Скачать или смотреть Soil Salinity Sentinel-2 in Google Earth Engine

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In this video, we explore how to use Sentinel-2 Surface Reflectance data to analyze soil salinity in the Nile Delta, Egypt. By leveraging the Soil Salinity Index (SI), which is a combination of the SWIR and NIR bands from Sentinel-2 imagery, we can identify areas with high levels of salinity that are crucial for agriculture and land management.

This tutorial takes you through a step-by-step process of:

Loading Sentinel-2 Data: We use Google Earth Engine (GEE) to access and filter Sentinel-2 surface reflectance data.

Cloud Masking: A cloud percentage filter is applied to ensure that only clear-sky data is considered.

Creating the Soil Salinity Index: The Soil Salinity Index is calculated using the normalized difference between the SWIR (B11) and NIR (B8) bands.

True Color Composite: A true color composite is generated to help visualize the landscape and distinguish different land features.

Visualization: We display the soil salinity index and true color images on a map with custom color palettes to highlight the salinity levels and the overall land cover.

This method is effective for monitoring land health, understanding salinity impacts on agriculture, and assisting in better water and land management practices. Follow along to learn how remote sensing and satellite data can aid in environmental monitoring!

🚀 Get full course access with complete code in Google Earth Engine!
👉 https://www.udemy.com/course/soil-sal...
👉 https://bit.ly/EarthsAI


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