Dr Mohadeseh Amiri | Climate Change | Best Researcher Award
Researcher at Isfahan University of Technology, Iran
Dr. Mohadeseh Amiri holds a Ph.D. in Rangeland Sciences and is affiliated with Isfahan University of Technology (IUT). Her expertise lies in the field of Rangeland Sciences, showcasing a dedication to advancing knowledge in this domain.
🌱 Research Focus:
Mohadeseh Amiri’s research primarily revolves around environmental ecology and remote sensing applications. Her work encompasses a diverse range of topics, including the use of natural fluorophores in chemiluminescence reactions, fuzzy classification for mapping invasive species, spatiotemporal variability of soil moisture in arid vegetation communities, and modeling the biological invasion of Prosopis juliflora under climate change. Additionally, she explores habitat degradation of Ursus arctos using species distribution modeling and remote sensing, as well as predicting desert dust sources through machine learning-driven scenario-based models. Her multifaceted research contributes to a deeper understanding of ecological dynamics and environmental challenges. 🌍🌿📡
- Citations: 55 citations received by the researcher across 54 documents.
- Documents: The researcher has authored 9 documents.
- h-index: The h-index is a metric that reflects both the productivity and impact of a researcher’s work. In this case, the h-index is 4.
The h-index suggests that there are 4 documents that have each been cited at least 4 times. These metrics are commonly used to assess the impact and influence of a researcher’s work in the academic community.
Publications Top Notes:
- “Machine learning-driven scenario-based models for predicting desert dust sources in central playas of Iran”
- Authors: Jafari, R.; Amiri, M.; Jebali, A.
- Journal: Catena, 2024, 234, 107618
- “Comparison of Regression and Machine Learning Techniques in Determination of Geographical Range of Onobrychis cornuta L. Under Environmental Characteristics and Climate Change Using the IPSL-CM6A-LR Model”
- Authors: Jafarian, Z.; Amiri, M.
- Journal: Journal of Environmental Studies, 2023, 49(1), pp. 107–120
- “Dust source susceptibility mapping based on remote sensing and machine learning techniques”
- Authors: Jafari, R.; Amiri, M.; Asgari, F.; Tarkesh, M.
- Journal: Ecological Informatics, 2022, 72, 101872
- “Modelling the biological invasion of Prosopis juliflora using geostatistical-based bioclimatic variables under climate change in arid zones of southwestern Iran”
- Authors: Amiri, M.; Tarkesh, M.; Shafiezadeh, M.
- Journal: Journal of Arid Land, 2022, 14(2), pp. 203–224
- “THE EFFECT OF ENVIRONMENTAL AND HUMAN FACTORS ON THE DISTRIBUTION OF BROWN BEAR (URSUS ARCTOS ISABELLINUS) IN IRAN”
- Authors: Hosseini, S.P.; Amiri, M.; Senn, J.
- Journal: Applied Ecology and Environmental Research, 2022, 20(1), pp. 153–170
These articles cover a diverse range of topics, including machine learning applications, ecological modeling, dust source mapping, and the impact of environmental factors on species distribution. 📚🌍