Yifei Yin | Speckle noise suppression in SAR images | Research Excellence Award

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Dr. Yifei Yin | Speckle noise suppression in SAR images | Research Excellence Award

Beijing Institute of Technology | China 

The research work focuses on the intelligent interpretation of synthetic aperture radar imagery, with particular emphasis on end-to-end understanding of satellite-based SAR data. Core research activities include SAR image pre-processing, Speckle noise suppression in SAR images speckle noise suppression, and robust target detection and recognition under complex imaging conditions. A key scientific contribution lies in addressing the limitations of conventional supervised learning approaches, which typically rely on clean reference images that are rarely available in real-world SAR scenarios. To overcome this challenge, a self-supervised despeckling framework was proposed, enabling effective network training using only intensity SAR images without the need for external ground-truth data. This strategy significantly enhances the practicality and scalability of deep learning methods for operational SAR systems. The research further contributes to improving feature preservation and structural consistency in despeckled images, which directly benefits downstream tasks such as object recognition and scene understanding. In addition, the work actively supports national-level research and development initiatives, fostering collaboration across multidisciplinary teams in remote sensing, signal processing, and artificial intelligence. Overall, these contributions advance the reliability, adaptability, and real-world applicability of intelligent SAR image interpretation, strengthening its role in satellite observation, surveillance, and Earth monitoring applications.

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Self-supervised despeckling based solely on SAR intensity images: A general strategy


– ISPRS Journal of Photogrammetry and Remote Sensing, 2026

Mohammad Imrul Islam | Geospatial and Spatial Statistics | Best Researcher Award

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Mr. Mohammad Imrul Islam | Geospatial and Spatial Statistics | Best Researcher Award

Bangladesh Space Research and Remote Sensing Organization (SPARRSO) | Bangladesh

Mr. Mohammad Imrul Islam is a highly dedicated Remote Sensing Researcher and Senior Scientific Officer (SSO) at the Bangladesh Space Research and Remote Sensing Organization (SPARRSO), where he has been contributing his expertise since 2015. With over a decade of professional experience in Remote Sensing (RS) and Geographic Information System (GIS), his work focuses on environmental monitoring, agriculture, forestry, and water resource management, making him one of the promising scientific minds in Bangladesh’s earth observation community. He holds a Master of Engineering in Remote Sensing and GIS from Beihang University, Beijing, China (GPA 3.76), along with both Master of Science and Bachelor of Science degrees in Geography and Environment from Jahangirnagar University, Bangladesh, with first-class distinction. At SPARRSO, he has successfully led and contributed to several national and institutional projects such as flash flood monitoring in Tanguar Haor, spatio-temporal analysis of fisheries habitats, water quality assessment for inland fisheries, and GIS-based marine fishing zone identification. His research showcases his ability to integrate satellite data with advanced geospatial analytics for sustainable environmental management and disaster resilience. His postgraduate research and pilot studies explored innovative approaches such as retrieving Leaf Area Index (LAI) and analyzing the relationship between Solar-Induced Chlorophyll Fluorescence (SIF) and Gross Primary Production (GPP), reflecting his strong foundation in combining remote sensing models with ecological parameters for vegetation monitoring. Mr. Islam has participated in numerous international training and capacity-building programs organized by ISRO, APSCO, NESAC, Hokkaido University, and the University of Twente (ITC, Netherlands), enhancing his global scientific exposure. His technical expertise covers major geospatial and analytical software including ArcGIS, QGIS, ERDAS Imagine, ENVI, SNAP, and cloud-based tools such as Google Earth Engine, complemented by programming proficiency in Python, R, and MATLAB. Fluent in both English and Bangla, and with a TOEIC score of 805, he demonstrates strong communication and collaboration skills across international platforms. Through his ongoing research on seasonality mapping of surface water and hydrometeorological flood monitoring, he continues to contribute toward global climate resilience and sustainable resource management. Actively engaged on ResearchGate, LinkedIn, and ORCID, Mohammad Imrul Islam inspires emerging geospatial researchers across South Asia. His academic rigor, technical competence, and impactful research contributions make him an exemplary candidate for the Best Researcher Award, recognizing his significant role in advancing earth observation and remote sensing research at both national and international levels.

Profiles: Google Scholar | Orcid | Linked In

Featured Publications

Islam, M. I., Rahman, M. M., & Islam, M. Z. (2025). Comparative analysis of chlorophyll-a retrieval algorithms for inland waterbodies of Bangladesh using Sentinel-2 and Landsat-8 imagery. Discover Geoscience.

Niloy, N. M., Habib, S. M. A., Islam, M. I., Haque, M. M., Shammi, M., & Tareq, S. M. (2023). Distribution, characteristics and fate of fluorescent dissolved organic matter (FDOM) in the Bay of Bengal. Marine Pollution Bulletin.

Islam, M. I., Habib, S. M. A., Haque, S. A. U., Sultana, N., Faisal, B. M. R., Rahman, H., & Sharifee, M. N. H. (2020). Applicability of OCO-2 solar induced chlorophyll fluorescence (SIF) data for the estimation of photosynthetic activity in Bangladesh. Journal of Engineering Science, 11(2), 1–9.

Faisal, B. M. R., Rahman, H., Sharifee, N. H., Sultana, N., Islam, M. I., Habib, S. M. A., & Ahammad, T. (2020). Integrated application of remote sensing and GIS in crop information system: A case study on Aman rice production forecasting using MODIS-NDVI in Bangladesh. AgriEngineering, 2(2), 243–257.

Rahman, M. M., Pramanik, M. A. T., Islam, M. I., & Razia, S. (2019). Mapping mangrove forest change in Nijhum Dwip Island. Journal of Environmental Science and Natural Resources, 11(1–2), 25–32.