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Institution

Esri (Canada)

CompanyToronto, Ontario, 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.

Papers
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Book ChapterDOI
R. K. Jones1
01 Jan 1994
TL;DR: The need for a greater understanding of the ecological nature of the forest is being driven by a number of environmental, economic, and socio-political factors as mentioned in this paper, which are increasingly being affected by the state of their knowledge about ecological conditions characterizing their land base and how these conditions influence land use, resource planning, and business decisions.
Abstract: Organizations involved in natural resource management are increasingly being affected by the state of their knowledge about ecological conditions characterizing their land base and how these conditions influence land use, resource planning, and business decisions. This need for a greater understanding of the ecological nature of the forest is being driven by a number of environmental, economic, and socio-political factors. Forest management is now really forestland management, in the broadest sense of the word “land”. With this changing outlook, we are seeing an emergence of more ecological management approaches which are better able to accomodate non-timber values, anticipate and mitigate environmental impacts of forest operations, and which are beginning to address the principles of sustainable development and integrated resource management.

5 citations

Book ChapterDOI
01 Jan 2012
TL;DR: In this paper, the authors focus on the status of Geographic Information System (GIS) in the secondary schools of Canada and discuss when and what geography is taught in the elementary through to the high school system.
Abstract: In this chapter, we focus on the status of Geographic Information System (GIS) in the secondary schools of Canada. We first discuss when and what geography is taught in the elementary through to the high school system. This is followed by a description of GIS education in the country, supported by exemplary applications of GIS in the classroom. The chapter concludes with a summary of obstacles most commonly encountered by GIS educators in schools as well as an optimistic outlook for the future.

3 citations

Proceedings Article
29 Oct 2018
TL;DR: Solving transportation and transit challenges requires integrating transdisciplinary knowledge, including computer science, engineering into city planning, and the melding of machine learning, simulations, predictive analytics and design create capacity and connectivity that will help policy and makers gain insight into complex decision-making processes.
Abstract: Providing efficient, cost-effective, sustainable transportation networks and services is a major challenge for cities around the world not only for individual cities, but for connectivity between cities. High quality transportation services, notably well-designed transit hubs within comprehensive networks are fundamental prerequisites for effective cities and spur economic, social and cultural inclusion, development and growth. Transportation strategies must be at the heart of smart city strategies. The melding of machine learning, simulations, predictive analytics and design create capacity and connectivity that will help policy and makers gain insight into complex decision-making processes and support evidence-based decision making. Solving transportation and transit challenges requires integrating transdisciplinary knowledge, including computer science, engineering into city planning.

1 citations

Proceedings ArticleDOI
07 May 2006
TL;DR: A novel architecture and requirements for integrating NMS and GIS (geographic information systems) technology to address issues such as the one mentioned above are proposed and a prototype system was developed to validate the architecture.
Abstract: Advanced network management systems (NMS) have made tremendous strides in terms of visualization, monitoring, and vulnerability analysis for Layer 2 and Layer 3 data networks. However, they are unable to take into account geographic considerations and vulnerability of the network to physical threats and hazards. This paper summarizes our recent work on utilizing geospatial mapping and technology for improving network infrastructure security. We propose a novel architecture and requirements for integrating NMS and GIS (geographic information systems) technology to address issues such as the one mentioned above. A prototype system was developed to validate the architecture. We conclude the paper with a discussion of challenges encountered during development and testing of the prototype on an emulation test-bed

1 citations

Posted ContentDOI
15 May 2023
TL;DR: In this article , the authors used a neural network approach to interpolate sparse observations, creating a monthly gridded seawater partial pressure of CO2 (pCO2) data product from January 1998 to December 2019, at 1/12° × 1/ 12° spatial resolution, in the Northeast Pacific open ocean.
Abstract: Abstract. The global ocean takes up nearly a quarter of anthropogenic CO2 emissions annually, but the variability of this uptake at regional scales remains poorly understood. Here we use a neural network approach to interpolate sparse observations, creating a monthly gridded seawater partial pressure of CO2 (pCO2) data product from January 1998 to December 2019, at 1/12° × 1/12° spatial resolution, in the Northeast Pacific open ocean. The data product (ANN-NEP; NCEI Record ID: BGSH2HNRP) was created from pCO2 observations within the 2021 version of the Surface Ocean CO2 Atlas (SOCAT), and a range of predictor variables acting as proxies for processes affecting pCO2 to create non-linear relationships to interpolate observations at a spatial resolution four times greater than leading global products and with better overall performance. In moving to a higher resolution, we show that the internal division of training data is the most important parameter for reducing overfitting. Using our pCO2 product, wind speed, and atmospheric CO2, we evaluate air-sea CO2 flux variability. On sub-decadal to decadal timescales, we find that the upwelling strength of the subpolar Alaskan Gyre, driven by large-scale atmospheric forcing, acts as the primary control on air-sea CO2 flux variability (r2 = 0.93, p < 0.01). In the northern part of our study region, divergence with atmospheric CO2 is enhanced by increased local wind stress curl, enhancing upwelling and entrainment of naturally CO2-rich subsurface waters, leading to decade-long intervals of strong winter outgassing. During recent Pacific marine heatwaves from 2013 on, we find enhanced atmospheric CO2 uptake (by as much as 45 %) due to limited wintertime entrainment. Our product estimates long-term surface ocean pCO2 increase at a rate below the atmospheric trend (1.4 ± 0.1 μatm yr−1) with the slowest increase in the center of the subpolar gyre where there is strong interaction with subsurface waters. This mismatch suggests the Northeast Pacific Ocean sink for atmospheric CO2 may be increasing.

Network Information
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20231
20212
20203
20193
20182
20171