Source: TEXAS A&M UNIVERSITY submitted to NRP
RAPID ASSESSMENT PROTOCOL FOR DISASTER RESPONSE (RAPDR) – A HYPER-RESOLUTION SATELLITE IMAGERY AND DEEP LEARNING ENABLED DECISION SUPPORT TOOL
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
ACTIVE
Funding Source
Reporting Frequency
Annual
Accession No.
1032850
Grant No.
2024-68016-43058
Cumulative Award Amt.
$299,370.00
Proposal No.
2024-05705
Multistate No.
(N/A)
Project Start Date
Jul 15, 2024
Project End Date
Jul 14, 2026
Grant Year
2024
Program Code
[A1712]- Rapid Response to Extreme Weather Events Across Food and Agricultural Systems
Recipient Organization
TEXAS A&M UNIVERSITY
750 AGRONOMY RD STE 2701
COLLEGE STATION,TX 77843-0001
Performing Department
(N/A)
Non Technical Summary
Starting on February 24, 2024, the Panhandle wildfire quickly spread within days, making it the largest wildfire in Texas history. The scale of the destruction has been enormous, with many people facing the loss of their homes and other structures, livestock, and forage, and while the fire is now contained, the damages are expected to grow as additional assessments are conducted.The immediate concern post-disaster is to ensure the safety and well-being of the affected communities, for which a clear understanding of the extent and severity of damage is imperative. Despite the known urgency, a comprehensive assessment of the Panhandle wildfire damages is still far from complete, andthe full scope of the current Panhandle wildfire structure damage and forage loss still is not known. There is an urgent and critical need for developing innovative technologies and an effective decision support tool that can enable rapid and comprehensive damage assessment in response to large wildfires and similar future disasters in Texas.To address those challenges, this project aims to develop and implement innovative technological approaches and an effective decision support tool and protocol for rapid disaster response in Texas. This project will develop a hyper-resolution structure damage classification map and fine-resolution forage loss and recovery datasets based on remote sensing observations. This project will also develop and implement a decision support tool for Texas A&MDisaster Assessment and Recovery (DAR) unit to support rapid assessment and recovery efforts for the Panhandle wildfire and similar future disasters in Texas. This project will lead toa significant improvement in the effectiveness of rapid response to disasters such as the Panhandle wildfire across Texas.
Animal Health Component
100%
Research Effort Categories
Basic
(N/A)
Applied
100%
Developmental
(N/A)
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
8070120107050%
7230120107025%
8010120107025%
Goals / Objectives
Our over-arching goals are to (1) develop cutting-edge technologies and tools to enable rapid and cost-effective assessment of wildfire damage of agricultural infrastructure and forage loss at regional scales in Texas, and (2) develop and implement a decision support tool and protocol for rapid response to large wildfire in Texas. We will(1) utilize hyper-resolution remote sensing and advanced deep learning models to generate hyper-resolution structure damage classification maps for the entire Texas Panhandle wildfire-impacted region, (2) develop fine-resolution maps of forage loss and their recovery over time, (3) seek input from key stakeholder groups and compile a comprehensive list of damage information needed for effective disaster assessment and response, (4) develop a decision support tool based on the needs assessment and the new technologies developed, and (5) engage stakeholders in outreach efforts to promote awareness and access to the damage information generated, to support disaster preparedness, response, and recovery.
Project Methods
We will use the following methods to achieve our goals and generate our expected products and outcomes: (1) develop Transformer deep learning-based structure damage identification models by leveraging hyper-resolution remote sensing data; (2) generate fine-resolution maps of the forage loss and recovery based on the satellite image time-series analysis; (3)conduct surveys and focus groups to seek input from key stakeholder groups to build a comprehensive list of specific damage information needed for disaster response actions immediately following a rangeland wildfire or similar disasters; (4)develop a decision support tool, namely Rapid Assessment Protocol for Disaster Response (RapDR), for the Disaster Assessment and Recovery (DAR) unit to support rapid assessment and recovery efforts after rangeland wildfires and similar disasters. This tool will be designed based on the damage information needs assessment and include a GIS database with pre-processed and updated key spatial data layers necessary for disaster response planning and assessment, and protocols to produce decision support information/maps for stakeholders from the products generated by the hyper-resolution satellite imagery and deep learning models; and (5)develop Extension and outreach programming on the RapDR, its damage and monitoring information products, and methods for accessing the information products, as well as roles and resources of different agencies and organizations involved in disaster response and relief. We will conduct this programming for personnel of related agencies and organizations to enhance their preparedness, and potentially their coordination, for effective rapid response to disasters. We will also design and conduct similar outreach programming for landowners and youth in areas being affected or with the potential to be affected by wildfire, to both promote awareness and access to the damage information that may be useful to them and enlist their participation in collecting onsite damage information and submitting using designated apps. We will deliver these programs in both in-person and virtual formats and will develop social media campaigns with key elements of these programs to broaden the reach.

