AI in the Service of Socio-Politically Adapted Sustainable Dust-Storm Control in the Middle East
Funding Agency: SRA-MECW. Duration: 2021-2024
The goals of this interdisciplinary project are to identify the climate- and human-induced sources of dust and to determine and explain the factors affecting the dust-source areas such as climate variation, land-use change, social, political, and economic drivers, and water management in time and space using remote sensing and artificial intelligence techniques. It will use agent-based models to simulate possible solutions to control and/or reduce dust-storms in the Middle East (ME) considering the impacts of proposed solutions from social, political, economic, and environmental perspectives.
The Middle East, which is experiencing severe environmental challenges such as dust-storms, is most vulnerable to climate and human-induced environmental changes. This interdisciplinary research project will run for three years. To consider environmental, socio-political, and economic aspects of dust-storm generation and control policy, the project involves expertise from engineering, science, and social sciences faculties of Lund University. The outcome enhances the ability of the policymakers and practitioners for environmental protection, sustainability, and resilience in the ME.
To consider environmental, socio-political, and economic aspects of dust-storm generation and control policy, the project involves expertise from engineering, science, and social sciences faculties of Lund University. By creating a consortium of researchers from different disciplines, apart from ensuring excellent science, we intend to generate a new multi/interdisciplinary research environment at Lund University.
Overall, the study’s objectives are projected to fill the stated gaps as follows:
- Spatiotemporal analysis of dust-storm sources, together with dust-source vulnerability mapping to identify new potential sources.
- Investigating the impact of climate change and conflicts, i.e., ISIS invasion, and water management, i.e., Iran and Turkey’s dam projects, on the frequency/intensity of dust-storms by investigating the spatiotemporal dust-storm dataset.
- Describing driving forces of dust-storm and identifying the external environmental and socio-political key factors.
- Providing strategies to control and/or decrease dust-storms in the region by analyzing social- political-economic and environmental impacts of possible solutions to achieve sustainability and resilience.
Boroughani, M., Hashemi, H., Hosseini, S.H., Pourhashemi, S. and Berndtsson, R.. (2019). "Desiccating Lake Urmia: a new dust source of regional importance". IEEE Geoscience and Remote Sensing Letters, 17(9): 1483-1487.
Boroughani, M., Pourhashemi, S., Hashemi, H., Salehi, M., Amirahmadi, A., Asadi, M.A.Z. and Berndtsson, R. (2020). "Application of remote sensing techniques and machine learning algorithms in dust source detection and dust source susceptibility mapping". Ecological Informatics, 56: 101059.
Hossein Hashemi, CMES Researcher and Associate Professor at the Division of Water Resources Engineering (Department of Building and Environmental Technology, Lund University)
hossein [dot] hashemi [at] tvrl [dot] lth [dot] se
Amir Naghibi, CMES Researcher and Postdoctoral Fellow at the Division of Water Resources Engineering (Department of Building and Environmental Technology, Lund University)
seyed_amir [dot] naghibi [at] tvrl [dot] lth [dot] se
Sara Brogaard, CMES Researcher and Senior Lecturer at the Lund University Centre for Sustainability Studies (LUCSUS, Lund University)
sara [dot] brogaard [at] LUCSUS [dot] lu [dot] se
Ali Mansourian, CMES Researcher and Associate Professor at the Department of Physical Geography and Ecosystem Science (Lund University)
ali [dot] mansourian [at] nateko [dot] lu [dot] se
Pengziang Zhao, Researcher at CMES and the Department of Physical Geography and Ecosystem Science (Lund University)
pengxiang [dot] zhao [at] nateko [dot] lu [dot] se