Attachment 1 - Statement of Work.pdf

US Department of Agriculture (USDA)

Statement of Work

Contents Project General Information

1.0 Background

2.0 Goals

3.0 Scope of Work (Objectives)

Contractor Requirements

3.0 Technical Requirements / Tasks

4.0 Government Furnished

5.0 Deliverables / Schedule

6.0 Travel

7.0 Contractor’s Key Personnel

8.0 Security Requirements

9.0 Data Rights

10.0 Section 508 – Electronic and Information Technology Standards Attachment

Project Examining and Enhancing the Factors Supporting Current Wildland-Urban Interface (WUI) Risk Approaches.

General Information

1.0 Background

There is a significant need for an improved wildland-urban interface (WUI) database that supports the evaluation and enhancement of WUI risk assessment methods. Primarily, characterizing WUI risk relies on information from retrospective correlation studies, minimal model evaluations, and limited assessment of WUI definitions. Also, no wildfire-affected building footprint database portraying the building type (e.g., home versus shed), damage status, and other information covering significant spatiotemporal extents exists, resulting in limited information to characterize WUI risk. Furthermore, correlation studies do not typically examine defensive actions, the relationship between defensive actions and property treatments, or segment the destroyed and not destroyed buildings based on exposure conditions (e.g., proximity to burned features). These studies utilize coarse-resolution vegetation and topography data (e.g., 30 meters) and information from post-fire assessments where fire has altered pre-fire conditions, resulting in identification difficulties of consumed materials. Finally, limited studies assess the response of vegetation within the home ignition zone and further afield.

2.0 Goals

This project aims to develop and deliver a database of wildfire-affected building footprints, classified by building type, attributed with structure separation distance (SSD), construction materials, and uncertainty categorized for this data. The database will cover significant spatiotemporal extents (e.g., 2010 to 2022 in the U.S.) and include unique information from the National Fire Incident Reporting Systems and other databases. High-resolution (e.g., 1 meter) pre-fire and post-fire-affected vegetation datasets will be derived at select fires. We will use this data to assess the uncertainty in correlation studies. We will focus on examining relationships between pre-fire and fire-affected vegetation, relationships between defensive actions and property treatments (e.g., defensible space), and how conclusions of correlation studies change when using new data derived through this project. Project data will support examining current WUI definitions when considering SSD and fine-scale vegetation. Additionally, we will evaluate WUI fire behavior models.

These efforts will facilitate examining and enhancing current parcel and building-scale risk assessment approaches.

3.0 Scope of Work (Objectives)

The above goals will be achieved by completing the following objectives or project tasks.

1. Acquire Pre-Fire and Post-Fire Aerial Imagery: The contractor will utilize provided funds and public sources to acquire pre-fire and post-fire aerial imagery of select WUI fire locations from appropriate vendors. This imagery and other satellite and aerial imagery and pre-fire light detection and ranging (LiDAR) data will be used to extract pre-fire vegetation and building footprints as described below.

2. Creating a Database and Assessing Uncertainty: The contractor will integrate a unique combination of data on wildfire-affected buildings to create a database to assess uncertainty in the location and type (e.g., primary versus secondary) of wildfire-affected building footprints, creating an extensive database covering the U.S. between 2010 and 2022. When possible, the contractor will attribute the buildings with SSD, information on defended buildings, and pre-fire building conditions with uncertainty. We will also utilize pre-fire and postfire remote sensing data to create and use existing high-resolution and coarse-resolution maps of vegetation and topography, creating a database to support the assessments below. This task will focus on answering the following question: Q1. What are the accuracies associated with various methods (e.g., remote sensing and ground-based) of identifying damaged and destroyed buildings, building conditions, and primary (e.g., home) and secondary (e.g., shed) building types?

3. Assessing Uncertainty in Correlation Studies: Assessing uncertainty in correlation studies will occur at select fires. We will utilize the databases derived above and the existing databases listed in Table 1 to address the following questions. Q2. What is the relationship between pre-fire vegetation conditions and wildfire-affected vegetation within the HIZ and further afield? Q3. Are defensive actions on parcels and buildings correlated with property treatments (e.g., defensible space) present in risk assessment approaches?

Q4. How do conclusions change in correlation studies between pre-fire conditions and building response to fire when using new information on defensive actions, wildfire-affected vegetation, building material, and fine-scale vegetation and topography? Q5. How can the Bradford Hill Criteria [1] for causation be modified to present a framework for determining the causation of building destruction at wildfires?

4. Examining WUI Definitions: We will examine the components of WUI definitions using the datasets and information produced in the above tasks. This examination will incorporate unique approaches to answer the following questions. Q6. How does examining SSD across representative WUI fires over the twelve-year period change our understanding of definitions of the WUI? Q7. How do coarse-scale measures of topography and vegetation compare to fine-scale measures of topography and vegetation when examining core components of current WUI definitions (e.g., distance to wildland vegetation)? Q8. How do answers to questions six and seven change current WUI definitions?

5. Evaluating and Refining Existing Risk Frameworks: Finally, based on the integrated efforts above, and in close conjunction with the USFS technical representative, the contractor will examine existing WUI parcel and building scale risk approaches, focusing on components to enhance through the insights and data developed in the above efforts. We will address question ten below in this final aspect of the project. Q10.

What methods can enhance parcel and building scale WUI risk approaches?

Contractor Requirements

3.0 Technical Requirements

Below are the technical requirements for the tasks above.

