Shabnam Jabari

Dr. Shabnam Jabari is an Associate Professor at the department of geodesy and geomatics engineering, University of New Brunswick (UNB).

She has received her PhD from UNB, working on 3D Information Supported Urban Change Detection using Multi-Angle and Multi-Sensor Imagery in 2015, which resulted in a commercialized patented technology. She received her MSc and BSc in Civil-Surveying Engineering in 2009 and 2005, respectively, from the University of Tehran.

Dr. Jabari's current research interests include 3D city models, 3D GIS, urban area change detection, multi-modal mapping. She focuses her research on the application of Geospatial Data for Disaster Management, especially for damage detection and flood mapping in urban areas.

Dr. Jabari's research outcomes have been recognized by different organizations, including the Canada Foundation for Innovation (CFI), as one of Canada's top innovative projects in the innovation campaign of 2018, University of New Brunswick (UNB), as one of the seven novel projects of 2017 (UNB 2017 Annual Report), and NSERC.

Dr. Jabari is an active member of the Canadian Remote Sensing Society (CRSS-SCT). She has served the CRSS-SCT as a secretary since 2020 and the chair of working group 3 since 2021. She is also a member of working group 4 of CRSS-SCT. Dr. Jabari is an active member of the ISPRS congress bid task force and the technical committee of ICAG-CSRS 2022 conference - Quebec. She is also the vice president of the Canadian Institute of Geomatics and a licensed member (PEng) of Professional Engineers and Geoscientists of New Brunswick (APEGNB). Additionally, she is a member of the American Society for Photogrammetry and Remote Sensing (ASPRS), IEEE and IEEE Geoscience and Remote Sensing Society (GRSS).

Dr. Jabari has taught different courses in GIS (GGE 3342, GGE 4423, GGE 6410/5410), Remote Sensing (GGE 3342) and Photogrammetry (GGE4313). She also has taught different courses as a co-instructor/mentor (GGE1001, GGE6322/5322, GGE4700, GGE 6900).

Media reports on research success

• CBC New Brunswick: “Satellite images could allow homeowners to check on homes during the next big flood”.
• Federal Budget Justification 2018
• Parliament Hill Event: “Parliamentarians celebrate new generation of Canadian researchers”.
• UNB 2017 Annual Report
• The Globe and Mail: "Helping Rescuers Save More Lives”.
• Canada Foundation Innovation: “Helping rescuers save more lives”.
• UNB Research Matters: “New research to help in response to natural disaster relief”.
• Radio Canada International: “New research to help in response to natural disaster relief and more”.
• Telegraph Journal: “Game-changing’ tech aims to aid disaster relief”.
• UNB News Room: “New technology at the UNB changing the face of disaster relief”.
• CBC New Brunswick: “3D images of Nepal to help earthquake relief efforts”.

Selected publications

G. Abdi, S. Jabari, A Multi-Feature Fusion Using Deep Transfer Learning for Earthquake Building Damage Detection, Canadian Journal of Remote Sensing, 1-16, 2021

M. Esfandiari, G. Abdi, S. Jabari, H. McGrath, D. Coleman, Flood hazard risk mapping using a pseudo supervised random forest, Remote Sensing, V 12- 19, 2020

S. Jabari, M. Rezaie, F. Fathollahi, Y. Zhang, “Multispectral change detection using multivariate Kullback-Leibler distance”, ISPRS Journal of Photogrammetry and Remote Sensing, 147, 163-177, 2019.

S. Jabari, Y. Zhang, “Urban Change Detection Utilizing High-Resolution Optical Images Taken from Different Viewing Angles and Different Platforms”, Urban Remote Sensing (second edition), P. Weng, Qihao; Quattrochi, Dale; Gamba, Ed. CRC Press, 2018, pp. 125–148

S. Jabari, F. Fathollahi, A. Roshan, and Y. Zhang, “Improving UAV imaging quality by optical sensor fusion: an initial study,” Int. J. Remote Sens., vol. 38, no. 17, pp. 4931–4953, 2017.

S. Jabari and Y. Zhang, “Building Change Detection Improvement Using Topographic Correction Models,” Adv. Remote Sens., vol. 6, no. 01, pp. 1–22, 2017.

S. Jabari and Y. Zhang, “RPC-Based Coregistration of VHR Imagery for Urban Change Detection,” Photogramm. Eng. Remote Sens., vol. 82, no. 7, pp. 521–534, 2016.

Patent

• Method and system of coregistration of remote sensing images

For the full list of publications, see ResearchGate and Google Scholar.