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

Gülçin, Derya; Bosch, Cecil C. Konijnendijk van den

doi:10.3390/f12010062

Cited by 19 publications

(9 citation statements)

References 65 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In each selected tree, the total height (H) (with a Blume-Leiss instrument), maximum and minimum crown diameter (CW) were measured. Then the tree crown diameter was calculated as the average of the maximum and minimum crown diameter (Gülçin and Bosch, 2021). As for the type of pavement, the usual pavements, which are covered with semi-permeable (at the joints) slabs, were found in both cities.…”

Section: Methods Of Investigationmentioning

confidence: 99%

Allometries of Acer negundo for a better space management in two cities of northeastern Greece

2023

View full text Add to dashboard Cite

The ability to estimate the space volume that a tree occupies, in various heights, is a crucial factor in designing the street trees schedule in pavements of new urban infrastructures. The dimensions of Acer negundo tree crown in various heights can be the basis for a better space management in the pavements of cities. In this study, the height and the crown width of the A. negundo street trees in the Greek cities of Orestiada and Alexandroupoli and the allometric relations that can be found between them, were investigated. Data from 117 street trees growing in semi-permeable pavements of the two cities were used. In each selected tree, the total height (H), and the maximum and minimum crown diameter (CW) were measured. The selected model (CW-H) for Alexandroupoli exhibits a coefficient of determination (R2) of 0.81. The R2 of the model selected for Orestiada is lower (R2 = 0.66). The R2 of the model selected using the complete dataset is 0.77. A. negundo appears to have greater crown width in Alexandroupoli compared to that of Orestiada. In Orestiada the conditions of growth were variable since in many cases the measured trees were under side shade, while this not the case in the corresponding trees in Alexandroupoli. The better fit of the selected model in Alexandroupoli compared to that of Orestiada is probably due to the more variable growth conditions of Orestiada.

show abstract

Section: Methods Of Investigationmentioning

confidence: 99%

Allometries of Acer negundo for a better space management in two cities of northeastern Greece

2023

View full text Add to dashboard Cite

show abstract

“…The main component of urban open and green areas is plants. Plants provide many benefits such as reducing air pollution, regulating micro-climate, providing habitat for wild animals, carbon sequestration, energy saving, reducing noise, erosion control, making positive contributions to urban aesthetics, and creating space (Önder & Akbulut, 2011;Sakıcı, Karakaş & Kesimoğlu, 2013;Yılmaz, Düzenli & Dinçer, 2017;Düzenli, Yılmaz & Tarakçı Eren, 2018;Eren, 2019;Gülçin & Van Den Bosch, 2021;Karaşah, 2021). However, despite all these benefits, it was seen that many plant species used in open and green spaces designed today are mostly chosen by keeping their form, color, and aesthetic features in the foreground (Bayramoğlu & Şatıroğlu, 2018;Sarı & Karaşah, 2018).…”

Section: Introductionmentioning

confidence: 99%

An Investigation on Plants with Allergic Pollen: The Case of Rize Urban Open Green Areas

EKREN

Çorbacı

2022

MBUD

View full text Add to dashboard Cite

With its environmental, social, and economic advantages, urban open and green areas play an essential role in improving the quality of life of city dwellers. Plants, which constitute the foundation of these areas, have both positive and detrimental effects on human health and provide numerous essential advantages to the urban ecosystem. One of these negative effects is that pollen causes allergic responses. The goal of this study was to identify allergenic plant taxa in Rize province's urban open green areas. In the Rize urban open green areas, 110 plant taxa that potentially induce allergic reactions were discovered as part of the study. These plants were evaluated in terms of family, life form, flowering period, allergen rate, protective case and location. As a result of this evaluation, from 110 plants; it was determined that 42 of them had low allergen rate, 26 of them had moderate allergen rate and 42 of them had high allergen rate. In addition, several proposals for using these species in planting design applications have been produced.

show abstract

“…Lin et al [28] delineated individual trees and extracted tree height, crown radius, competition index, and stem diameter from airborne LiDAR-derived canopy height model (CHM), then they accurately modelled aboveground carbon stocks. Gulcin et al [29] segmented individual trees and estimated diameter at breast height (DBH) using LiDAR height and canopy area, and then they estimated carbon stocks using LiDAR heights, estimated DBH, and an existing empirical model for estimating tree-level above-ground carbon stocks [30]. Coomes et al [31] delineated trees within the CHM derived from airborne-LiDAR data by a itcSegment algorithm, which works by finding local maxima in the raster CHM and then growing crowns around them by local searching of the raster CHM [32][33][34][35].…”

Section: Introductionmentioning

confidence: 99%

Estimating Aboveground Carbon Stock at the Scale of Individual Trees in Subtropical Forests Using UAV LiDAR and Hyperspectral Data

et al. 2021

View full text Add to dashboard Cite

Accurate estimation of aboveground carbon stock for individual trees is important for evaluating forest carbon sequestration potential and maintaining ecosystem carbon balance. Airborne light detection and ranging (LiDAR) data has been widely used to estimate tree-level carbon stock. However, few studies have explored the potential of combining LiDAR and hyperspectral data to estimate tree-level carbon stock. The objective of this study is to explore the potential of integrating unmanned aerial vehicle (UAV) LiDAR with hyperspectral data for tree-level aboveground carbon stock estimation. To achieve this goal, we first delineated individual trees by a CHM-based watershed segmentation algorithm. We then extracted structural and spectral features from UAV LiDAR and hyperspectral data respectively. Then, Pearson correlation analysis was conducted to assess the correlation between LiDAR features, hyperspectral features, and tree-level carbon stock, based on which, features were selected for model development. Finally, we developed tree-level carbon stock estimation models based on the Schumacher–Hall formula and stepwise multiple regression. Results showed that both LiDAR and hyperspectral features were strongly correlated to tree-level carbon stock. Both tree height (H, r = 0.75) and Green index (GI, r = 0.83) had the highest correlation coefficients with tree-level carbon stock in LiDAR and hyperspectral features, respectively. The best model using LiDAR features alone includes the metrics of H, the 10th height percentile of points (PH10), and mean height of points (Hmean), and can explain 74% of the variations in tree-level carbon stock. Similarly, the best model using hyperspectral data includes GI and modified normalized differential vegetation index (mNDVI), and has similar explanatory power (r2 = 0.75). The model that integrates predictors, namely, GI and the 95th height percentile of points (PH95) from hyperspectral and LiDAR data, substantially improves the explanatory power (r2 = 0.89). These results indicated that while either LiDAR data or hyperspectral data alone can estimate tree-level carbon stock with reasonable accuracy, combining LiDAR and hyperspectral features can substantially improve the explanatory power of the model. Such results suggested that tree-level carbon stock estimation can greatly benefit from the complementary nature of LiDAR-detected structural characteristics and hyperspectral-captured spectral information of vegetation.

show abstract

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

Cited by 19 publications

References 65 publications

Allometries of Acer negundo for a better space management in two cities of northeastern Greece

Allometries of Acer negundo for a better space management in two cities of northeastern Greece

An Investigation on Plants with Allergic Pollen: The Case of Rize Urban Open Green Areas

Estimating Aboveground Carbon Stock at the Scale of Individual Trees in Subtropical Forests Using UAV LiDAR and Hyperspectral Data

Contact Info

Product

Resources

About