Diane

Visit our training calendar for upcoming QTRA training dates and prices

QTRA and Visual Tree Assessment – Estimating Probability of Failure training has been scheduled for the United Kingdom. For dates and costs, follow this link our training calendar.

QTRA and Visual Tree Assessment – Estimating Probability of Failure training has been scheduled for the United Kingdom. Follow this link to read the latest QTRA Newsletter Quantified Tree Risk Assessment

Quantified Tree Risk Assessment (QTRA) training

07 July - Guildford

14 July - Cambridge

07 Oct - Liverpool

13 Oct - Monmouth

21 Oct - Exeter

28 Oct - Glasgow

03 Nov - Warwick

Visual Tree Assessment – Estimating Probability of Failure Training

08 July - Guildford

15 July - Cambridge

08 Oct - Liverpool

14 Oct - Monmouth

22 Oct - Exeter

29 Oct - Glasgow

04 Nov - Warwick

For further information visit Quantified Tree Risk Assessment and if you have any questions email Quantified Tree Risk Assessment

Tree safety management is a matter of limiting the risk of harm from tree failure while maintaining the benefits conferred by trees.

The Quantified Tree Risk Assessment (QTRA) system moves the management of tree safety away from labelling trees as either ‘safe’ or ‘unsafe’ and thereby away from requiring definitive judgements from either tree assessors or tree managers.

Instead, QTRA quantifies the risk of significant harm from tree failure in a way that enables tree managers to balance safety with tree values and operate to predetermined limits of tolerable or acceptable risk.

We have received some excellent feedback from workshops carried out throughout the UK as well as Australia and New Zealand over the course of the year.

Visit Training to use QTRA for booking and further information on QTRA and Visual Tree Assessment workshops.

For large landowners, Quantified Tree Risk Assessment (QTRA) is a way of informing reasonable and proportionate allocation of financial resources while optimising the benefits from trees. For anyone who manages a small number of trees and wants to base their safety management decisions on the best possible analysis of the risk, QTRA will help you to quantify the risk better than any other approach. For the tree advisor, QTRA provides a risk assessment framework for the survey of your client’s trees, whether as a detailed inventory or a broad overview, and it provides an audit trail to demonstrate that you have followed a structured process.

Using QTRA, you first assess the land-use (targets) onto which trees could fail, and this enables the tree managers to determine whether or not and to what degree of rigour a survey or inspection of the trees is required. Where it is necessary to assess an individual tree, the tree or branch is then considered in terms of both impact potential (size) and probability of failure. Values derived from the assessment of these three components are used to calculate the risk, which can then be considered against thresholds for action.

Due to popular demand, and as a complement the QTRA training, we run it side-by-side with our ‘Practitioners Guide to Visual Tree Assessment’. VTA is an integral part of QTRA because it informs the Probability of Failure component of the risk assessment. During the day, inside and out in the field, we bring together the key work of researchers to look at tree health and stability with an emphasis on decay colonisation, vitality and mechanical self-optimisation, limitations of strength-loss formulae, and mapping decay with the Thor 710 hammer. The ‘Practitioner’ leaves with a greater understanding and confidence in their VTA skills that will better inform risk assessments.

Click on the link below for QTRA and Visual Tree Assessment Training workshops, which have been scheduled for the first half of 2013:

Training to use QTRA

You may also find our Newsletter of interest, which includes information on the services we offer and some articles on current tree management issues:

http://www.qtra.co.uk/cms/index.php?action=download&id=231&module=downloadmodule&src=%40random4ecb7957db7c6