Standardization of Street Sampling Units to Improve Street Tree Population Estimates Derived by i-Tree Streets Inventory Software

Street trees are a subpopulation of the urban forest resource and exist in the rights-of-way adjacent to public roads in a municipality. Benefit-cost analyses have shown that the annual benefits provided by the average street tree far outweigh the costs of planting and maintenance. City and municipal foresters spend a majority of their time and resources managing street tree populations. Sample street tree inventories are a common method of estimating municipal street tree populations for the purposes of making urban forest policy, planning, and management decisions.

i-Tree Streets is a suite of software tools capable of producing estimates of street tree abundance and value from a sample of street trees taken along randomly selected sections (segments) of public streets. During sample street tree inventories conducted by Virginia Tech Urban Forestry, it was observed that the lengths of the sample streets recommended by i-Tree varied greatly within most municipalities leading to concern about the impact of street length variation on sampling precision.

This project was conducted to improve i-Tree Streets by changing the recommended sampling protocol without altering the software. Complete street tree censuses were obtained from 7 localities and standardized using GIS. The effects of standardizing street segments to 3 different lengths prior to sampling on the accuracy and precision of i-Tree Streets estimates were investigated though computer simulations and analysis of changes in variation in number of trees per street segment as a basis for recommending procedural changes.

It was found that standardizing street segments significantly improved the precision of i-Tree Streets estimates. Based on the results of this investigation, it is generally recommended that street segments be standardized to 91m (300 ft) prior to conducting a sample inventory. Standardizing to 91m will significantly reduce the number of trees, the number of street segments, and the percentage of total street segments that must be sampled to achieve an estimate with a 10% relative standard error.

The effectiveness of standardization and the associated processing time can be computed from municipal attributes before standardization so practitioners can gauge the marginal gains in field time versus costs in processing time. Automating standardization procedures or conducting an optimization study of segment length would continue to increase the efficiency and marginal gains associated with street segment standardization.