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Evaluating and monitoring tree populations
Tree inventory
A tree inventory is an essential tool if you manage urban tree populations on a tree by tree basis. Programs that manage street trees and trees under utility lines are the most common users of inventories. Inventories are also used for park and campus sites.
The data record for each tree typically includes information about tree characteristics, maintenance history, and management needs. The data that is maintained for each inventoried tree will depend on the tree program's needs, who will be collecting the data, and the role that the inventory plays in the tree management program. Typical inventory information is summarized in the table below.
| Data category | Example data fields | Notes |
| Tree site information | - address/location/coordinates |
Data are important for anticipating potential tree/infrastructure conflicts and maintenance needs. Data can be collected by trained community volunteers or may be assessed/extracted from GIS layers if coordinates are known. Typically needs to be updated only when surrounding hardscape infrastructure is modified. |
| Basic tree descriptive data | - species, |
Simplest inventories may be limited to data in this category. Size data is often recorded in broad size classes (e.g., 15-30 ft) and may be collected by trained community volunteers. Condition and size class data should be updated every few years. |
| Tree management data | - past maintenance activities |
Data on tree management is critical if the inventory is integrated with work planning. Data should be collected by trained tree care professionals, typically staff or contractors. Should be updated as work is performed or on a regular schedule if no work is scheduled. |
| Time data | - date added to inventory |
Time variables show whether information is current. Fields can also show the most recent maintenance. In systems coupled wih work scheduling and reporting, the complete listing of work records by date is normally stored in a one or more separate linked databases. |
Trained volunteers, staff members, or contractors can collect initial inventory data. Once the initial inventory is developed, it needs to be updated as changes occur. Updated data can be collected when trees are inspected or maintained.
The inventory should be maintained in a computer database that allows for easy access to the information. You can use general-purpose database management or GIS software to manage a tree inventory database. Dedicated software for tree inventory management is also available from a variety of sources. Such programs typically provide templates for entering tree data. In addition, they provide various ways to produce reports by querying, summarizing, and cross-tabulating tree data. The USDA Forest Service maintains a list of free and commercial tree inventory software.
Sample survey
Some situations call for general information about a large number of trees rather than tree-by-tree management information. In these situations, conducting a complete inventory may be unnecessary as well as expensive and time-consuming. Instead, you can collect data on an appropriate sample of the tree population. If the sampling is done correctly, data from the sample will provide a reliable estimate for the overall tree population. The term "sample survey" is used to describe this method of data collection..
Sample surveys are typically used to describe large stands of trees that are not intensively managed, such as open space trees. A sample survey can also be used to collect data on urban tree populations that are not included in an inventory. Such information may be useful for estimating tree-related benefits or assessing particular needs. A sample survey can also provide infomation that may be useful for designing an appropriate tree inventory database.
Proper sampling is the key to a successful and reliable sample survey. The samples should be random, independent, and unbiased. This means that all members of the population should have an equal chance of being sampled and the selection of one sample should not affect the selection of other samples. The same sampling considerations apply to both ground based samples and sampling done in aerial image analysis described below. Also, urban tree populations can vary widely between different areas. You may need to break the sample area up into more uniform subunits (strata) and distribute samples across these different strata to avoid bias. This is known as stratified sampling.
Up to a point, the reliability of the population estimate will improve as the number of trees (or other sampled units) increases. However, the gain in reliability does not increase in a linear fashion as the sample size increases (see this link). You will typically need to sample at least 300 to 500 trees to obtain reasonably reliable estimates for the overall tree populaiton. Larger sample sizes are needed to get reliable estimates for uncommon features of the population, such as uncommon tree species.
The ISA Tree Ordinance website's pages on Sampling and Ground Survey provide detailed information about conducting sample surveys. The i-Tree Eco application provides protocols that can be used to conduct a sample survey of a tree population. The Streets application of i-Tree also includes the option of using sample survey data. The program can generate a random sample of street segments if appropriate GIS data is supplied.
You can also select random sample points within a sampling area using a map and random number generator. Coordinates within the sampled area can be defined by existing map-based coordinates such as UTM or State Plane grids. You can also establish an arbitrary grid based on units measured on a map or aerial image (e.g., distances in cm or pixels from the bottom and left edge of the map or image). Determine the range of X and Y coordinates that occur within the area to be sampled. A random number generator (e.g., from a spreadheet program) can be used to generate random X and Y coordinates that fall within these ranges. Each random coordinate pair you generate can designate the location of a random sample point, which can be located using a map or GPS receiver. For sampling individual trees, you can select the closest tree to a random point if it does not fall directly on a tree.
