Unveiling Falling Urban Trees before and during Typhoon Higos (2020): Empirical Case Study of Potential Structural Failure Using Tilt Sensor

Abstract

Urban trees in a densely populated environment may pose risks to the public’s safety in terms of the potential danger of injuries and fatalities, loss of property, impacts on traffic, etc. The biological and mechanical features of urban trees may change over time, thereby affecting the stability of the tree structure. This can be a gradual process but can also be drastic, especially after typhoons or heavy rainstorms. Trees may fall at any time with no discernible signs of failure being exhibited or detected. It is always a challenge in urban tree management to develop a preventive alert system to detect the potential failure of hazardous urban trees and hence be able to have an action plan to handle potential tree tilting or tree collapse. Few studies have considered the comparison of tree morphology to the tilt response relative to uprooting failure in urban cities. New methods involving numerical modeling and sensing technologies provide tools for an effective and deeper understanding of the interaction of root-plate movement and windstorm with the application of the tailor-made sensor. In this study, root-plate tilt variations of 889 trees with sensors installed during Typhoon Higos (2020) are investigated, especially the tilting pattern of the two trees that failed in the event. The correlation of tree response during the typhoon among all trees with tilt measurements was also evaluated. The results from two alarm levels developed in the study, i.e., Increasing Trend Alarm and Sudden Increase Alarm indicated that significant root-plate movement to wind response is species-dependent. These systems could help inform decision making to identify the problematic trees in the early stage. Through the use of smart sensors, the data collected by the alert system provides a very useful analysis of the stability of tree structure and tree health in urban tree management.

Crown feature effect evaluation on wind load for evergreen species based on laser scanning and wind tunnel experiments

“…The wind tunnel test was conducted following the procedure below: (1) Cut off three fractal-like branches, which are around 1.5 m tall and like small trees, from each sample tree; (2) Each branch, together with load sensors, was fixed to a base in the wind tunnel laboratory; (3) The wind tunnel test was performed under 5 different wind speeds: 4, 6, 8, 10, 12 m/s, corresponding to light breeze, gentle breeze, moderate breeze, fresh breeze and strong breeze, respectively (referring to Beaufort Scale: level 2 to level 6). The setting of wind speeds in this study is based on the record of wind speed tree suffered in urban green space during typhoon period 33 , and considering the complicated urban wind field in typhoon where wind speed is smaller at a lower height 34 . The 3-axis forces on the piece caused by the wind were measured using load balance.…”

“…Windward side projection area : SC = SA0 + SB0 ). The setting of wind speeds in this study is based on the record of wind speed tree suffered in urban green space during typhoon period 33 , and considering the complicated urban wind field in typhoon where wind speed is smaller at a lower height 34 . The 3-axis forces on the piece caused by the wind were measured using load balance.…”

Smart Fruit Growing Through Digital Twin Paradigm: Systematic Review and Technology Gap Analysis

“…The range of sensors used in agriculture is wide, starting with clip-type cameras used to monitor plants and predict optional time for harvesting based on images (Lee et al, 2022) and ending with more unusual IoT solutions, like tilt sensors. They are not common in agriculture, but they can be used for danger warnings in locations with potential highintensity storms or hurricanes (Hui et al, 2022).…”

Spatial Analysis of Risk Exposure of Urban Trees: A Case Study from Bologna (Italy)

“…Tree risk research currently focuses on predicting defects and structural impact principles from accidental causes [36][37][38]. Despite the fact that systematic risk assessment is an effective and economical method of determining tree risk at the outset, data acquisition for assessment metrics remains predominantly subjective [34], and further research is needed.…”