Automated mapping and spatial analysis o ...
2018 | Benoit St-Onge, PhD, University of Quebec at Montreal, Canada
Urban forests have both positive and adverse effects on human well-being, while their sustainability, given climate change and invasive species, is at risk. Setting targets for key attributes such as optimal tree density, age/size distribution, species variety, in this context will thus require precise data on public and private trees. Tree detection performed using airborne LIDAR 3D models can provide information on the size of most urban trees, and can also identify species or species groups with a good accuracy. We propose to test these methods on existing LIDAR data for the City of Montreal, used as a case study representative of North American cities, and derive the above-mentioned key attributes. From these we will produce indicators at the neighborhood level for the entire island of Montreal (500 km2) such as: local density and height of trees, species biodiversity, etc. The overarching goal is to develop methods for characterizing a) individual trees and b) features of the urban forest at the neighborhood level.
This project will be carried out in close collaboration with the City of Montreal, Canada. Having started to work on the above goals with them in 2018, but without external funding, the foundations of the proposed project are already laid out. Because the software tools will have be delivered and explained to the personnel of the City of Montreal at the end of the project, the City’s personnel will be autonomous for applying the methods as soon as 2019, as well as in the future, such that updating the data outputs will be possible. These outputs, i.e. a map of all individual trees visible from the air (both public and private) and their attributes and species, as well as maps of neighborhood level indicators, will help guide the City of Montreal in decisions for creating an urban forest that has a positive impact of human health and well-being, and that is more resilient to climate change and invasive insect species. The results will be disseminated at three levels: at the City of Montreal itself (one-day workshop), at the regional level (during a presentation at a conference attended by municipal actors from the entire province of Quebec, Canada), and internationally (during a presentation at one conference in the U.S.A., and in a paper in one international journal). Based on Montreal’s case, we hope that the adoption the proposed approach and related technology by other municipalities will be facilitated.
For more information on this project, contact the researcher via TREE Fund at treefund@treefund.org.
