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SUMMARY:Advanced Course on Optical Remote Sensing for Agroecological Sustainability
DESCRIPTION:On Tuesday\, October 21\, and Thursday\, October 23\, 2025\, the “Advanced Course on Optical Remote Sensing for Agroecological Sustainability” will take place in the Grandori Classroom (Building 4) from 14:00 to 18:00 CET. \nThe course will be delivered by Prof. Lachezar Filchev from the Space Research and Technology Institute\, Bulgarian Academy of Sciences (SRTI-BAS). \nParticipation is also available online via the following Webex link: https://politecnicomilano.webex.com/meet/vasil.yordanov \n\n  \nCourse Description \nThis course provides an in-depth introduction to optical and hyperspectral remote sensing\, emphasizing open-source and cloud-based workflows for environmental and agricultural monitoring. Participants explore the full analytical chain—from data acquisition and atmospheric correction to machine learning-based classification and biophysical parameter estimation. The course integrates theoretical lectures with guided exercises using real satellite datasets. \nLearning Objectives \nUpon completion\, participants will be able to: \n\nExplain key principles of multispectral and hyperspectral remote sensing.\nPerform atmospheric correction using Sen2Cor and QGIS tools.\nDevelop and utilize spectral libraries for material and vegetation analysis.\nApply random forest classification and transfer learning techniques in crop monitoring.\nImplement drought and soil health indices using optical and hyperspectral data.\nOperate GRASS GIS and Google Earth Engine for integrated data analysis.\n\nDuration: 8h \nTopics: \n(1) Optical Remote Sensing Fundamentals\, covering multispectral imaging principles and atmospheric correction workflows using QGIS and Sen2Cor\, spectral reflectance characteristics; \n(2) Hyperspectral Data Analysis\, (exploring legacy data EO-1/Hyperion\, CHRIS/PROBA\, and PRISMA and DESIS missions\, spectral library development\, and derivative spectroscopy); \n(3) Machine Learning in Crop Monitoring\, (implementing random forest classification and transfer learning); \n(4) Drought & Soil Health Monitoring\, (Modified Temperature Vegetation Dryness Index (MTVDI) and hyperspectral soil organic carbon (SOC) estimation using Google Earth Engine and GRASS GIS). \nTechnology \nThroughout the course\, participants gain hands-on experience with a diverse FOSS toolchain\, including Sen2Cor\, ENVI FOSS\, QGIS\, GRASS GIS\, and Google Earth Engine. \n\n\nLecturer’s bio\n\n\nProf. Lachezar Filchev is a professor and Head of the Remote Sensing and GIS Department at the Space Research and Technology Institute\, Bulgarian Academy of Sciences (SRTI-BAS) in Sofia\, Bulgaria. With over 15 years of experience in remote sensing\, GIS\, landscape ecology\, and environmental management\, he has led numerous national and international research projects and published extensively in peer-reviewed journals. His expertise spans Earth observation\, hyperspectral remote sensing\, land use/cover analysis\, and the application of spatial data infrastructure for environmental and agricultural monitoring. Prof. Filchev is actively involved in mentoring early-career researchers and has received multiple awards for scientific excellence and peer review.
URL:https://www.dica.polimi.it/en/evento/advanced-course-on-optical-remote-sensing-for-agroecological-sustainability-2/
CATEGORIES:Seminari e conferenze
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