This July, Dr. Maryam Robati, starts her one-year visiting scholarship at York and EUC Research Assistant, Igor Lutay, interviews her on her plans for engagement and research at the Faculty.
Q. Why did you apply for visiting scholarship at EUC and what research do you plan to do at York University?
A. I am interested in pursuing my research work at York and experiencing its teaching environment. I chose York University because of its high research ranking in the world I am interested in joining the EUC as a visiting scholar, which would bring me more experience and knowledge in addressing some of the challenges we are facing now. Specifically, I have been inspired by the following research project (climate change crisis) at EUC which are also aligned with my current research studies. I am enthusiastic to spend an academic year at EUC as visiting research scholar. I want to thank EUC, specifically Prof. Jose Etcheverry for giving me the chance to do my research here and to work with him in further studying the field of climate change and sustainability. During my period of research work at York University, I plan to expand my knowledge, improve my work and make new connections with experts from other Faculties.
Q. What can you tell me about your current work? Are there any challenges that you foresee in doing your research work at York?
A. I work as an Assistant Professor in the Science and Research Branch, IAU, Iran. I teach Environmental Science and Urban Planning courses in the university. When someone is a newcomer to a new place or country, the main challenge is the new culture as well as finding research or teaching work opportunities. Nonetheless, I am adapting to the new culture and ways of doing things.
Q. What kind of impact do you anticipate your work will have in your field of research?
A. Climate change is very crucial at this time to all of the world. We want to achieve pragmatic solutions and desired outcome for climate change adaptation in urban areas. We co-authored an article on Urban Resilience Assessment Using Hybrid MCDM Model Based on DEMATEL-ANP Method (DANP) (JISRS, 2023) and the research provided new perspectives to help urban planners understand the causal relationship between dimensions (environmental, socioeconomic, physical and institutional) and criteria (disasters and natural disasters, water resources, environmental pollution, topography, urban infrastructure, land use, green space, employment rate, population and education, health status, and insurance coverage) to better understand resilience.
Q, What topics are you most passionate about researching in the future?
A. I believe that we should go beyond net zero emission and target absolute zero carbon. I know that Canada's vision up to 2050 is achieving net zero in industries which is why it is also my passion to research more about net zero and carbon reduction. We have also co-published a paper on analyzing Land subsidence hazard assessment based on novel hybrid approach: BWM, weighted overlay index (WOI), and support vector machine (SVM) (Natural Hazards, 2023). In this study, we evaluate the efficiency of the support vector machine (SVM) algorithm and weighted overlay index (WOI) models in zoning the rate of land subsidence hazard in Hashtgerd plain, Iran. First, the 19 criteria include groundwater depletion, groundwater extraction, aquifer thickness, alluvium thickness, aquifer recharge, well density, drainage density, groundwater depth, lithology, bedrock depth, average annual precipitation, average annual temperature, climate type, agricultural use, urban use, industrial use, distance from rivers and streams, distance from roads, distance from faults were considered. Then, the layers were weighed based on the Best–Worst Method (BWM). Therefore, all of the models used here can predict the areas vulnerable to subsidence properly. The results of this study can help planners in managing and reducing the possible hazards of subsidence.
Q. What other aspects are you passionate about in your research work?
A. I want to develop a holistic model to provide an effective, useful and tangible measure towards reducing the effects of climate change by emphasizing urban resilience and sustainability. We co-authored an article on Urban Resilience and Climate Change: Developing a Multidimensional Index to Adapt against Climate Change in the Iranian Capital City of Tehran (Urban Science, 2023). In this research, we sought to enhance the understanding of climate resilience in the metropolitan area of Tehran in the absence of enrolling a sweeping framework. Thus, a tangible approach equipped with GIS was adopted to outline and illustrate the resilience hotspots over the 22 municipal districts in Tehran. Interpreting the EFA results coupled with CRI classification and functional zoning gave more insight than applying a simple subjective MCDM method. The repetitiousness of the proposed multidimensional metric was regarded as the other concern following its applicability in varied scales.
Q. Finally, what motivated you to start doing work in this field?
A. I have been working in this field for about three years and climate change topic is very important. My work now relates to my past research in the field of urban resilience and urban sustainability. In the last couple of years, this topic has become increasingly important and I want to make a relationship study between climate change and urban issues. I found that this topic encompasses current issues in ecosystem management and I want to contribute to providing solutions for future issues around climate change and urban sustainability. Most people are now living in urban areas with more than 85% of them residing in large cities and this number is expected to go up in the next 20 years.
Dr. Maryam Robati is a visiting scholar at York University and supervised by Professor Jose Etcheverry. She is an Assistant Professor in Environmental Science and Engineering at IAU, Science and Research Branch with special interest in sustainability research. She has carried out works on urban resiliency and climate change and has also worked on Machine Learning and multi decision making approaches using MATLAB .