scholarly journals A Review of Dynamic Tree Behaviors: Measurement Methods on Tree Sway, Tree Tilt, and Root–Plate Movement

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 379
Author(s):  
Zi Yang ◽  
Ka Wai Hui ◽  
Sawaid Abbas ◽  
Rui Zhu ◽  
Coco Yin Tung Kwok ◽  
...  
Keyword(s):  
Monitoring System ◽  
Indicator System ◽  
Measurement Methods ◽  
Urban Trees ◽  
Wind Loads ◽  
Individual Tree ◽  
Plate Movement ◽  
Dynamic Tree ◽  
Analytical Approaches ◽  
Root Plate

Urban forest ecosystems are being developed to provide various environmental services (e.g., the preservation of urban trees) to urban inhabitants. However, some trees are deteriorated asymptomatically without exhibiting an early sign of tree displacement, which results in a higher vulnerability under dynamic wind loads, especially during typhoon seasons, in the subtropical and tropical regions. As such, it is important to understand the tilt and sway behaviors of trees to cope up with the probability of tree failure and to improve the efficacy of tree management. Tree behaviors under wind loads have been broadly reviewed in the past literature, yet thorough discussions on the measurement methods for tree displacement and its analysis of broadleaf specimens are lacking. To understand the behavioral pattern of both broadleaf and conifer species, this paper presents a detailed review of sway behavior analysis from the perspectives of the aerial parts of the individual tree, including tree stem, canopy, and trunk, alongside a highlighted focus on the root–plate movement amid the soil-root system. The analytical approaches associated with the time-space domain and the time-frequency domain are being introduced. In addition to the review of dynamic tree behaviors, an integrated tree monitoring framework based on geographic information systems (GIS) to detect and visualize the extent of tree displacement using smart sensing technology (SST) is introduced. The monitoring system aims to establish an early warning indicator system for monitoring the displacement angles of trees over the territory of Hong Kong’s urban landscape. This pilot study highlights the importance of the monitoring system at an operational scale to be applicable in the urban areas showcasing the practical use of the Internet of Things (IoT) with an in-depth understanding of the wind-load effect toward the urban trees in the tropical and subtropical cities.

scholarly journals A study on the development of a light scattering particulate matter sensor and monitoring system

2020 ◽  
Vol 17 (3) ◽  
pp. 867-890
Author(s):  
Jun-Hee Choi ◽  
Hyun-Sug Cho
Keyword(s):  
Big Data ◽  
Particulate Matter ◽  
Light Scattering ◽  
Real Time ◽  
Monitoring System ◽  
Low Cost ◽  
Gravimetric Method ◽  
Correction Method ◽  
Measurement Methods ◽  
Linear Correction

The gravimetric method, which is mainly used among particulate matter (PM) measurement methods, includes the disadvantages that it cannot measure PM in real time and it requires expensive equipment. To overcome these disadvantages, we have developed a light scattering type PM sensor that can be manufactured at low cost and can measure PM in real time. We have built a big data system that can systematically store and analyze the data collected through the developed sensor, as well as an environment where PM states can be monitored mobile in real time using such data. In addition, additional studies were conducted to analyze and correct the collected big data to overcome the problem of low accuracy, which is a disadvantage of the light scattering type PM sensor. We used a linear correction method and proceeded to adopt the most suitable value based on error and accuracy.

scholarly journals Structural Root-Plate Characteristics of Wind-Thrown Norway Spruce in Hemiboreal Forests of Latvia

Forests ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1143 ◽  
Author(s):  
Oskars Krišāns ◽  
Valters Samariks ◽  
Jānis Donis ◽  
Āris Jansons
Keyword(s):  
Norway Spruce ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Rooting Depth ◽  
Peat Soils ◽  
Individual Tree ◽  
Weather Events ◽  
Mineral Soils ◽  
Root Plate ◽  
Plate Width

