How to Calculate NDVI using Global Mapper

NDVI (Normalized Difference Vegetation Index) is a widely used index for assessing vegetation health and density using satellite or aerial imagery. NDVI leverages the difference in how healthy vegetation reflects near-infrared (NIR) and red light, with healthy plants reflecting more NIR and absorbing more red light.
The formula for calculating NDVI is:
NDVI=(NIR−Red)(NIR+Red)NDVI = \frac{(NIR - Red)}{(NIR + Red)}NDVI=(NIR+Red)(NIR−Red)
Where:
• NIR represents the near-infrared band (which plants reflect strongly).
• Red represents the red band (which plants absorb for photosynthesis).
NDVI Value Ranges:
• +0.2 to +1: Dense, healthy vegetation. The higher the value, the healthier or denser the vegetation.
• 0 to +0.2: Sparse or stressed vegetation (e.g., shrubland, grassland, or crops with poor health).
• 0 or negative: Non-vegetated surfaces such as water, rocks, barren land, or urban areas.
Steps to Calculate NDVI in Global Mapper:
1. Load Multi-spectral Imagery: Ensure your satellite imagery or aerial data contains at least two bands: one for the red wavelength and one for near-infrared (NIR).
2. Open Raster Calculator: In Global Mapper, use the Raster Calculator tool. This is located under the Analysis/Measurement menu, where you can perform raster band math.
3. Apply NDVI Formula:
o Select the NIR band and subtract the red band.
o Divide the result by the sum of the NIR and red bands.
o The formula should look like: (Band_NIR - Band_Red) / (Band_NIR + Band_Red).
4. Generate NDVI Output: Once you apply the calculation, Global Mapper will produce a new raster layer where each pixel represents the NDVI value.
5. Interpret the Results:
o NDVI values will range from -1 to +1, where higher values indicate healthy, dense vegetation, and lower values indicate bare soil, water, or sparse vegetation.
o You can visualize the results using a color ramp to better understand vegetation patterns across the area.
Uses of NDVI:
• Agricultural Monitoring: Farmers use NDVI to monitor crop health, estimate biomass, and detect areas of stress.
• Forestry: NDVI can assess forest density and monitor deforestation or afforestation efforts.
• Environmental Studies: It helps in tracking changes in vegetation over time due to urbanization, climate change, or natural disasters.
• Land Cover Classification: NDVI is often used in land cover mapping to distinguish between vegetated and non-vegetated areas.
• Drought Detection: NDVI values can highlight areas experiencing drought stress as vegetation loses health.

[@Yourealer]

Great Tutorial..🎉