Evaluating the efficacy of a local tree protection policy using LiDAR remote sensing data

Sung, Chan Yong

doi:10.1016/j.landurbplan.2011.09.009

Cited by 23 publications

(9 citation statements)

References 41 publications

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“…In this context, researchers note that the City of Melbourne is currently developing a register of exceptional trees on private property with the intention of protection through the Melbourne Planning Scheme. The study authors also note that regulation has been shown to be effective in retaining large private trees in at least one western city (Sung 2012).…”

Section: Planning and Management Implicationsmentioning

confidence: 80%

Using Size Class Distributions of Species to Deduce the Dynamics of the Private Urban Forest

Pearce¹,

Kirkpatrick²,

Davison³

2013

AUF

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Urban governance in Western societies is increasingly shaped by awareness of the importance of trees in maintaining the environmental function and social livability of cities. Records of change in urban forest composition on public land are generally good. However, a great proportion of trees in western cities occur on private land, where such changes are poorly-documented. The study authors trialed the use of size class analysis, a technique widely used to deduce the dynamics of natural forests, to determine change in the private urban forest. From a sample of blocks in ten suburbs of the Australian cities of Melbourne and Hobart, in which most dwellings have front and back gardens, researchers assessed the implications of changes for the functionality of the urban forest. The height class distributions of a large number of front garden tree taxa were classified. Although the factors affecting height class distributions differ between a natural and an urban forest, those distributions found for most species were so extreme that there was little doubt in interpretation. Tree species that can grow to a large height were under-represented in the smaller height classes, indicating their future decline in the private tree estate. Individuals of glossy-leaved small tree species were over-represented in the smaller height classes, indicating a recent increase in their popularity. The shift toward smaller, denser trees on private land has implications for the functions of the urban forest. A higher level of large tree protection on private land and compensation through planting on public land could mitigate impacts.

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Section: Planning and Management Implicationsmentioning

confidence: 80%

Using Size Class Distributions of Species to Deduce the Dynamics of the Private Urban Forest

Pearce¹,

Kirkpatrick²,

Davison³

2013

AUF

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“…In contrast to RADAR data, LiDAR data on urban forest have been widely used and adopted (Forzieri et al 2009;Nicholas et al 2012;Oshio et al 2012;Zhang and Qiu 2012;Zhu et al 2012;Adeline et al 2013;Niemeyer et al 2013;Oshio et al 2013;Zhou 2013). Sung (2012) applied LiDAR data to assess the mean canopy height and percent canopy cover of an urban forest. According to the land development ordinance, the landowner should secure a permit to remove trees larger than 41 cm in diameter at breast height.…”

Section: Evaluation Of Different Satellite Imaging Techniquesmentioning

confidence: 99%

“…Many studies have been employed on different aspects of urban forests, including tree crown shape and structure (Oshio et al 2012;Sung 2012;Oshio et al 2013), tree detection and urban vegetation mapping (Hofle et al 2012;MacFaden et al 2012;Yao and Wei 2013;Zhou 2013), tree position and plant density (Forzieri et al 2009), and individual tree species detection (Nicholas et al 2012;Zhang and Qiu 2012). Zhang and Qiu (2012) solved the limitation of LiDAR data by using hyperspectral imaging to distinguish more than 10 tree species, and LiDAR data to detect tree crowns only; thus, the accuracy of tree species detection was directly related to the resolution of the images.…”

Section: Evaluation Of Different Satellite Imaging Techniquesmentioning

confidence: 99%

Review on the Use of Remote Sensing for Urban Forest Monitoring

Shojanoori¹,

Shafri²

2016

AUF

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Urban forests are vital in urban areas because they clean the air, absorb water, and protect the environment from intense heat. Destruction of the urban forest by increased urbanization is a considerable threat to the ecosystem. Hence, urban planners must obtain and manage information about urban forests, but the complexity of urban areas has made these tasks difficult. With developments in remote-sensing technologies, the monitoring and detection of urban forests can be achieved without performing any field measurements. In this study, different remote-sensing imageries and various methods are evaluated to obtain urban forest information. This review demonstrates that very high resolution (VHR) satellite imagery, such as from WorldView-2, is the most efficient data that can be used to obtain urban forest information. The use of the combination of LiDAR data with VHR imagery increases the accuracy of information, particularly about tree crown delineation. Traditional pixel-based classification methods are not effectively applicable to obtain urban tree information because of significant spectral variability in urban areas. An object-based classification technique, which uses spatial, textural, and color information, can be a potential method to detect urban forest and tree species discrimination. The new VHR imaging method, which uses the object-based technique, is recommended to overcome limitations of collecting urban forest information.

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“…The heights of tree canopies were derived by subtracting the ground elevations interpolated by the TIN from elevations of the above-the-ground LiDAR points. Because not all of the above-the-ground LiDAR points were returned from tree canopy but from other objects, such as rocks and benches, the estimated canopy heights less than 1 m were excluded from the analysis (Sung, 2012).…”

Section: Lidar Data Processingmentioning

confidence: 99%

Estimating the annual carbon budget of a weekend tourist resort in a temperate secondary forest in Korea

Sung¹,

Cho²,

Hong³

2015

Urban Forestry & Urban Greening

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Evaluating the efficacy of a local tree protection policy using LiDAR remote sensing data

Cited by 23 publications

References 41 publications

Using Size Class Distributions of Species to Deduce the Dynamics of the Private Urban Forest

Using Size Class Distributions of Species to Deduce the Dynamics of the Private Urban Forest

Review on the Use of Remote Sensing for Urban Forest Monitoring

Estimating the annual carbon budget of a weekend tourist resort in a temperate secondary forest in Korea

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