Use geospatial analysis and machine learning along with human-centered-design to create an automated remote sensing tool for early detection of invasive tree pests.

In order to be considered for participation, please fill out this form:



Trees provide many important benefits to the residents of LA County. In addition to beautifying our communities, they provide shade and cooling, support biodiversity, help manage stormwater, reduce air pollution, and improve mental health. Unfortunately, trees in the County face multiple threats. In addition to the ongoing threats of drought stress and heat stress, trees in the County also face the threat of invasive pests which have the potential to kill millions of trees in Southern California—of particular concern are the invasive shot hole borer (ISHB) and the golden spotted oak borer (GSOB). On May 18, 2021, the LA County Board of Supervisors adopted a motion, authored by Supervisors Kuehl and Solis, titled “Implementing an Early Detection Rapid Response Plan to Invasive Pests.” The motion directed the Chief Sustainability Office (CSO) to work with relevant County departments to develop a plan for early detection and rapid response (EDRR) to these invasive pests. One part of this plan is to pilot a remote sensing solution for early detection of invasive beetles.

The Opportunity:

County staff are racing against the clock to locate and control new infestations before they spread to surrounding areas. Today, the County relies on physical inspection, including surveying and trapping, to identify infestations of invasive pests. This boots-on-the-ground process is time-consuming, labor-intensive, and expensive, making it unrealistic for limited staff to manually survey every tree in the County. The County needs a way to frequently and comprehensively identify areas of potential new infestations Countywide so limited resources can be deployed to conduct physical inspections at priority locations. An automated remote sensing program using publicly available satellite data would provide an important monitoring tool to meet this need and help the County protect its vital tree resources.

Why Participate:

This challenge gives participants the ability to consider the relationship between designing a targeted application and developing the data models utilized by that application.

Through this project, participants will explore building data models around a specific data challenge for the identification of wooded areas with potential pest infestations. To successfully complete this challenge, teams must consider: What are we predicting and why? What is the end use for the data models we are we training towards specifically?

Through research and conversations with stakeholders, teams go through a process of value discovery to identify applications that would be viable within the context of the stakeholder’s needs. This process of refining the technical goal must guide how teams utilize the data and identify relevant models.

Based on the identified end goal, participants may choose to utilize a computational, machine learning workflow, or a remote sensing spatial workflow to fulfill the data goals of this project. Workshops and available mentors will guide participants through possible workflows, although a combination of spatial and computational skills will be necessary to complete the final challenge.

This isn’t simply a data challenge. The goal of this program is to not only enable participants to learn data skills relevant to this use case, but to also give them the tools for R&D of product development with data.


February 22nd: Applications Open

March 8th: Info Session

March 16th: Applications Close

March 18-20th: Design and Development Workshop

Friday Evening: Stakeholder Presentation

Friday Evening: Teambuilding Activities

Saturday Morning: Design Workshop

Saturday Afternoon: Computational Analysis Workflow

Saturday Afternoon: Remote Sensing Spatial Analysis Workflow

Saturday Evening: Work Sessions

Sunday Morning: Work Sessions

Sunday Afternoon: Teams present their Design Breakdowns and projected Data Workflows to stakeholders for feedback

April 21st: Demo Day



User interface for multiple jurisdictions

  • The data workflow and outputs for this challenge should take into consideration the way that the information will be implemented. If the prospective analysis is successful, the automated remote sensing process can be expanded to be used Countywide.
  • Take into consideration the time cycles that new data becomes available, as well as the frequency of on-the-ground monitoring in order to design a challenge-appropriate feedback system. In anticipation of a successful prospective analysis, design a user interface (e.g., monitoring dashboard) that can alert the County of new areas of potential infestation and notify the County of the jurisdiction of the potential infestation. The interface should include a way for the County to share information with affected jurisdictions in a user-friendly fashion (e.g., to identify the relevant jurisdiction and provide a push email or text message to the relevant contacts).


Retrospective analysis

  • Starting with imagery closest to the date of infestation, work backwards in time to determine when the infestation first becomes detectable in the satellite imagery. Consider that your findings may or may not differ between ISHB infestations and GSOB infestations. Once the early detection window has been identified, train and validate a ML methodology or create a spatial analysis workflow to prioritize emerging infestation sites.

Prospective analysis – Santa Monica Mountains Pilot

  • Create a process to automate the early detection of potential pest infestations using newly collected Landsat data. Apply your process to each newly acquired Landsat image, using the Santa Monica Mountains National Recreation Area as the pilot study boundary. Identify potential areas of new infestations within the boundary area for the County to ground truth with physical inspections. If your methodology and time allow, also provide potential areas of new infestation Countywide.

Proactive response

  • Today, the County’s response to invasive pests is reactive. To mount a proactive response to invasive pests, the County will need a better understanding of some of the habits and impacts of these pests, especially ISHB. Incorporate data gathering on the impacts of ISHB into your automated remote sensing program. Potential data points of interest include infested tree data such as tree species, tree size, tree canopy density, and tree health; infestation physical distribution data such as geography and ecology; infestation temporal distribution data such as meteorology and seasonality; and response effectiveness information such as the effect of infested tree removal on the spread of pests.

Hackathon Sponsors


$15,000 in prizes

1st place

• $10,000 USD
• Featured on the AI LA Blog
• Social network amplification from our partners
• Office Hours with Starburst Aerospace
• 4 hours of free corporate services with Wilson Sonsini ($4000 value)

2nd place

• $2,500 USD
• Featured on the AI LA Blog
• Social network amplification from our partners
• Office Hours with Starburst Aerospace
• 2 hours of free corporate services with Wilson Sonsini ($2000 value)

3rd place

• $2,500 USD
• Featured on the AI LA Blog
• Social network amplification from our partners
• Office Hours with Starburst Aerospace
• 2 hours of free corporate services with Wilson Sonsini ($2000 value)

Devpost Achievements

Submitting to this hackathon could earn you:


Rebecca Ferdman

Rebecca Ferdman
LA County Chief Sustainability Office

David Whelan

David Whelan

David Herman

David Herman

Judging Criteria

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