Mrs. Dinara Talgarbaeva | Remote Sensing | Top Researcher Award

Mrs. Dinara Talgarbaeva | Remote Sensing | Top Researcher Award

Mrs. Dinara Talgarbaeva | Remote Sensing | Institute of Ionosphere | Kazakhstan

Mrs. Dinara Talgarbayeva is an accomplished Senior Researcher at the Institute of Ionosphere, Almaty, Kazakhstan, whose expertise lies in satellite-based geodynamic monitoring, InSAR technology, Sarscape data analysis, and GIS analytics. She holds both a Bachelor’s and a Master’s degree in Geology from Satbayev University, Kazakhstan, where she developed her foundational understanding of geological processes and earth observation systems. Over the course of her career, Mrs. Talgarbayeva has built a solid professional portfolio focused on applying remote sensing techniques to study geological deformations, land subsidence, and mineral exploration. Her research integrates Sentinel-1 SAR data, digital elevation models, and lineament analysis to provide accurate insights into seismic hazards and geodynamic changes in Kazakhstan and other Central Asian regions. As a dedicated scientist, she actively collaborates with multidisciplinary teams and international researchers, contributing to innovative solutions in geodesy, environmental monitoring, and mineral mapping. Her research interests are centered around earth observation, geodynamic zoning, natural hazard detection, and data-driven modeling for sustainable resource management. Mrs. Talgarbayeva possesses advanced research skills in SAR interferometry, GIS processing, multispectral analysis, and automation of geological data interpretation using satellite imagery, enabling her to produce reliable and scalable models for terrain deformation and subsidence assessment. She has demonstrated consistent excellence through her participation in numerous high-impact studies and has published multiple research papers in prestigious peer-reviewed journals such as Minerals, Geomatics, Engineered Science, and Reliability Theory and Applications, all indexed in Scopus and IEEE. These publications reflect her growing academic influence and her ability to translate complex scientific data into actionable insights.

Professional Profile: ORCID | Scopus

Selected Publications 

  1. Talgarbayeva, D., Satbergenova, A., Vilayev, A., Urazaliyev, A., & Yelisseyeva, A. (2025). InSAR-based assessment of land subsidence induced by coal mining in Karaganda, Kazakhstan. Geomatics, 5(4). [Cited by 12]

  2. Talgarbayeva, D., Serikbayeva, E., Orynbassarova, E., & Sydyk, N. (2025). Application of multispectral data in detecting porphyry copper deposits: The case of Aidarly Deposit, Eastern Kazakhstan. Minerals, 15(9). [Cited by 9]

  3. Talgarbayeva, D., Vilayev, A., Serikbayeva, E., & Ahmadi, H. (2025). Integrated prospectivity mapping for copper mineralization in the Koldar Massif, Kazakhstan. Minerals, 15(8). [Cited by 11]

  4. Talgarbayeva, D., Kairanbayeva, A., Nurakynov, S., & Mitkov, A. (2024). Predictive system for road condition monitoring based on open climate and remote sensing data – A case study with mountain roads. Engineered Science, 8(2). [Cited by 7]

  5. Talgarbayeva, D., Fremd, A., & Gaipova, A. (2023). Possibilities of lineament analysis of DEM SRTM during geodynamic zoning of seismic hazardous territories (on the example of the North-Tien-Shan region). Reliability Theory and Applications, 5(75), 96–110. [Cited by 5]

Dr. Adlin Dancheva | Remote Sensing | Best Researcher Award

Dr. Adlin Dancheva | Remote Sensing | Best Researcher Award

Dr. Adlin Dancheva | Remote Sensing | Space Research and Technology Institute-BAS | Bulgaria

Dr. Adlin Dancheva is a distinguished GIS and Remote Sensing specialist with extensive expertise in geospatial analysis, cartography, drone-based imaging, and environmental monitoring. She is currently pursuing her Ph.D. at the Bulgarian Academy of Sciences, Space Research and Technology Institute (SRTI), focusing on aerospace information and remote sensing for environmental and infrastructure applications. She holds a Master’s degree in GIS and Cartography from Sofia University St. Kliment Ohridski and a Bachelor’s degree in Geography from Veliko Tarnovo University St. Cyril and St. Methodius. Dr. Adlin Dancheva has developed a strong professional portfolio through her work as a GIS Analyst at Megatron EAD (Bulgaria) / Terrascan Labs (Israel), where she processes and analyzes aerial mapping projects, interprets drone and satellite data, and generates soil sampling and topographical maps. She has also served as a GIS and Cartography Expert at the Road Infrastructure Agency – National Toll Administration and Agritask, Israel, applying advanced spatial data analysis, digital map design, shapefile creation, and data visualization to support environmental and infrastructure projects. Her contributions have garnered attention internationally, reflected in 13 publications, 31 citations, and an h-index of 3, demonstrating a strong and growing influence in battery research.

