Esri (Canada)

About: Esri (Canada) is a company organization based out in Toronto, Ontario, Canada. It is known for research contribution in the topics: Geographic information system & Smart city. The organization has 20 authors who have published 19 publications receiving 140 citations. The organization is also known as: Environmental Systems Research Institute.

The Early Detection of the Emerald Ash Borer (EAB) Using Advanced Geospacial Technologies

Abstract: The objectives of this study were to exploit Light Detection And Ranging (LiDAR) and very high spatial resolution (VHR) data and their synergy with hyperspectral imagery in the early detection of the EAB presence in trees within urban areas and to develop a framework to combine information extracted from multiple data sources. To achieve these, an object-oriented framework was developed to combine information derived from available data sets to characterize ash trees. Within this framework, individual trees were first extracted and then classified into different species based on their spectral information derived from hyperspectral imagery, spatial information from VHR imagery, and for each ash tree its health state and EAB infestation stage were determined based on hyperspectral imagery. The developed framework and methods were demonstrated to be effective according to the results obtained on two study sites in the city of Toronto, Ontario Canada. The individual tree delineation method provided satisfactory results with an overall accuracy of 78 % and 19 % commission and 23 % omission errors when used on the combined very high-spatial resolution imagery and LiDAR data. In terms of the identification of ash trees, given sufficient representative training data, our classification model was able to predict tree species with above 75 % overall accuracy, and mis-classification occurred mainly between ash and maple trees. The hypothesis that a strong correlation exists between general tree stress and EAB infestation was confirmed. Vegetation indices sensitive to leaf chlorophyll content derived from hyperspectral imagery can be used to predict the EAB infestation levels for each ash tree.

Iterative ‘what-if’ neighborhood simulation: energy and emissions impacts

Abstract: As efforts to address climate change shift to action at local scales, municipalities are called upon to develop locally specific action plans. Many municipalities lack the resources to develop energy and emissions-reducing policy interventions appropriate to their characteristics. This research synthesises urban form, scenario analysis and energy simulation into a cohesive workflow for evaluating energy and emissions policy interventions across a range of urban forms. A geospatial and census analysis of six cities across British Columbia, Canada, led to the development of seven urban neighborhood patterns. These represent neighborhood forms and densities found in cities of various sizes, densities, forms and climates. To test the approach of an urban built environment model (UBEM), retrofit and infill redevelopment ‘what-if’ scenarios were applied iteratively to two sample patterns comparing the relative efficacy of building technology-improvement policies versus land-use intensification policies. The future ‘what-if’ policy scenarios were spatially tested and validated using relevant policy. The simplified UBEM methods applied to typical patterns and development demonstrates a step towards an accessible and flexible modeling approach. Small and medium-sized municipalities can use this approach to assess and compare potential energy and emissions policy options and outcomes at building and neighborhood scales. Practice relevance A new, simple method has been created for municipalities to understand multiple ‘what-if’ scenarios for reducing energy demand and emissions from buildings. This is based on profiles from census data, geospatial analysis and energy data that characterise urban neighborhood patterns. The approach integrates building-scale and neighborhood-scale energy and greenhouse gas simulations. It can simulate a variety of policy scenarios and strategy interventions in order to show the interactions between and among urban form and retrofit options. This enables planners and decision-makers to compare the relative magnitudes of different interventions at the neighborhood or city level for energy and emissions performance. The model was developed for use by a variety of communities in British Columbia, Canada. There is potential for adapting this method for use in other locations.