Tree canopy cover assessment
Tree inventories generally do not provide enough information to provide estimates of total canopy cover. Many inventories (e.g., for street trees) do not include all trees in the urban forest. If a complete inventory of all trees is available and tree canopy spread information is included, it may be possible to estimate total tree canopy. However, canopy cover estimates calculated from canopy spread data may not be accurate if:
-
many tree canopies overlap
- tree canopies are
very irregular in shape
- canopy spread is recorded in wide categories (e.g., 15-30 ft).
Ground survey methods are available that can provide accurate estimates of canopy cover, especially over relatively small areas. However, with the wide availability of high resolution aerial imagery available from online sources, aerial image analysis generally provides a simpler, cheaper, and more efficient means for measuring canopy cover.
The ISA Tree Ordinance website page on Photogrammetry and remote sensing techniques discusses methods that can be used to assess tree canopy cover from both digital images and hard copy photos. Much recent and some older aerial imagery is available in digital formats. However, older aerial photo images that may be useful for showing trends over time may only be available as paper copies. Although such images can be digitized, it may be easier to measure canopy cover directly from printed images.
Tree risk assessment
A risk of damage or harm exists when a tree or a large part from it can fail and land on a valuable target. Compared with most natural forests, urban forests have a much higher density of people, structures, vehicles, and other items that may be considered valuable targets. As a result, most urban forest programs need to include provisions for assessing risks related to tree failure. A tree risk management program uses a systematic approach to identify tree-related risks and appropriate ways to minimize or eliminate high-risk situations. The National Park Service Hazard Tree Guidelines page provides a concise summary of the legal reasons for developing a hazard tree program and its basic components.
All trees have the potential to fail, and given enough time, any given tree will eventually fail. Of course, the same can be said of most human-made structures. Experience shows that trees, structures, and people can all coexist within cities. To minimize risks associated with failures of trees, buildings, utility poles, bridges, or other urban infrastructure, an appropriate level of inspection is needed to identify obvious hazards and take corrective action before damaging failures occur. However, even with appropriate inspections and corrective actions, risks cannot be completely eliminated. The goal of any risk management program is to reduce risk to tolerable levels by taking reasonable and prudent measures.
Periodic tree inspections are a key component of a tree risk assessment and hazard management program. As noted above, a tree inventory provides an efficient way to manage data related to tree failure risk. Tree risk ratings and other information about potentially hazardous trees can be stored in an inventory. This information can be used to schedule corrective actions or appropriate reinspection intervals for each tree
A number of systems have been developed and used to rate tree failure potential and risk. Most systems assess the following factors:
- Likelihood of failure of the tree (or a part of it). This is the most important factor but is essentially unpredictable in a quantitative way. Ratings generally rank trees (or branches) as being more likely to fail if they have various detectable defects. However, except in extreme cases (e.g., a cracked dead branch hanging by a small bit of wood), it is not technically possible to predict when a failure will occur.
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Damage-causing potential. In most systems, the size (and weight) of the part that is most likely to fail is used to predict the potential to cause damage. A large branch that fails will typically exert more destructive force on a target than will a small branch. However, other factors unrelated to size can affect the amount of force that a failure exerts. The speed of the failure, whether the break is complete or hinged, whether the failed part is slowed by other branches, etc., can also affect how much damage may be caused. These factors may be difficult or impossible to predict.
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Presence and type of target in the area that will be impacted by the failure. The first consideration is whether a target is present in the likely impact zone. If the target area is not occupied full time, this factor needs to consider the likelihood that the target area would be occupied when the failure occurs. The second consideration is the relative value of the target. People are the highest value targets, but other targets (e.g., electrical equipment that might start a fire if impacted) also have the potential to affect human safety and would have a high value.
Many of the tree failure riIsk rating scales in use begin by assessing these factors, usually on a relative scale (low to high). Numerical values are associated with these ratings (typically 1 to 3 or 4). The numbers are either added or multiplied to produce a summary rating. The summary rating can be useful to help identify trees that have the highest need for corrective action to abate potential hazards. However, tree risk ratings do not indicate whether a tree is actually likely to fail in a given time interval. At best, most risk rating systems can identify trees that, on average, are more likely to fail than other trees or will tend to cause more damage if they fail.
The USFS has produced a publication that covers many aspects of creating a hazard reduction program in detail:
Urban Tree Risk Management: A Community Guide to Program Design and Implementation
A
companion software product is also available:
Electronic Tree Risk Assessment Calculator (E-TRAC) software
An ANSI standard for Tree Risk Assessment and corresponding BMPs are currently under development.