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Ennassiri GIS, Agadir (2026)

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24/10/2024

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The Global Wind Atlas is a free, web-based application developed to help policymakers, planners, and investors identify high-wind areas for wind power generation virtually anywhere in the world, and then perform preliminary calculations.

23/10/2024

24/09/2024

TOP 8 REMOTE SENSING INDICES YOU SHOULD KNOW

1. Normalized Difference Vegetation Index (NDVI) 🌿
📊 Formula: (NIR - Red) / (NIR + Red)
🔍 Purpose: Measures vegetation health by comparing Near-Infrared (NIR) and Red bands.
🌱 Range: -1 to 1 (Higher = Healthier Vegetation)

2. Normalized Difference Water Index (NDWI) 💧
📊 Formula: (NIR - SWIR) / (NIR + SWIR)
🔍 Purpose: Identifies water bodies and monitors vegetation moisture.

3. Soil Adjusted Vegetation Index (SAVI) 🌱
📊 Formula: ((NIR - Red) / (NIR + Red + L)) * (1 + L)
🔍 Purpose: Reduces soil noise in areas with sparse vegetation.
🌍 L Factor: Soil brightness correction.

4. Enhanced Vegetation Index (EVI) 🌾
📊 Formula: 2.5 * ((NIR - Red) / (NIR + 6 * Red - 7.5 * Blue + 1))
🔍 Purpose: Corrects for atmospheric interference and soil noise in high biomass regions.

5. Normalized Burn Ratio (NBR) 🔥
📊 Formula: (NIR - SWIR) / (NIR + SWIR)
🔍 Purpose: Detects burn severity and monitors post-fire recovery.

6. Atmospherically Resistant Vegetation Index (ARVI) 🌲
📊 Formula: (NIR - (2 * Red) + Blue) / (NIR + (2 * Red) + Blue)
🔍 Purpose: Reduces atmospheric scattering to provide better vegetation monitoring.

7. Normalized Difference Built-Up Index (NDBI) 🏙️
📊 Formula: (SWIR - NIR) / (SWIR + NIR)
🔍 Purpose: Identifies built-up urban areas by contrasting man-made structures against natural surroundings.

8. Normalized Difference Snow Index (NDSI) ❄️
📊 Formula: (Green - SWIR) / (Green + SWIR)
🔍 Purpose: Detects snow cover by differentiating snow from clouds and water. Ideal for snowpack monitoring and climate studies.

NIR = Near-Infrared
SWIR = Shortwave Infrared

Enhance your remote sensing analysis with these powerful indices that highlight key features of the Earth's surface.

Which one(s) do you use the most? Let us know in the comments!