Progress 07/15/24 to 07/14/25

Outputs
Target Audience:Our audiences include educators and disaster response professionals, landowners and rangeland resource managers, students and public. Educators and disaster response professionals learn new cutting-edge technologies for rapid and cost-effective assessment.Landowners and rangeland resource managers learn near-real time forage and structure damage and recovery for timely future plans.Students and public develop awareness of rangeland disasters, the threats to them, and effective mitigation strategies. Changes/Problems:The major changes in approach is about our development of remote sensing based wildfire building damageassessment. We improved our model to be applicable under all weather conditions. This is mainly because when we are doing the assessment of building damage, the California wildfire happed and we noticed thick smoke weather condition couldhamperthe assessment from space. The California wildfire smoke weather made us revise our current optical remote sensing based methods into data fution of SAR (Synthetic apertureradar)and Optical remote sensing images to make our assessment have the capacity to penetrate smoke cover from space observation. Now we revised our model to be able to apply in all weather conditions. What opportunities for training and professional development has the project provided?This project has provided extension training programs for county agencies and wildfire response professionals for wildfire response, we also provided internshipsand postdoc research opportunities for young scientists to train the cutting edge observation technologies for wildfire damage assessment. How have the results been disseminated to communities of interest?Our results have been disseminated to communities via multiple out-reach activities. For example, the Great Plains Fire Summit was held in Canyon TX in 2024 summer, we had more than 250 participants attended including landowners, prescribed burn associations, volunteer fire departments, state and federal agencies, universities, and non-profit organizations. Other major activities include: •March 6, 2025: Houston Livestock Show and Rodeo, 190 participants, "Determining Damages from Wildfires." •March 15, 2025: Upper llanos Prescribed Bur Association, 40 participants, "Assessing Wildfire Damage". •April 1, 2025: Texas Master Naturalists, 120 participants, "Understanding Fire Effects." •April 4, 2025:Prescribed Burn Board, Texas Department of Agriculture, 25 participants, "Documenting Wildfire Damages". •April 8, 2025: Reagan County Rangeland Day, 20 participants,"Strategically Rebuilding Following Wildfire". •April 8, 2025: Upton County Brush and Weed Program, 5 participants,"Understanding Wildfire Response". •April 9, 2025: Scurry County Agricultural Program, 40 participants,"Managing Post-Fire Rangeland". •Wildfire Preparedness Meeting, February 13, Canadian, TX •Hemphill County Beef Conference April 29-30, Canadian, TX •December 18: North Region Ag Conference (online and in-person to 16 counties), 341 participants •January 21: Fire and Rangeland Management Symposium, Pampa, TX What do you plan to do during the next reporting period to accomplish the goals?We plan to collect more input from local stakeholders for forage recovery information after the wildfire; we also need more time to test our platform; and Panhandle region is experiencing extendeddrought impacts and we plan to take more time to monitor the impact on the wildfire recovery of forage biomass.

Impacts
What was accomplished under these goals? We have developed the remote sensing and AI based rapid assessment model for wildfire damage of agriculture infrastructure, and have identified building damage location and severityover Panhandle region. We have also developed time-series based forage lossand recovery maps over Panhandle wildfire region. We have conducted a series of outreach activities to seek input from key stakeholders for decision support tool development.

Publications