Preservation and Restoration of Roadside Tree Alleys in Line with Sustainable Development Principles—Mission (Im)possible?

Źróbek-Sokolnik, Anna; Dynowski, Piotr; Źróbek, Sabina

doi:10.3390/su13179635

Cited by 4 publications

(2 citation statements)

References 31 publications

(28 reference statements)

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“…Most roadside trees consist of broadleaved trees which were usually the same species, similar in tree age (i.e., tree height and crown size) [141][142][143]. The regular layout of roadside trees made the offset simple and spatially consistent [144,145], reducing the local registration noise for roadside trees.…”

Section: Matching Accuracy In Different Landscapesmentioning

confidence: 99%

A Novel Approach to Match Individual Trees between Aerial Photographs and Airborne LiDAR Data

Xu,

Wang,

Skidmore

et al. 2023

Remote Sensing

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Integrating multimodal remote sensing data can optimize the mapping accuracy of individual trees. Yet, one issue that is not trivial but generally overlooked in previous studies is the spatial mismatch of individual trees between remote sensing datasets, especially in different imaging modalities. These offset errors between the same tree on different data that have been geometrically corrected can lead to substantial inaccuracies in applications. In this study, we propose a novel approach to match individual trees between aerial photographs and airborne LiDAR data. To achieve this, we first leveraged the maximum overlap of the tree crowns in a local area to determine the correct and the optimal offset vector, and then used the offset vector to rectify the mismatch on individual tree positions. Finally, we compared our proposed approach with a commonly used automatic image registration method. We used pairing rate (the percentage of correctly paired trees) and matching accuracy (the degree of overlap between the correctly paired trees) to measure the effectiveness of results. We evaluated the performance of our approach across six typical landscapes, including broadleaved forest, coniferous forest, mixed forest, roadside trees, garden trees, and parkland trees. Compared to the conventional method, the average pairing rate of individual trees for all six landscapes increased from 91.13% to 100.00% (p = 0.045, t-test), and the average matching accuracy increased from 0.692 ± 0.175 (standard deviation) to 0.861 ± 0.152 (p = 0.017, t-test). Our study demonstrates that the proposed tree-oriented matching approach significantly improves the registration accuracy of individual trees between aerial photographs and airborne LiDAR data.

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Section: Matching Accuracy In Different Landscapesmentioning

confidence: 99%

A Novel Approach to Match Individual Trees between Aerial Photographs and Airborne LiDAR Data

Xu,

Wang,

Skidmore

et al. 2023

Remote Sensing

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“…But research revealed less than ideal situations. In different cities, transport land use had low tree biodiversity (Sever- Mutlu et al, 2017;Liu & Slik 2022;Źróbek-Sokolnik et al, 2021). Hong Kong shared a similar situation.…”

Section: Introductionmentioning

confidence: 99%

Streamlining urban forest monitoring based on a large-scale tree survey: a case study of highway vegetation in Hong Kong

Lee

Zhang

Ng³

et al. 2022

Environ Monit Assess

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Urban tree monitoring is essential to successful urban forestry. Transport land use accommodates huge tree stock which require substantial monitoring efforts. In Hong Kong, more research is needed to take into considerations how monitoring works can be modi ed in response to variations in tree stand characteristics. This case study aimed to illustrate the usefulness of a large-scale tree survey in mainstreaming future tree monitoring and management in transport land use. 7,209 trees were found in a large-scale tree survey conducted in 53 slopes and 52 verges along San Tin Highway in Hong Kong. Dominance by Corymbia citriodora (72%) was observed, especially for the highway verges. Using chisquare tests, signi cant associations were found between monospeci c stands, habitat type, and tree risk rating. A logistic regression model was constructed to predict the occurrence of monoculture. Every metre increase in maximum tree height, the odds of a stand being monospeci c would be 1.22 times greater.Stands on verges had 5.26 times greater odds of being monospeci c against slope. The associations and relationships were attributed to the dominance of C. citriodora. By boosting the logistic model, model reliability increased as kappa rose from 0.51 to 0.63, while balanced accuracy improved from 0.72 to 0.85. The occurrence of monospeci c stands could be reliably predicted using maximum tree height and habitat type of tree stands. These quantitative ndings monitoring can guide urban forest monitoring. Through a better understanding of urban forest structure and composition, future monitoring can aid the mainstreaming of urban forestry in transport planning.

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Assessing large-scale roadside tree removal using aerial imagery and crash analysis: A difference-in-differences approach

White,

Meixler

2024

Landscape and Urban Planning

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Preservation and Restoration of Roadside Tree Alleys in Line with Sustainable Development Principles—Mission (Im)possible?

Cited by 4 publications

References 31 publications

A Novel Approach to Match Individual Trees between Aerial Photographs and Airborne LiDAR Data

A Novel Approach to Match Individual Trees between Aerial Photographs and Airborne LiDAR Data

Streamlining urban forest monitoring based on a large-scale tree survey: a case study of highway vegetation in Hong Kong

Assessing large-scale roadside tree removal using aerial imagery and crash analysis: A difference-in-differences approach

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