there is a TOP grant to involve students in pandemic response simulations. With this grant, we would include the economics angle as well as the health response. Students would present real data on the boom and bust of Ebola response in Beni.

Name: Dr. Yangyang Xu 
Email: yangyang.xu@tamu.edu
Phone: 979-845-8076

Team Leaders:
Dr. Yangyang Xu, Assistant Professor, Atmospheric Sciences, College of Geosciences
Dr. Xiaohui Xu, Associate Professor, Biostatistics, School of Public Health

Units Represented: Atmospheric Sciences, College of Geosciences, Biostatistics, School of Public Health

Background: Heat extremes kill thousands of people globally every year. Even though the appearance of heat extreme episode is not as striking as other natural disasters, it is indeed the one causing the most economic losses as well as causality according to the report released by National Oceanic and Atmospheric Administration (NOAA). Therefore, it is notoriously dubbed as a ‘silent killer’. Heat extreme is also a global problem that has caused wide spread concerns and media coverage in tropical regions as well as regions traditionally having cooler summers.

Heat extreme can cause acute effects in human health, leading to strokes and heart attacks, but also the lingering effect on public health. The negative health impact places particular burden on vulnerable groups (children, elderlies and those who have chronic diseases) and social-economically disadvantaged groups (such as those who lived in inner cities with no green space around, or population in developing nations without easy access to air conditioning). The associated issue of environmental injustice has caused great concerns in social science research in the last few years and urgently need an interdisciplinary solution.

Goals: The overarching goal of this project is to generate such a comprehensive dataset of environment and demographical data, deliver the interpretation to stakeholders, and actively engage students and local residents in the process of knowledge creation and dissemination.

The three tasks to achieve this goal are detailed below.

(1) Data generation.

We aim to quantify the meteorological heat extreme as well as the accurate exposure of population in major US cities (especially in Austin, Houston, Dallas, and San Antonio in Texas and Florida). We will collect the temperature record from various sources including (a) the ground network of meteorological stations, (b) newly available remote sensing products based on land surface infrared retrieval, and (c) the newly developed high-resolution regional climate model coupled with land module. 

These data sources have their own advantages and limitation. For example, the remote sensing dataset have good spatial coverage over many urban areas and enables easier scaling-up of our approach and generalization of knowledge gained, but the passive remote sensing suffer from uncertainties in its accuracy. Moreover, an important quantity for heat extreme health impact studies, the relative humidity, is poorly measured using remote sensing approaches. The third data source, high-resolution regional climate model, will help to extrapolate the missing data in any observation sources, but the model bias -- when compared against with observations -- should be properly adjusted for, before any rigorous scientific conclusion can be drawn.

(2) Data visualization and analysis

We will generate detailed maps of temperature, humidity, web-bulb temperature, heat index, and a few other quantities in high spatial resolution maps. The heat map will be overlaid over geospatial features, such as urban boundary, population, and building types, and coverage of greenspace, which enables further analysis. 

The population dataset is another main novelty of this project, for which we will adopt a newly developed dynamic population dataset that tracks the diurnal (hour to hour) redistribution of urban population (e.g. due to commute for work). The heat exposure from the high-resolution meteorological dataset and dynamic population dataset will be a major step forward from the existing studies in which the results are mostly based on static population and rather coarse spatial dataset (e.g. one city may only have 5-10 data points over it).

(3) The synthesis and knowledge distribution.

We will write a report based on the main research findings in accessible language and present the report to the stakeholders at various cities. The main success of this project will be evaluated based on the reception and feedback provided by the stakeholders. We in particular aim to reach out to the health management community as well as social-economically disadvantaged community (in Houston area).

Projected Outcomes: The three tasks as proposed here will generate three distinct outcome.

The fused dataset will be delivered via a visualization site (with google map or google Earth engine providing the spatial feature). The actual codes and data obtained as the end result will be shared via open sourced dataset and code repository, free of charge for academic use.

The data analysis results will be published in peer-reviewed journals, likely open-access to both climate and public health communities. The main authors of the papers will be the graduate student involved. The undergraduate students will also wrote first-author paper and publish them in student-only journal such as the LAUCH journal here in the University.

The public report will be written in more accessible languages and distributed to public domain for free. The hard copied of the report will be mailed to relevant NGOs and governmental offices.

