Open Innovation Challenge Spring 2022

Feb 22, 2022

We are excited to announce a new type of 'hackathon' we call an 'Open Innovation Challenge,' where teams will compete to find the most efficient solution using satellite imagery to detect invasive pests in LA County's tree canopy.

Individuals and unfunded teams can apply -- we are looking for cross-disciplinary teams: computer scientists, data scientists, geospatial scientists, entrepreneurs, designers, MLops, et al.

Teams will be provided pre-processed Landsat 8 data, GPU compute, and mentors to help them design and develop a proof of concept GeoAI-enabled pest infestation alert system in 4 weeks.

Important Dates
Info Session: March 8th at 5 pm PST Virtual
Kick-Off: March 18-20th in Los Angeles
Demo Day: April 21st in Los Angeles

Important Details
It's mandatory that at least 1 team member participate in the in-person kick-off and demo day.
Individuals and unfunded teams can apply (ideally 3-5).
We are looking for cross-disciplinary teams: computer scientists, data scientists, geospatial scientists, entrepreneurs, designers, MLops, et al.
Teams will present on stage at AI LA's Earth Summit on April 21st at the BioscienceLA Collaboration Hub in Culver City.

Register here.

First: $10,000
Second: $2,500
Third: $2,500

The 3 winning teams will also receive office hours from Starburst Aerospace Accelerator and free corporate legal services from Wilson Sonsini, and other perks from our partners.

The judging criteria for this project reflect the need for hybrid design and data skills:

  • Data Workflow (10%)
  • Model Accuracy (30%)
  • Functionality (20%)
  • UX Design (20%)
  • Alignment with Challenge (10%)
  • Presentation (10%)

Please fill out this form to be considered as a participant in this challenge.


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 trees 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 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.

Key Dates:

February 22nd: Applications Open
March 11th: 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 (optional)

  • 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.


  • What pre-processing will already be completed on the data?

The lat/long and time stamps of the ISHB and GSOB infestations are available as pre-processed chips, with the data mapping to the Landsat time-series data.

  • Where will all of the pre-processed data be stored and how will it be regularly accessed by the teams?

During the March 18-20th workshop, we have a powerful data science workstation that can be on-prem during the kick off weekend.

Workstation Specs: Dual Socket Xeon GOLD 8 Core, 196gb DDR4 Ram, 1TB NVME SSD and Dual Nvidia Quadro RTX 8000

In the 4 weeks leading up to demo day, the data will have to be accessed remotely.

  • What will project teams complete during the workshop weekend?

During the workshop weekend, participants will be offered a deeper dive into challenge considerations, as well as potential project workflows. Teams will use this information to present their proposed workflow and breakdown of design requirements to stakeholders at the end of the weekend for feedback.

  • What are recommended competencies for project teams?


  • Image processing/feature extraction
  • Machine learning
  • Geospatial tools and methods
  • Statistical methods and analysis


  • Knowledge of ecosystem analysis and forests
  • Understanding of local government needs and processes
  • Systems and user experience design
  • How will final projects be judged?

The judging criteria for this project reflect the need for hybrid design and data skills. Judging criteria are: Data Workflow, Model Accuracy, Technical Implementation, UX Design, Alignment with Challenge, and Presentation.

  • How can we get additional questions about the challenge answered?

For more information about this challenge, or if you have questions, please email with the subject line, “OIC Question.” We will also be holding an information session with more information on March 8th.

Rachel Joy Victor
Head of Design, Open Innovation Studio

Rachel Joy Victor is a strategist and designer working with emerging technologies. Her strategy work aligns brand, product, and content strategy, centering user engagement and experience throughout. She designs systems architectures and user experiences--from tools and platforms to spaces and cities to narratives and immersive content. Rachel draws from degrees in computational neuroscience and spatial economics and data analysis to align emergent systems and human behavior in her work.