Elizaveta Khazieva on the Use of Satellite Images and Vegetation Indices to Track Environmental Issues
Elizaveta Khazieva, an experienced GIS specialist with over 10 years in remote sensing and GIS, delivered an informative lecture on "Satellite Images and Vegetation Indices" on February 7th. The lecture, part of the "Earth Observations in Monitoring SDGs with Google Earth Engine" course, explored the use of these tools for environmental monitoring, particularly in the context of the Sustainable Development Goals (SDGs).
Khazieva's lecture provided a comprehensive overview of the topic, starting with an introduction to satellite images and the basics of remote sensing. She traced the history of remote sensing, from early aerial cameras to the sophisticated satellite systems of today, and compared different remote sensing platforms. She then delved into the key characteristics of satellite data, explaining the importance of spatial, spectral, and temporal resolution.
The lecture covered major satellite missions, including the long-standing Landsat series for environmental monitoring, the high-resolution Sentinel-2 mission ideal for vegetation analysis, and MODIS and PlanetScope, which offer varying spatial and temporal resolutions for diverse applications. Khazieva dedicated a significant portion of her talk to the crucial steps of filtering and processing satellite data. She explained how to select appropriate images, filter collections by time, location, and cloud cover, and effectively handle cloud contamination - a common challenge in satellite imagery.
Khazieva then introduced image reduction techniques within Google Earth Engine (GEE), including first image selection, mean, median, and mode calculations for noise reduction, and advanced cloud masking methods for cleaner analysis. She also discussed the importance of spectral band combinations, from natural color (RGB) for human perception to infrared and shortwave infrared (SWIR) for distinguishing vegetation, water, and urban areas. She highlighted the use of vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), for assessing plant health and biomass.
The lecture connected these technical aspects to real-world applications in SDG monitoring, such as tracking deforestation (e.g., in the Amazon), assessing vegetation growth and land-use changes, and monitoring the impacts of floods, droughts, and climate change. The session culminated in a practical, hands-on demonstration of GEE features. Khazieva guided participants through filtering images by date, area, and cloud cover, and applying different visualization techniques using spectral bands.