Mārtiņš Puķītis is a research assistant at the Institute of Electronics and Computer Science (EDI), where he began working in 2015. In the same year, he obtained a master’s degree in mathematics from the Faculty of Physics and Mathematics at the University of Latvia.
Mārtiņš research interests are related to remote sensing, with a particular focus on the automatic classification of images obtained by remote sensing. His work involves the application of various image processing, machine learning, and data analysis methods to improve image interpretation and ensure effective information extraction from satellite and other image data.
Recent projects
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Object based context aware self-learning network for land cover classification (Dynland-2)
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Sentinel for confidence in outdated maps: SentiMap
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Remote sensing based system for forest risk factor monitoring (Forest Risk) #ESIF
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Comprehensive analysis of hemiboreal forest structure, species composition and ecosystem services using VHR hyperspectral and LiDAR data (HYLIFORES) #FLPP
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Monitoring urban waterfront and recreation territories (Waterfront) #ESA
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EO Baltic Platform for Governmental Services (EO-BALP) #ESA
Recent publications
- Andris Skromulis, Juris Breidaks, Mārtiņš Puķītis. 2023. "Wetland Change Detection Using Sentinel-2 in the Part of Latvia" Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference. https://doi.org/10.17770/etr2023vol1.7305
- Martins Pukitis, Ints Mednieks. "Classification of satellite images using Dynland technology" Proc. SPIE 12786, Ninth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2023), 127860E (21 September 2023); https://doi.org/10.1117/12.2681896