Tree Assessment (Condition/Health) utilizing Drone Technology, Computer Visioning and Predictive Analytics

Government:

City of San Diego

Category:

Data Analytics, Data Collection, Geo Services, Intrastructure Assessment, IoT, Resident Engagment

Budget:

Budget Not Determined Yet

Procurement Method:

Other
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Application Period:

October 16, 2019 - November 20, 2019

Q&A Period:

October 16, 2019 - November 5, 2019

Challenge

The Transportation & Storm Water (Urban Forestry) is seeking a comprehensive and robust solution to simplify the collection and assessment of tree condition/health for our communities.

Background

The City of San Diego is the eighth-largest city in the United States and the second largest in California, with a population of 1.3 million. The City’s aggregate tree canopy provides significant contributions to the quality of life for residents and visitors, primarily because trees make a vital and affordable contribution to the sense of community, and create pedestrian-friendly neighborhoods. San Diego is committed to increasing the amount of trees in the City's urban forest to help the City meet the goals defined by the City San Diego Climate Action Plan by continuing to expand the City's tree canopy. A healthy forest is essential to increasing tree canopy cover, and technology can bridge the gap between what an expert arborist can observe and record in the field and what an arborist cannot observe in our tree’s canopy. 

Requirements & Outcome

Transportation and Storm Water Department seeks a solution that would incorporate the following outcomes: 
 
  • Develop a tree health assessment tool and data gathering system using drone technology, computer visioning and predictive analytics. 
  • Ability to develop a predictive model to assess and prioritize tree conditions and identify potential ‘hot spots’ caused by known disease(s) and/or other form(s) of deterioration.   
  • Design and develop a data gathering tool that effectively captures tree height, crown measurement and species identification using drone technology and computer visioning.