Dr. Arif UR Rehman | Remote Sensing Awards | Best Researcher Award

Dr. Arif UR Rehman, Aerospace Information Research Institute, CAS, Pakistan

Arif UR Rehman, is a dedicated researcher specializing in Remote Sensing, GIS, and Forestry. He is currently a Research Assistant at the Aerospace Information Research Institute, Chinese Academy of Sciences, in Beijing, China, where he focuses on spatio-temporal remote sensing data acquisition, processing, and developing machine learning-based tools for vegetation mapping. Previously, he worked as a Remote Sensing Analyst at CABI International under an ADB project, contributing to food security by enhancing crop classification techniques. Arif holds a Master’s degree in Forestry from Beijing Forestry University, an MPhil in Remote Sensing and GIS from the University of the Punjab, an MSc in GIS, a PGD in Remote Sensing & GIS, and an MSc in Electronics from the University of Peshawar. His academic research spans diverse topics, including forest classification, afforestation impact assessment, and land surface temperature analysis. With a strong background in scientific publications and GIS-based spatial analysis, he continues to contribute to advancements in remote sensing and environmental monitoring.

Professional Profile:

SCOPUS

Suitability for the Best Researcher Award

Based on the provided information, Arif UR Rehman has a strong academic and research background in Remote Sensing, GIS, and Machine Learning Applications in Forestry and Agriculture. His qualifications and achievements make him a potential candidate for the Best Researcher Award, but there are some aspects to consider:

🎓 Education

📍 Master in Forestry (Professional Degree) (2019 – 2021)

Institution: Beijing Forestry University, China 🇨🇳
Field: Forest Management
Final Grade: A+
Thesis: Feasibility of combining Landsat-8 data with ancillary variables for forest types and land cover classification in mountainous terrains of northern Pakistan

📍 Master of Philosophy (MPhil) in Remote Sensing and GIS (2017 – 2019)

Institution: PUCIT, University of the Punjab, Pakistan 🇵🇰
Field: Remote Sensing & GIS
Final Grade: 72.8%
Thesis: Remote Sensing & GIS application for monitoring and evaluating afforestation impact – A case study of the Billion Tree Tsunami Project in Peshawar, Pakistan 🌳

📍 Master of Science (MSc) in Geographic Information System (GIS) (2015 – 2017)

Institution: PUCIT, University of the Punjab, Pakistan 🇵🇰
Field: GIS
Final Grade: 73.2%
Thesis: Analyzing the impacts of deforestation on Land Surface Temperature in Northern Pakistan 🌍🌡️

📍 Post Graduate Diploma (PGD) in Remote Sensing & GIS (2014 – 2015)

Institution: NCE in Geology, University of Peshawar, Pakistan 🇵🇰
Field: GIS & Remote Sensing
Final Grade: 73%
Thesis: Spatial-Temporal assessment of Land-Use and Land-Cover changes in Lahore 🏙️

📍 Master of Science (MSc) in Electronics (2013 – 2015)

Institution: University of Peshawar, Pakistan 🇵🇰
Field: Electronics
Final Grade: 64%
Thesis: Developing Hardware & Android software for Outdoor Advertisement Display 📱💡

🏢 Work Experience

🔹 Research Assistant (Feb 2023 – Aug 2024)

Institution: Aerospace Information Research Institute, Chinese Academy of Sciences 🇨🇳
Location: Beijing, China
Key Responsibilities:
- Spatio-Temporal Remote Sensing data acquisition & processing 🛰️
- Developing Machine Learning-based tools for vegetation mapping 🌿🤖
- Scientific Publications 📚

🔹 Remote Sensing Analyst (Jun 2022 – Dec 2022)

Organization: CABI International; ADB Project: Strengthening Food Security 🇵🇰
Location: National Agricultural Research Centre (NARC), Islamabad
Key Responsibilities:
- Capacity development of the Crop Reporting Service Department 🌾
- Google Earth Engine for Crop Classification 🛰️
- Seasonal Crop Classification Maps 📊

🏆 Achievements & Contributions

✔ Published multiple scientific papers in Remote Sensing, GIS, and Forestry journals 📄🔬
✔ Expertise in Google Earth Engine, Machine Learning, GIS & Remote Sensing, and Crop Mapping 🌍🌾
✔ Significant contributions to afforestation projects (Billion Tree Tsunami) 🌳✅
✔ Developed ML-based tools for vegetation mapping and land cover classification 🤖🌎

🎖 Awards & Honors

🏅 A+ Grade in Master’s at Beijing Forestry University (Highest distinction)
🏅 Recognized for contributions to afforestation monitoring in Pakistan 🌲
🏅 Key researcher in major GIS & Remote Sensing projects 📊