Professional Profile: Scopus

Selected Publications 

  1. Dancheva, A., & colleagues. (2025). Citric acid as electrolyte additive in aqueous magnesium-air battery used in Antarctic climate. Electrochimica Acta. (8 citations)

Mr. Faruk Hossain | Remote Sensing | Best Researcher Award

Mr. Faruk Hossain | Remote Sensing | Best Researcher Award 

Mr. Faruk Hossain | Geological Survey of Bangladesh | Bangladesh

Faruk Hossain is a highly accomplished geoscientist and Assistant Director (Geology) at the Geological Survey of Bangladesh, specializing in fluvial and tectonic geomorphology, active fault identification, and 3D subsurface geological modeling. With a deep commitment to advancing geoscience research, he integrates field investigations, laboratory analysis, and advanced geospatial technologies to address pressing geological and environmental challenges. His expertise extends to geohazard assessment, seismic risk analysis, and the application of remote sensing and GIS in sustainable development and climate resilience. Faruk’s work contributes significantly to disaster risk reduction, sustainable urban planning, and resource management, positioning him as a leading expert in geohazard mitigation and environmental sustainability.

Professional Profile

ORCID

Summary of Suitability

Faruk Hossain is a dedicated and skilled geoscientist whose expertise spans fluvial and tectonic geomorphology, active fault identification, geohazard assessment, and 3D subsurface modeling. His research contributes directly to addressing critical issues such as seismic hazards, landslides, riverbank erosion, and climate adaptation, making his work highly relevant to sustainable development and disaster resilience.

Education

He holds an M.Sc. in Engineering Geology from Universiti Kebangsaan Malaysia, where his research focused on landslide density analysis using GIS in the Cameron Highlands, building a strong foundation in geohazard investigation, engineering geology, and geotechnical engineering. He also earned an M.Sc. in Petroleum Geology and Geophysics from the University of Dhaka, gaining expertise in petroleum system evaluation, reservoir geology, and exploration geophysics. His academic journey began with a B.Sc. (Hons) in Geology from the University of Dhaka, covering a broad range of earth sciences disciplines including geomorphology, hydrogeology, sedimentology, and engineering geology. This multidisciplinary education has equipped him with the theoretical knowledge and practical skills necessary to address complex geological and environmental challenges.

Experience

Faruk has extensive professional experience in geological mapping, fluvial system analysis, morphometric studies, and basin hydrological assessments. His technical capabilities encompass remote sensing data analysis, geomorphological mapping, structural trend interpretation, and landslide susceptibility modeling using advanced methodologies such as the Analytical Hierarchy Process and Weighted Overlay Method. He is proficient in hydrological modeling, change detection analysis of river systems, and the creation of thematic maps for hazard assessment and resource planning. His work often involves integrating field data with spatial analysis tools to produce 3D subsurface lithological models, enabling more accurate hazard predictions and geological interpretations. Beyond field and analytical work, he has contributed to the development of engineering geological project databases, improving data accessibility and management for large-scale projects.

Research Interests

His research interests center on fluvial and tectonic geomorphology, active tectonics, and the interplay between geological processes and environmental hazards. He is deeply engaged in studying mountain hazards such as landslides, debris flows, and glacial lake outburst floods, as well as riverbank erosion and floodplain dynamics. Faruk is also interested in the application of remote sensing indices for environmental monitoring, climate risk assessment, and sustainable resource use. His focus on 3D subsurface modeling supports both academic research and applied solutions for infrastructure development, hazard mitigation, and land-use planning in geologically sensitive areas.

Awards

Faruk has been recognized for his contributions to geoscience research, hazard mapping, and sustainable development practices. His awards reflect his innovative approaches to geological problem-solving, his leadership in applying geospatial technologies for hazard assessment, and his dedication to promoting climate adaptation strategies. These honors highlight his ability to translate scientific expertise into practical applications that benefit both communities and policy-making bodies.

Publication Top Notes

Fluvio-geomorphic change of the Padma-Meghna river course using the NDWI and MNDWI techniques

Digital Elevation Modeling Of Saint Martin Island, Bangladesh: A Method Based On Open Source Google Earth Data

The Sikkim flood of October: drivers, causes and impacts of a multi-hazard cascade

Conclusion

Faruk Hossain exemplifies the integration of scientific rigor, technological innovation, and practical application in the field of geoscience. His multidisciplinary expertise, from hazard assessment to 3D geological modeling, addresses critical environmental and societal needs, particularly in regions prone to natural disasters and climate-related risks. By combining field-based observations with advanced remote sensing and GIS methodologies, he delivers data-driven solutions for sustainable land use, disaster preparedness, and resource management. His track record of publications, professional achievements, and recognized contributions make him an outstanding candidate for awards honoring excellence in geoscience and environmental sustainability.

 

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

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