An increase in extreme weather events is predicted with increasing climate changes. Changes indicate major problems in the future, as Norway spruce (Picea abies L. Karst.) is one of the most important forestry species in Northern Europe and one of the most susceptible to damage from extreme weather events, like windstorms. Root architecture is essential for tree anchorage. However, information of structural root-plate volume and characteristics in relation to tree wind resistance in drained deep peat soils is lacking. Individual tree susceptibility to wind damage is dependent on tree species, soil properties, tree health and root-plate volume. We assessed the structural root-plate dimensions of wind-thrown Norway spruce on freely drained mineral and drained deep peat soils at four trial sites in Latvia, and root-plate measurements were made on 65 recently tipped-up trees and 36 trees from tree-pulling tests on similar soils. Tree height, diameter at breast height, root-plate width and depth were measured. Measurements of structural root-plate width were done in five directions covering 180° of the root-plate; rooting depth was measured on the horizontal and vertical axes of root-plate. Root-plate volume was higher in drained peat soils in comparison to mineral soils, and root-plate width was the main driver of root-plate volume. A decreasing trend was observed in structural root depth distribution with increasing distance from the stem (i.e., from the center to the edge of the root plate) with a greater decrease in mineral soils.

scholarly journals Comparison of the Economic Value of Urban Trees Through Surveys with Photographs in Two Seasons

2018 ◽  
Author(s):  
Claudia García-Ventura ◽  
Álvaro Sánchez-Medina ◽  
M. Ángeles Grande-Ortíz ◽  
Concepción González-García ◽  
Esperanza Ayuga-Tellez
Keyword(s):  
Engineering Students ◽  
Economic Value ◽  
Economic Assessment ◽  
Statistical Test ◽  
Urban Trees ◽  
Anova Analysis ◽  
Deciduous Species ◽  
Individual Tree ◽  
Welch Test ◽  
Differences Of Opinion

Urban trees are generally considered to be a public asset and are an important part of a city's heritage. The aim of this work is to analyse the influence of season on the economic appraisal of various trees in Madrid. Photographs were taken of 43 individual tree specimens in summer and winter. The survey was designed to compare differences of opinion in the economic assessment of trees. The trees were assessed by five valuation methods used worldwide. 78 agroforestry engineering students answered a written survey, and the variables considered were: percentage of students who always evaluated the tree equally (%0), percentage of students who assigned more value to the summer photograph (%S), and percentage of students who assigned more value to the winter photograph (%W). The results were analysed by the statistical test of equal proportions and ANOVA to detect differences according to tree type (evergreen or deciduous), species and other groupings made by the authors in previous works. W and S percentages are similar. The ANOVA analysis rejects the equality of percentages of S and W between groups. The Welch test rejects the equality of percentage of S, W and O between species.

scholarly journals Detection of Tree Crown from Satellite Imagery using Object Based Image Examination

2019 ◽  
Vol 8 (2S10) ◽  
pp. 281-285
Keyword(s):  
Decision Tree ◽  
Urban Areas ◽  
Gaussian Mixture ◽  
Tree Canopy ◽  
Urban Trees ◽  
Individual Tree ◽  
Object Based ◽  
High Resolution Satellite Images ◽  
Multiresolution Segmentation ◽  
Decision Tree Method

Detection and delineation of individual tree mainly depends on high resolution satellite images or LiDAR data. Urban green structure, specially urban trees plays a key role in enhancing the life of people. Now a day’s more than half of population is leaving in cities and urban areas. Methods to quantify and monitor trees are not efficient. The traditional methods for forest survey and ground survey are complex because of changes occurs in urban environment. The objective of this research is to extract vegetation using colour based and decision tree method, which can be further sub-classify to obtain area under tree canopy. The results obtained through Object-Based Image Analysis (OBIA) method are also compared with existing Gaussian Mixture Model (GMM) method. The overall accuracy achieved thereby is 93.85% using Decision tree-multiresolution segmentation and 93.31% using Decision tree-GMM method.

scholarly journals Assessment of Sensor Technologies for Aircraft SHM Systems

2014 ◽  
Vol 2013 (5) ◽  
pp. 53-59 ◽  
Author(s):  
Artur Kurnyta ◽  
Krzysztof Dragan ◽  
Michal Dziendzikowski
Keyword(s):  
Power Consumption ◽  
Monitoring System ◽  
Eddy Current ◽  
Data Transmission ◽  
Measurement Methods ◽  
Strain Gages ◽  
Safety And Reliability ◽  
Inspected Object ◽  
Fatigue Fractures

