• views: 82
• date: 6 August 2025
• posted by: 0nelove

Map and analyze soil erosion risk using remote sensing, GIS, and Google Earth Engine tools.
What you'll learn
Understand the fundamental concepts of soil erosion processes and the factors influencing erosion risk.
Learn how to access, process, and analyze remote sensing datasets (e.g., SRTM, CHIRPS, Sentinel-2) in Google Earth Engine for environmental mapping.
Develop skills to create normalized indices (such as slope, rainfall, and NDVI) and combine them to generate a soil erosion risk map.
Gain hands-on experience exporting and visualizing geospatial results, enabling effective communication of soil erosion risk assessments for decision-making.
Requirements
No prior experience with Google Earth Engine is required — the course will guide you step-by-step.
Description
Soil erosion poses a significant threat to agricultural productivity, ecosystem stability, and sustainable land management. Understanding and mapping erosion risk is critical for implementing effective mitigation strategies. This course equips students with a comprehensive understanding of remote sensing and GIS principles applied to soil erosion risk assessment.The course begins with a thorough introduction to remote sensing fundamentals, including the physics of satellite imagery and data acquisition. Students learn about different satellite sensors, focusing on Sentinel-2's spectral bands and spatial resolutions that are essential for environmental monitoring. The introduction to GIS covers spatial data handling, analysis techniques, and visualization, laying the groundwork for geospatial data manipulation.A major focus is on Google Earth Engine (GEE), a cloud-based platform offering vast satellite imagery archives and powerful processing capabilities. Learners will master GEE's interface, scripting environment, and essential tools for remote sensing data processing. The course culminates in the application of these skills to develop a soil erosion risk mapping project. Students will learn how to integrate slope, rainfall, vegetation indices, and other relevant datasets to generate accurate risk maps.Through hands-on exercises and real-world examples, students gain practical experience in environmental data analysis and spatial decision-making. This course is ideal for environmental scientists, GIS professionals, land managers, and anyone interested in leveraging cutting-edge technology for sustainable land use planning and natural resource management.
Who this course is for
Students, researchers and professionals in agriculture, environmental science, geography, or remote sensing looking to apply satellite data in real-world scenarios.



   
   
   

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