Publication Top Notes:

Removal of environmental influences for estimating soil texture fractions based on ZY1 satellite hyperspectral images

Multi-Temporal Sentinel-1 and Sentinel-2 Data for Orchards Discrimination in Khairpur District, Pakistan Using Spectral Separability Analysis and Machine Learning Classification

Estimation of above-ground biomass in dry temperate forests using Sentinel-2 data and random forest: a case study of the Swat area of Pakistan

The role of random forest and Markov chain models in understanding metropolitan urban growth trajectory

Large Scale Fish Images Classification and Localization using Transfer Learning and Localization Aware CNN Architecture

Combining Landsat-8 spectral bands with ancillary variables for land cover classification in mountainous terrains of northern Pakistan

Comparing different space-borne sensors and methods for the retrieval of land surface temperature

Efstratios Karantanellis | Remote Sensing | Best Researcher Award

Dr. Efstratios Karantanellis, University of Michigan-Ann Arbor, United States.

Dr. Efstratios Karantanellis is a research fellow in the Department of Earth and Environmental Sciences at the University of Michigan, specializing in natural hazards, engineering geology, and landslide analysis. He obtained his PhD from Aristotle University of Thessaloniki in 2022 and has collaborated on various projects focused on disaster risk reduction and response, utilizing remote sensing and object-based image analysis (OBIA). Efstratios has extensive experience in hazard assessment and mitigation planning, contributing to research in Greece and internationally. He has been recognized with multiple awards for his contributions to the field.

Publication Profiles

Googlescholar

Education and Experience

PhD, Aristotle University of Thessaloniki, Greece (2022)
MSc, University of Twente, ITC, Netherlands (2015)
BSc, Aristotle University of Thessaloniki, Greece (2013)
Research Fellow, University of Michigan, Ann Arbor, USA (2022 – ongoing)
Visiting Researcher, University of California, Berkeley, USA (2024)
Research Associate, various projects in Greece (2020 – 2023)

Suitability For The Award

Dr. Efstratios Karantanellis is an outstanding candidate for the Best Researcher Award, recognized for his exceptional contributions to geosciences, specifically in the field of disaster risk reduction and environmental management. His extensive educational background, including a PhD from Aristotle University of Thessaloniki and ongoing research at the University of Michigan, equips him with a robust foundation in both theoretical and applied aspects of his discipline.

Professional Development

Dr. Efstratios Karantanellis has actively participated in numerous research projects, enhancing his expertise in engineering geology and disaster risk management. He contributed to the Center for Land Surface Hazards (CLaSH) as part of the U.S. National Science Foundation. His research includes developing tools for landslide disaster risk reduction and coastal zone monitoring systems. By collaborating with interdisciplinary teams, he has leveraged interoperable technologies to support infrastructure resilience. Through his extensive work, Efstratios has made significant contributions to natural hazards research and continues to advance knowledge in this critical field.

Research Focus

Dr. Efstratios Karantanellis focuses on natural hazards, particularly landslide engineering geology and risk management. His research incorporates remote sensing techniques and object-based image analysis (OBIA) to assess and mitigate the impacts of landslides and other geological hazards. He emphasizes disaster risk reduction throughout the disaster life cycle, utilizing innovative methodologies to support effective response and recovery strategies. His work aims to enhance resilience in vulnerable regions, contributing to safer and more sustainable communities.

Awards and Honors

Richard Wolters Prize, International Association for Engineering Geology and the Environment (2024, Runner-up)
Early Career Research Award of Excellence, Faculty of Natural Sciences, Aristotle University of Thessaloniki (2022)
Postdoctoral Fellowship, NASA’s Applied Science Disasters Program (2022)
Research Grant, co-financed by Greece and the EU (MIS-5000432)
ISPRS Foundation Travel Grant, 2019
EuroSDR GeoInformation Travel Grant, 2018

Publication Top Notes

Object-based analysis using UAVs for site-specific landslide assessment – Remote Sensing, 2020, Cited by: 72
Satellite imagery for rapid detection of liquefaction surface manifestations: Türkiye–Syria 2023 Earthquakes – Remote Sensing, 2023, Cited by: 32
Automated 3D jointed rock mass structural analysis using LiDAR for rockfall susceptibility – Geotechnical and Geological Engineering, 2020, Cited by: 29
Evaluation of machine learning algorithms for object-based mapping of landslide zones using UAV data – Geosciences, 2021, Cited by: 26
3D hazard analysis and object-based characterization of landslide motion using UAV imagery – International Archives of Photogrammetry and Remote Sensing, 2019, Cited by: 20
The September 18-20 2020 Medicane Ianos Impact on Greece: Phase I Reconnaissance Report – GEER Association, 2020, Cited by: 19