Abstract SHM is a monitoring system which uses sensors, actuators and data transmission, acquisition and analysis, permanently integrated with the inspected object. The objective of SHM is to detect, localize, identify and predict development of fatigue fractures, increasing safety and reliability. This paper presents an assessment of sensor technologies used in aircraft SHM system. Due to the fact that most of these measurement methods are relatively new and still under development the present appraisal focuses on a number of parameters with reference to each method, including a sensor’s installation issues, reliability, power consumption, sensor infrastructure, sensitivity and cost and availability. The work is predominantly focused on the assessment ofpermanently bonded sensors, such as foil strain gages, Comparative Vacuum Monitoring (CVM), Piezo sensors (PZT), Eddy-Current Transducers (ECT). Finally, all these methods are briefly discussed.

scholarly journals Automatic Detection and Parameter Estimation of Ginkgo biloba in Urban Environment Based on RGB Images

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Kai Xia ◽  
Hao Wang ◽  
Yinhui Yang ◽  
Xiaochen Du ◽  
Hailin Feng
Keyword(s):  
Neural Network ◽  
Parameter Estimation ◽  
Inventory Management ◽  
Ginkgo Biloba ◽  
Tree Height ◽  
Urban Trees ◽  
Percentage Error ◽  
Individual Tree ◽  
Tree Crowns ◽  
Rgb Images

Individual tree crown detection and morphological parameter estimation can be used to quantify the social, ecological, and landscape value of urban trees, which play increasingly important roles in densely built cities. In this study, a novel architecture based on deep learning was developed to automatically detect tree crowns and estimate crown sizes and tree heights from a set of red-green-blue (RGB) images. The feasibility of the architecture was verified based on high-resolution unmanned aerial vehicle (UAV) images using a neural network called FPN-Faster R-CNN, which is a unified network combining a feature pyramid network (FPN) and a faster region-based convolutional neural network (Faster R-CNN). Among more than 400 tree crowns, including 213 crowns of Ginkgo biloba, in 7 complex test scenes, 174 ginkgo tree crowns were correctly identified, yielding a recall level of 0.82. The precision and F -score were 0.96 and 0.88, respectively. The mean absolute error (MAE) and mean absolute percentage error (MAPE) of crown width estimation were 0.37 m and 8.71%, respectively. The MAE and MAPE of tree height estimation were 0.68 m and 7.33%, respectively. The results showed that the architecture is practical and can be applied to many complex urban scenes to meet the needs of urban green space inventory management.

scholarly journals Remotely Sensed Tree Characterization in Urban Areas: A Review

2021 ◽  
Vol 13 (23) ◽  
pp. 4889
Author(s):  
Luisa Velasquez-Camacho ◽  
Adrián Cardil ◽  
Midhun Mohan ◽  
Maddi Etxegarai ◽  
Gabriel Anzaldi ◽  
...  
Keyword(s):  
Urban Areas ◽  
Urban Forestry ◽  
Remotely Sensed ◽  
Critical Discussion ◽  
Urban Trees ◽  
Future Research ◽  
Remotely Sensed Data ◽  
Individual Tree ◽  
Processing Methods ◽  
Urban Tree

Urban trees and forests provide multiple ecosystem services (ES), including temperature regulation, carbon sequestration, and biodiversity. Interest in ES has increased amongst policymakers, scientists, and citizens given the extent and growth of urbanized areas globally. However, the methods and techniques used to properly assess biodiversity and ES provided by vegetation in urban environments, at large scales, are insufficient. Individual tree identification and characterization are some of the most critical issues used to evaluate urban biodiversity and ES, given the complex spatial distribution of vegetation in urban areas and the scarcity or complete lack of systematized urban tree inventories at large scales, e.g., at the regional or national levels. This often limits our knowledge on their contributions toward shaping biodiversity and ES in urban areas worldwide. This paper provides an analysis of the state-of-the-art studies and was carried out based on a systematic review of 48 scientific papers published during the last five years (2016–2020), related to urban tree and greenery characterization, remote sensing techniques for tree identification, processing methods, and data analysis to classify and segment trees. In particular, we focused on urban tree and forest characterization using remotely sensed data and identified frontiers in scientific knowledge that may be expanded with new developments in the near future. We found advantages and limitations associated with both data sources and processing methods, from which we drew recommendations for further development of tree inventory and characterization in urban forestry science. Finally, a critical discussion on the current state of the methods, as well as on the challenges and directions for future research, is presented.