• Consultation services provided through the tasks above will have the following technical requirements for the Geospatial Data Scientist.

o The ability to organize and participate in virtual meetings and phone calls with USFS and other government staff.

o The ability to create presentations in appropriate media to enhance consultation services and present research findings to diverse audiences.

o The ability to use advanced remote sensing techniques to extract information from the built and natural environments regarding vegetation and human-made features.

o Expert knowledge regarding building and maintaining geospatial databases of the built and natural environments.

o Expert knowledge of fire behavior in the WUI.

o Expert knowledge of machine learning techniques such as deep learning for the classification of remotely sensed data.

o Demonstrated ability to extract building footprints from light detection and ranging (LIDAR) data.

o Demonstrated ability to recreate timelines of WUI fires from diverse data sources.

o Demonstrated ability to publish databases resulting from post-fire assessments of WUI environments.

o Expert knowledge of spatiotemporal data integration.

o Demonstrated ability to identify and extract indicators of defensive actions from overhead imagery.

o Demonstrated ability of assessing the affects of defensive actions on structure survival in the WUI.

o The ability to publish geospatial datasets to the ESRI ArcGIS Online platform.

o Demonstrated ability to creating interactive websites detailing the results of post-fire assessments.

o Demonstrated ability to publish geospatial datasets to the USDA Forest Service Research Data Archive.

o The ability to write clearly and concisely regarding the integration of data in a WUI environment.

o Demonstrated ability to extract exposure fires from the National Fire Incident Reporting System (NFIRS) and analyze structure separation distance and defensive action information using this data.

o Demonstrated ability to integrate geospatial data for inputs to the next generation of fire and smoke models, with a focus on the Fire Dynamics Simulator.

o Demonstrated ability to integrate diverse datasets from large outdoor fires, particularly for evaluating fire models like the Fire Dynamics Simulator.

o Demonstrated ability to publish datasets from large outdoor fires, particularly those supporting fire model evaluation.

o Demonstrated ability to create interactive websites portraying data collected from large outdoor fires.

o The ability to program in modern computer languages to create tools for integrating 3D, time-dependent fire models.

o Ability to conduct either a virtual workshop.

o Ability to train a diverse audience in industry standard techniques for managing and integrating data collected for the evaluation of 3D, time-dependent fire behavior models.

4.0 Government Furnished

The government will provide the contractor with an ArcGIS Online account and approve access of the contractor to the MAXAR Global Enhanced GEOINT Delivery website (https://evwhs.digitalglobe.com/myDigitalGlobe/login)

5.0 Deliverables / Schedule

The table below describes the project deliverables and schedule.

Key Deliverables

Item No. Deliverable Objective Due 1 Pre-Fire Remote

Sensing Data Obtain pre-fire remote sensing data from public and private sources.

Three to six months after project initiation.

2 Database of wildfire-affected footprints between 2010 and 2022.

Integrate datasets to develop a database of wildfire-affected buildings and NFIRS exposure fires.

One year after project initiation.

3 Attribute fires with building type, pre-fire conditions, and defensive action status.

Utilize ground and aerial remote sensing and other sources of Information to attribute select fires with information on building type, pre-fire conditions, and defensive actions.

One year after project initiation.

4 Database of pre-fire vegetation and topography and wildfire-affected vegetation.

Integrate existing datasets and develop new datasets portraying topography and pre-fire and wildfire-affected vegetation at select WUI fires.

One and one-quarter years after project initiation.

5 Published Database of High- Resolution and Coarse-Resolution Vegetation and Topography.

Publish database of pre-fire and post-fire vegetation and topography at multiple resolutions to the USDA Forest Service Research Data Archive.

One and one-half years after project initiation.

6 Conduct accuracy assessments.

Conduct accuracy assessments of building footprints, construction materials, and building types.

One and one-half years after project initiation.

7 Publish Database of U.S. Wildfire- Affected Footprints.

Publish database of U.S. Wildfire-affected footprints (2010 to 2022) classified by type, attributed with pre-fire conditions,SSD, defensive action status, with associated uncertainties to USDA Forest Service Research Data Archive.

One and three-quarters years after project initiation.

8 Published Paper on Uncertainties Associated with Mapping Wildfire-Affected Footprints

A journal article or GTR detailing the methods employed to create the building databases, statistics on SSD, and other results of uncertainty assessments.

One and three-quarters years after project initiation.

9 Assess uncertainty in correlation studies and develop criteria for determining building damage causation.

Examine the relationships between pre-fire versus post-fire vegetation, defensive actions and property treatments, and pre-fire conditions and building response. Enhance Bradford Hill Criteria [82] for building response causation determination.

Two years after project initiation.

10 Published WUI Correlation Paper

At least one journal article or general technical report (GTR) detailing the results of the correlation studies.

Two years after project initiation.

11 Evaluate and enhance WUI risk approaches.

Building from the efforts above, evaluate and identify enhancements to existing parcel and

Two years after project initiation.

building scale WUI risk approaches. This effort will involve close collaboration with Dr.

William Mell, who will contribute significantly to the effort.

12 Interactive Web Site and WUI Stakeholder Workshop.

An interactive website detailing project results and data. A workshop for WUI stakeholders detailing project results.

Two years after project initiation.

13 Final Project Report In conjunction with the USFS Technical Representative, deliver final project report

Two years after project initiation.

14 Project Presentations or Conference Attendance

Attend and present at one conference during the second year.

Once during the second year of the project.

6.0 Travel

The contract will attend one conference during the second year and develop project presentations as appropriate.

7.0 Contractor’s Key Personnel

The key personnel for this project would consist of a senior level geospatial data scientist and a geographic information system/programmer technician.

8.0 Security Requirements

There are no security requirements for this contract.

9.0 Data Rights

All data produced and provided to the contractor will be consider within the public domain.

10.0 Section 508 – Electronic and Information Technology Standards Any software or websites produced for this project will be compliant with section 508.

Attachment Not Required.