Dr. Niraj KC | Remote Sensing | Editorial Board Member
Lumbini Technological University | Nepal
Dr. Niraj K. C. is a leading geospatial scientist whose research integrates remote sensing, GIS, machine learning, and satellite-based analytics to address complex geohazard and environmental challenges in the Himalayan region and beyond. His work focuses on developing advanced landslide early warning systems by fusing optical and SAR datasets, optimizing statistical and machine learning models, and refining susceptibility mapping using NDVI-linked predictors, ensemble learning, and transfer-learning approaches. He has significantly contributed to time-series SAR deformation analysis using D-InSAR and MT-InSAR for precise landslide event dating, slope instability characterization, and hazard zonation in mountainous terrain. His research also extends to urban environmental monitoring, including the assessment of urban heat islands, land-use/land-cover transitions, and long-term environmental changes using multi-decadal satellite archives, cloud computing platforms, and AI-driven predictive modeling. Dr. Niraj has pioneered methods that combine NDVI with SAR deformation patterns to improve event timing accuracy, optimized pseudo-absence sampling strategies, and introduced robust ensemble ML workflows for data-scarce regions. His scholarly output includes numerous publications in Q1/Q2 journals, demonstrating strong contributions to remote sensing, engineering geology, environmental risk assessment, spatial statistics, and geospatial modeling. He has supervised multiple postgraduate theses and collaborated extensively within multidisciplinary teams advancing geospatial research. His scientific impact is reflected through growing citation metrics and peer recognition, with publications widely referenced across remote sensing, geomatics, and hazard-science communities. He actively contributes as a reviewer for international journals and continues to expand research on AI-based hazard prediction, permafrost and glacier lake dynamics, InSAR-driven surface deformation, and climate-risk analytics, supporting evidence-based disaster mitigation and sustainable development. Dr. Niraj K. C. is a strong contender for Editorial Board Member, given the depth, innovation, and scientific influence of his contributions.
Publication Profile
Google Scholar
Featured Publications
KC, N., Singh, A., & Shukla, D. P. (2023). Effect of the normalized difference vegetation index (NDVI) on GIS-enabled bivariate and multivariate statistical models for landslide susceptibility mapping. Journal of the Indian Society of Remote Sensing, 51(8), 1739–1756.
Singh, A., Chhetri, N. K., Nitesh, Gupta, S. K., & Shukla, D. P. (2023). Strategies for sampling pseudo-absences of landslide locations for landslide susceptibility mapping in complex mountainous terrain of Northwest Himalaya. Bulletin of Engineering Geology and the Environment, 82(8), 321.
KC, N., Gupta, S. K., & Shukla, D. P. (2022). Kotrupi landslide deformation study in non-urban area using DInSAR and MTInSAR techniques on Sentinel-1 SAR data. Advances in Space Research, 70(12), 3878–3891.
Singh, A., Dhiman, N., KC, N., & Shukla, D. P. (2024). Ensembled transfer learning approach for error reduction in landslide susceptibility mapping of the data-scarce region. Scientific Reports, 14(1), 29060.
KC, N., Chatterjee, R. S., & Shukla, D. P. (2023). Estimating the period of probable landslide event using advanced D-InSAR technique for time-series deformation study of Kotrupi region. Geomatics, Natural Hazards and Risk, 14(1), 2281245.