scholarly journals Assessment of Above-Ground Carbon Storage by Urban Trees Using LiDAR Data: The Case of a University Campus

Forests ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 62
Author(s):  
Derya Gülçin ◽  
Cecil C. Konijnendijk van den Bosch
Keyword(s):  
Carbon Storage ◽  
Mean Squared Error ◽  
Information Criterion ◽  
Urban Ecosystem ◽  
Urban Trees ◽  
Tree Level ◽  
Lidar Data ◽  
Estimation Model ◽  
Individual Tree ◽  
Essential Information

The biomass represented by urban trees is important for urban decision-makers, green space planners, and managers seeking to optimize urban ecosystem services. Carbon storage by urban trees is one of these services. Suitable methods for assessing carbon storage by urban trees are being explored. The latest technologies in remote sensing and data analyses can reduce data collection costs while improving accuracy. This paper introduces an assessment approach that combines ground measurements with unmanned aerial vehicle-based light detection and ranging (LiDAR) data to estimate carbon storage by urban trees. Methods underpinning the approach were tested for the case of the Vancouver campus of the University of British Columbia (UBC), Canada. The study objectives were (1) to test five automated individual tree detection (AITD) algorithms and select one on the basis of the highest segmentation accuracy, (2) to develop a model to estimate the diameter at breast height (DBH), and (3) to estimate and map carbon storage over the UBC campus using LiDAR heights, estimated DBHs, and an existing tree-level above-ground carbon estimation model. Of the segmentation algorithms tested, the Dalponte AITD had the highest F score of 0.83. Of the five CW thresholds (th) tested in the DBH estimation model, we chose one resulting in the lowest Akaike’s information criterion, the highest log-likelihood, and the lowest root-mean-squared error (19.55 cm). Above-ground carbon was estimated for each tree in the study area and subsequently summarized, resulting in an estimated 5.27 kg C·m−2 over the main campus of UBC, Vancouver. The approach could be used in other urban jurisdictions to obtain essential information on urban carbon storage in support of urban landscape governance, planning, and management.

scholarly journals A CONCEPT FOR THE SEGMENTATION OF INDIVIDUAL URBAN TREES FROM DENSE MLS POINT CLOUDS

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 171-178
Author(s):  
P.-R. Hirt ◽  
L. Hoegner ◽  
U. Stilla
Keyword(s):  
Urban Areas ◽  
Laser Scanning ◽  
Region Growing ◽  
Point Clouds ◽  
General Concept ◽  
Urban Trees ◽  
Individual Tree ◽  
Positive Effects ◽  
3D Point Clouds ◽  
The Individual

Abstract. In our daily lives, trees can be seen as the tallest and most noticeable representatives of the plant kingdom. Especially in urban areas, the individual tree is of high significance and responsible for a manifold of positive effects on the environment and residents. In the context of urban tree registers and thus monitoring of urban vegetation, we propose a general concept for the segmentation of trees from 3D point clouds. Mobile Laser Scanning (MLS) is introduced as the preferred sensor. Based on an analysis of earlier work in this field, we gather arguments and methods in order to involve segmentation in the bigger frame of a tree register workflow, including detailed modeling and change detection. Our concept for segmentation is based on a voxel-structure. In a first step, region growing approaches are used for ground removal and rough segmentation. Later, graph-based optimization will separate neighboring trees. For now, only the general concept can be introduced—quantitative analysis and optimization of the steps will follow in future work.

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