This course provides a thorough introduction to snow cover monitoring using MODIS satellite data and the Google Earth Engine (GEE) platform. Designed for students, researchers, environmental professionals, and anyone interested in remote sensing, this course covers essential concepts and practical skills needed for effective snow cover analysis. You will start by learning the fundamentals of remote sensing, including how satellites collect data, spectral bands, spatial and temporal resolution, and data processing basics. The course emphasizes the importance of snow cover for climate regulation, water resource management, and ecosystem health, explaining why accurate monitoring is critical.
You will then be introduced to Google Earth Engine, a powerful cloud-based platform for analyzing large-scale geospatial datasets. The course guides you through accessing, filtering, and visualizing MODIS snow cover data, focusing on the NDSI_Snow_Cover product. You’ll learn how to handle temporal data, generate maximum snow cover maps for specific periods, and create insightful time series to observe seasonal and yearly trends.
Hands-on implementation is a key part of this course. You will work with real datasets to process, visualize, and interpret snow cover changes over multiple years. You will also gain practical experience exporting your results as GeoTIFF files for use in GIS or further analysis. By the end of the course, you will be equipped with the knowledge and skills to confidently monitor snow cover dynamics, apply remote sensing techniques, and leverage GEE’s capabilities to support environmental research, climate studies, and resource management decisions.
- Students and researchers in agriculture, environmental science, geography, or remote sensing looking to apply satellite data in real-world scenarios.
