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Vancouver urban trees

Compendium of Best Urban Forest Management Practices

Chapter 7. GIS and Other Technologies


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GIS and Other Technologies

Technologies like Geographic Information Systems, LIDAR, apps, and data management software are increasingly used in urban forest management. The potential for mapping trees has many implications for forest management and education; vector and raster techniques can be used in the digital representation of the geographic data to display and analyze various attributes based on specific objectives (e.g. being able to generate a map displaying underground and overhead infrastructure with elevation data for a proposed planting site; or, coupled with tree inventory data, being able to model sun angle diagrams in relation to existing vegetation or buildings to increase shade provision at a given site, etc.). Other technologies include more sophisticated equipment, hardware and software for dendrology, soil and tree core sampling, leaf area and crown density monitoring, geographic positioning systems (GPS), etc. With progress in technology, the benefit to having access to such tools can prove to be more time efficient and effective in management planning.

Free and public domain technologies for urban forestry:

Canadian online resources:

Non-Canadian online resources:

Further reading:

Alonzo, M., McFadden, J. P., Nowak, D. J., & Roberts, D. A. (2016). Mapping urban forest structure and function using hyperspectral imagery and lidar data. Urban Forestry & Urban Greening, 17, 135-147. https://doi.org/10.1016/j.ufug.2016.04.003

Feghhi, J., Teimouri, S., Makhdoum, M. F., Erfanifard, Y., & Abbaszadeh Tehrani, N. (2017). The assessment of degradation to sustainability in an urban forest ecosystem by GIS. Urban Forestry & Urban Greening, 27, 383-389. https://doi.org/10.1016/j.ufug.2017.06.009

Singh, K. K., Chen, G., McCarter, J. B., & Meentemeyer, R. K. (2015). Effects of LiDAR point density and landscape context on estimates of urban forest biomass. ISPRS Journal of Photogrammetry and Remote Sensing, 101, 310-322. https://doi.org/10.1016/j.isprsjprs.2014.12.021

Zhang, C., Zhou, Y., & Qiu, F. (2015). Individual Tree Segmentation from LiDAR Point Clouds for Urban Forest Inventory. Remote Sensing, 7(6), 7892-7913. doi:10.3390/rs70607892

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