Assessment of urban tree condition using sonic tomography technology

Abstract Key message A model for sustainable planning of urban tree stocks is proposed, incorporating growth, mortality, replacement rates and ecosystem service provision, providing a basis for planning of urban tree stocks. Abstract Many recent studies have improved the knowledge about urban trees, their structures, functions, and ecosystem services. We introduce a concept and model for the sustainable management of urban trees, analogous to the concept of sustainable forestry developed by Carl von Carlowitz and others. The main drivers of the model are species-specific tree diameter growth functions and mortality rates. Based on the initial tree stock and options for the annual replanting, the shift of the distribution of the number of trees per age class can be predicted with progressing time. Structural characteristics such as biomass and leaf area are derived from tree dimensions that can be related to functions such as carbon sequestration or cooling. To demonstrate the potential of the dynamic model, we first show how different initial stocks of trees can be quantitatively assessed by sustainability indicators compared to a target stock. Second, we derive proxy variables for ecosystem services (e.g. biomass for carbon sequestration, leaf area for deposition and shading) from a given distribution of the number of trees per age class. Third, we show by scenario analyses how selected ecosystem services and functions may be improved by combining complementary tree species. We exercise one aspect (cooling) of one ecosystem service (temperature mitigation) as an example. The approach integrates mosaic pieces of knowledge about urban trees, their structures, functions, and resulting ecosystem services. The presented model makes this knowledge available for a sustainable management of urban tree stocks. We discuss the potential and relevance of the developed concept and model for ecologically and economically sustainable planning and management, in view of progressing urbanization and environmental changes.

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Urban tree analysis using unmanned aerial vehicle (uav) images and object-based classification (case study: university of indonesia campus)

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/683/1/012105 ◽

2021 ◽

Vol 683 (1) ◽

pp. 012105

Author(s):

A Wicaksono ◽

R Hernina

Keyword(s):

Unmanned Aerial Vehicle ◽

Tree Analysis ◽

Urban Tree ◽

Object Based ◽

Aerial Vehicle ◽

Uav Images

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Linking Urban Tree Cover Change and Local History in a Post-Industrial City

Land ◽

10.3390/land10040403 ◽

2021 ◽

Vol 10 (4) ◽

pp. 403

Author(s):

Lara A. Roman ◽

Indigo J. Catton ◽

Eric J. Greenfield ◽

Hamil Pearsall ◽

Theodore S. Eisenman ◽

...

Keyword(s):

Land Cover ◽

Low Income ◽

Historical Context ◽

Local History ◽

Tree Canopy ◽

Tree Cover ◽

Open Spaces ◽

Urban Tree ◽

Suburban Areas ◽

Post Industrial

Municipal leaders are pursuing ambitious goals to increase urban tree canopy (UTC), but there is little understanding of the pace and socioecological drivers of UTC change. We analyzed land cover change in Philadelphia, Pennsylvania (United States) from 1970–2010 to examine the impacts of post-industrial processes on UTC. We interpreted land cover classes using aerial imagery and assessed historical context using archival newspapers, agency reports, and local historical scholarship. There was a citywide UTC increase of +4.3 percentage points. Substantial UTC gains occurred in protected open spaces related to both purposeful planting and unintentional forest emergence due to lack of maintenance, with the latter phenomenon well-documented in other cities located in forested biomes. Compared to developed lands, UTC was more persistent in protected open spaces. Some neighborhoods experienced substantial UTC gains, including quasi-suburban areas and depopulated low-income communities; the latter also experienced decreasing building cover. We identified key processes that drove UTC increases, and which imposed legacies on current UTC patterns: urban renewal, urban greening initiatives, quasi-suburban developments, and (dis)investments in parks. Our study demonstrates the socioecological dynamism of intra-city land cover changes at multi-decadal time scales and the crucial role of local historical context in the interpretation of UTC change.

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A TIMBER Framework for Mining Urban Tree Inventories Using Remote Sensing Datasets

2018 IEEE International Conference on Data Mining (ICDM) ◽

10.1109/icdm.2018.00183 ◽

2018 ◽

Cited By ~ 7

Author(s):

Yiqun Xie ◽

Han Bao ◽

Shashi Shekhar ◽

Joseph Knight

Keyword(s):

Remote Sensing ◽

Urban Tree

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Assessing the conservation status, biodiversity potentials and economic contribution of urban tree Ecosystems in Nigerian Cities

Urban Ecosystems ◽

10.1007/s11252-021-01137-z ◽

2021 ◽

Author(s):

Aladesanmi Daniel Agbelade ◽

Jonathan Chukwujekwu Onyekwelu ◽

Adebayo Adeleke John ◽

Johnson Adedayo ◽

Tunrayo Alabi

Keyword(s):

Conservation Status ◽

Urban Tree ◽

Economic Contribution

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Mapping the Urban Atmospheric Carbon Stock by LiDAR and WorldView-3 Data

Forests ◽

10.3390/f12060692 ◽

2021 ◽

Vol 12 (6) ◽

pp. 692

Author(s):

MD Abdul Mueed Choudhury ◽

Ernesto Marcheggiani ◽

Andrea Galli ◽

Giuseppe Modica ◽

Ben Somers

Keyword(s):

Remote Sensing ◽

Urban Area ◽

Tree Species ◽

Carbon Stock ◽

Dominant Species ◽

Remote Sensing Data ◽

Data Sources ◽

Lidar Data ◽

Urban Tree ◽

Sensing Data

Currently, the worsening impacts of urbanizations have been impelled to the importance of monitoring and management of existing urban trees, securing sustainable use of the available green spaces. Urban tree species identification and evaluation of their roles in atmospheric Carbon Stock (CS) are still among the prime concerns for city planners regarding initiating a convenient and easily adaptive urban green planning and management system. A detailed methodology on the urban tree carbon stock calibration and mapping was conducted in the urban area of Brussels, Belgium. A comparative analysis of the mapping outcomes was assessed to define the convenience and efficiency of two different remote sensing data sources, Light Detection and Ranging (LiDAR) and WorldView-3 (WV-3), in a unique urban area. The mapping results were validated against field estimated carbon stocks. At the initial stage, dominant tree species were identified and classified using the high-resolution WorldView3 image, leading to the final carbon stock mapping based on the dominant species. An object-based image analysis approach was employed to attain an overall accuracy (OA) of 71% during the classification of the dominant species. The field estimations of carbon stock for each plot were done utilizing an allometric model based on the field tree dendrometric data. Later based on the correlation among the field data and the variables (i.e., Normalized Difference Vegetation Index, NDVI and Crown Height Model, CHM) extracted from the available remote sensing data, the carbon stock mapping and validation had been done in a GIS environment. The calibrated NDVI and CHM had been used to compute possible carbon stock in either case of the WV-3 image and LiDAR data, respectively. A comparative discussion has been introduced to bring out the issues, especially for the developing countries, where WV-3 data could be a better solution over the hardly available LiDAR data. This study could assist city planners in understanding and deciding the applicability of remote sensing data sources based on their availability and the level of expediency, ensuring a sustainable urban green management system.

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