Assist. Prof. Dr. Rafael Lemos Paes | Remote Sensing | Research Excellence Award – 6908

Assist. Prof. Dr. Rafael Lemos Paes | Remote Sensing | Research Excellence Award

Assist. Prof. Dr. Rafael Lemos Paes | Remote Sensing | Brazilian Air Force Academy | Brazil

Assist. Prof. Dr. Rafael Lemos Paes is a Remote Sensing Scientist specializing in Synthetic Aperture Radar and artificial intelligence applications for maritime and aerospace domains, with a career that integrates advanced academic research, operational defense expertise, and strategic technological advisory roles. Rafael Lemos Paes holds a PhD and a Master’s degree in Remote Sensing from the National Institute for Space Research in Brazil and a Bachelor’s degree in Aeronautical Sciences from the Brazilian Air Force Academy, reflecting a strong interdisciplinary foundation spanning Earth observation, computational intelligence, and aeronautical operations. During his doctoral training, Rafael Lemos Paes served as a visiting researcher at the Università degli Studi di Napoli “Parthenope” in Italy, where he conducted internationally supervised research that strengthened his expertise in spaceborne and airborne radar systems. Professionally, Rafael Lemos Paes currently serves at the Brazilian Air Force General Staff, where he provides high-level advisory support in C4ISR, advanced technologies, research and development, strategic innovation initiatives, and long-term defense and aerospace programs, bridging scientific research with national security and aerospace decision-making. His research interests are centered on Synthetic Aperture Radar data analysis, compact polarimetric SAR in hybrid modes, deep learning and automatic pattern recognition, maritime surveillance, and the extraction of actionable intelligence from large-scale remote sensing datasets. Rafael Lemos Paes has made notable contributions to maritime target detection over ocean surfaces, including ship detection, oil spill monitoring, and small vessel identification in complex environments such as Amazonian river systems, as well as aircraft accident analysis and shipwreck debris detection using SAR imagery. His research skills include SAR signal processing, polarimetric analysis, Big Data analytics, machine learning and deep learning model development, computational intelligence techniques, geospatial data integration, and the operational exploitation of airborne and spaceborne sensor data for defense and civil applications.

Citation Metrics (Google Scholar)

300

200

100

0

Citations
296

h-index
8

i10-index
8

Citations
h-index
i10-index


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Featured Publications


Ship Detection Using TerraSAR-X Images in the Campos Basin (Brazil)


– IEEE Geoscience and Remote Sensing Letters, 2010 · 80 citations


Oil Rig Recognition Using Convolutional Neural Networks on Sentinel-1 SAR Images


– IEEE Geoscience and Remote Sensing Letters, 2019 · 36 citations


On the Capability of Hybrid-Polarity Features to Observe Metallic Targets at Sea


– IEEE Journal of Oceanic Engineering, 2015 · 24 citations

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)