i-Tree Pest Detection (IPED)


Urban areas are frequently the first site of introduction for exotic pests, where they remain undetected until populations are well established and have had harmful impacts on the health of host trees. Many communities routinely complete and update tree inventories, but often overlook pest invasions because pest detection tools are not part of the inventory process. There are also no processes in place for aggregating pest inventory data into a standardized form, which would allow communities to analyze pest trends that are otherwise difficult to detect across geographic or political boundaries.

Project Goal

The goal of the i-Tree Pest Detection Development Team is to develop, disseminate, implement, and establish an accepted, modern protocol for long-term national urban pest detection and monitoring

Benefits of Pest Detection

  • Increase and broaden efforts to detect exotic pests.
  • Increase awareness of the need for routine tree health assessments.
  • Provide a standardized method for integrating pest detection with urban forest management.
  • Improve opportunities to control pests while invasions are still manageable.
  • Reduce unchecked movement of pests across geographic and political boundaries.
  • Reduce costs for long-term tree management, removal, and replacement.
  • Provide a tool for integrating pest detection with more innovative, technologically advanced tree inventory and assessment tools.

Pest Detection Integration in i-Tree

i-Tree was created to develop, disseminate, support and refine urban forest analysis tools and will be utilized as a platform for Pest Detection delivery. The release of i-Tree v5.0 includes the pest detection protocol as an optional module within the i-Tree Streets and Eco applications. See Vendor section below for information for Pest Detection external integration.

The Pest Detection module in i-Tree Streets and Eco provides:

  • A portable, accessible and standardized method of observing a tree for possible insect or disease problems.

i-Tree Streets and Eco integrated field data collection and desktop reporting:

Pest Detection Resources:

Pest Detection Training

Four archived 60-minute online sessions offered by the Urban Natural Resources Institute (UNRI) focusing on the Pest Detection module.

Pest Detection Future Developments

  • A national database repository that will enable pest specialists to access regional pest data to query for pest detection anomalies and trends at multiple scales.


One goal is to make the Pest Detection Protocol accessible to vendors and other interested parties. XML is employed to accomplish this. Extensible Markup Language is similar to the language of the web, HTML (HyperText Markup Language). However, XML is designed to carry data and it is recommended by the World Wide Web Consortium. XML structures, stores, and transmits data. Refer to: w3schools.com website for more background on XML.

The Pest Detection (and i-Tree Streets) XML schema definitions provided on the Resources - Archives page are geared towards software developers. They can use the XML schema to integrate Pest Detection data collection fields into their applications. Also, developers may wish to engineer their applications to output their related Pest and/or i-Tree Streets data in a format that adheres to the XML schemas specified here. This will provide straightforward compatibility between their application and i-Tree.

Development Team

A project planning and development team is working to move this effort forward. Team subgroups are focusing on pest signs and symptoms, i-Tree integration and programming, pilot community involvement, research database development, and online resources. The team includes employees of several U.S. Department of Agriculture agencies, including the Animal and Plant Health Inspection Service, and the Forest Service Northern Research Station and the Northeastern Area State and Private Forestry's Urban and Community Forestry and Forest Health Protection Programs. Other team members represent the Society of Municipal Arborists, The Davey Institute, the University of Georgia Bugwood Network, Cornell University, National Plant Diagnostic Network, Purdue University, University of California, Davis, University of Florida, University of Maryland, University of Vermont and the Vermont Department of Forests, Parks, and Recreation. The USDA Forest Service manages the project planning team.