Name: Dr. Lei Zou
Email: lzou@tamu.edu 
Phone: 979-458-1803

Team Leaders: 
Dr. Lei Zou, Visiting Assistant Professor (appointed Assistant Professor, effective Aug. 2019), Department of Geography, College of Geosciences
Dr. Dongying Li, Assistant Professor, Department of Landscape Architecture and Urban Planning, College of Architecture

Team Contributors: 
Dr. Lei Zou, Visiting Assistant Professor (appointed Assistant Professor, effective Aug. 2019). Department of Geography, College of Geosciences
Dr. Dongying Li, Assistant Professor, Department of Landscape Architecture and Urban Planning, College of Architecture

Units Represented: Department of Geography, College of Geosciences, Department of Landscape Architecture and Urban Planning, College of Architecture, Urban Planning, Public Health

Background: Disaster resilience is the capacity of a community to prepare for, absorb, recover from and adapt to disastrous events. A variety of resilience measurement models have been proposed, but most aim at developing standardized metrics. Although standardization can facilitate comparison and uniform disaster recovery policy, it hinders the development of place-based solutions that address the challenges and resilience goals of specific communities. As an operationalized concept, both the anticipated resilience goals and process to achieve the goals rely heavily on local contexts, including the size of the community, demographics, affluence and deprivation, as well as the underlying economic and social structures. The dynamics in environmental and human systems also demand the goals to be ever-adaptive. Therefore, externally imposed and static resilience frameworks often fall short in stimulating local changes in disaster preparedness and recovery. To fill these gaps, this project aims to develop and evaluate an innovative resilience framework based WebGIS that for participatory goal setting, real-time volunteered geographic information, data computation and analysis, and feedback loops.

Goals: The main goal of this project is to develop a customized resilience measurement framework through WebGIS-enabled community engagement, service learning and citizen science. The Manchester/Harrisburg neighborhood in Houston has been selected as the test bed, because of high minority population, poverty, complex socio-economic issues, and severe losses during Hurricane Harvey. The specific objectives are:

1. Develop a WebGIS application that integrates data visualization, user interaction and resilience modeling. The app fulfills three missions: 
First, it monitors and visualizes local disaster-related information dynamically. The app integrates official environmental, plan-related, and socio-economic information, and mines social media (e.g., Twitter) to analyze disaster assistance request and recovery-related sentiments. Second, the platform supports user determined resilience goals by prompting for importance ratings of key recovery metrics and local design suggestions. Based on the input, an online module will compute community disaster resilience and identify key local social-environmental factors based on the CRIM framework (Obj.3). Third, the outcomes of the model are displayed, with additional functionalities to retrieve and compare multiple previously specified models. 

2. Conduct community meetings through an interdisciplinary service-learning studio class to calibrate the CRIM framework. 
We will develop a service-learning GeoDesign studio (LAND602/URPN 493) to increase students’ exposure to resilience modeling and community engagement. Through Texas Targeted Communities (TTC), we will build connections with Manchester neighborhood and hold community meetings. Students will assist participants from different interest groups to develop their resilience goals and generate output. Using the model results and key social-environmental factors identified, the class will develop specific goal-oriented design scenarios and action plans with the public.

3. Complete the Customized Resilience Inference Measurement (CRIM) framework for assessing community disaster resilience. 
The CRIM framework will be completed based on PI Zou’s previously published Resilience Inference Measurement model combined with the customized resilience goals acquired through public engagement (Obj.2). The model assesses disaster resilience based on the exposure to hazards, damage sustained, and post-disaster recovery. Local resilience levels are estimated using k-means clustering of the customized indicators for three dimensions. Social-environmental factors contributing to or impeding disaster resilience will be assessed using Bayesian networks. 

4. Test the applicability of framework by crowdsourcing. 
The platform will be open to the public in the U.S. Data Display and computing capabilities will be expanded. User input and model results will be used to evaluate the applicability and limits of the framework beyond the initial test community.

Projected Outcomes: Four major outcomes are anticipated:

1. Publications: We expect to publish the CRIM framework and its applications in high impact journals such as Global Environmental Change and Annals of the American Association of Geographers. 

2. Web Application: The WebGIS platform developed will be open to the public, facilitating work of disaster planners, researchers, community advisory groups and every resident. 

3. Vertical Integration in Education: The vertical GeoDesign studio at the 4th undergraduate and 2nd graduate levels will involve students from LAND, URPN, GEOG and PHLT. Students will participate in webGIS mapping, model specification, resilience driven community planning and design, and become fully involved in community engagement. 

4. Social Impacts: Fourth, we will strengthen our partnerships with Houston communities through Texas Targeted Communities, and produce white papers on the planning and design outcomes

Contact the School of Innovation
Robert Shandley
Associate Dean, School of Innovation
innovationx@tamu.edu 
(979) 862-6071
 
Emily Finbow
Assistant Director, School of Innovation
innovationx@tamu.edu
(979) 862-6071