Master the use of satellite remote sensing data and Google Earth Engine to analyze, map, and monitor drought risk
Drought poses a significant threat to global agriculture, impacting food security, water resources, and livelihoods. This course equips you with cutting-edge skills to analyze and map drought risk using remote sensing data and the Google Earth Engine platform. Beginning with the fundamentals of remote sensing, you’ll gain a solid understanding of how satellites like Sentinel-2 capture essential data on vegetation health and soil moisture.
What you’ll learn
- Analyze drought risk factors using remote sensing data and understand their impact on agriculture..
- Process, filter, and visualize multi-source satellite data effectively in Google Earth Engine..
- Calculate, normalize, and interpret various drought risk indices using NDVI, rainfall, and soil moisture data..
- Develop, export, and utilize detailed drought risk maps to support informed agricultural decision-making and resource management..
Course Content
- Introduction –> 6 lectures • 1hr 5min.
Requirements
Drought poses a significant threat to global agriculture, impacting food security, water resources, and livelihoods. This course equips you with cutting-edge skills to analyze and map drought risk using remote sensing data and the Google Earth Engine platform. Beginning with the fundamentals of remote sensing, you’ll gain a solid understanding of how satellites like Sentinel-2 capture essential data on vegetation health and soil moisture.
The course then delves into remote sensing applications for environmental risk mapping, with a special focus on drought. You will learn to process time-series satellite images, calculate vegetation indices such as NDVI, and assess rainfall and soil moisture anomalies by comparing current data with historical baselines.
Next, you will be introduced to Google Earth Engine—a cloud-based platform that simplifies large-scale data analysis. You’ll get hands-on experience scripting in GEE to integrate multiple datasets and develop comprehensive drought risk indices. The course also covers normalization techniques and anomaly detection to identify areas of elevated drought risk accurately.
In the final modules, you will implement a complete drought risk mapping workflow in GEE. This includes selecting the area of interest, processing seasonal data, combining multiple drought indicators, and visualizing results with effective color palettes. The course culminates with exporting high-quality maps for use in agricultural planning and disaster management.
By the end of the course, you will confidently apply remote sensing and GEE tools to support drought monitoring initiatives, helping mitigate the impacts of drought on agriculture and natural resources.