NDMI
Normalized Difference Moisture Index. Measures vegetation water content using the difference between near-infrared and shortwave infrared bands. Used to monitor drought stress, irrigation needs, and fire risk assessment.
Formula
NDMI = (NIR - SWIR) / (NIR + SWIR)Overview
The Normalized Difference Moisture Index (NDMI) quantifies water content within vegetation canopies by combining NIR and SWIR reflectance. It is one of the most widely used indices for detecting vegetation water stress, monitoring drought, and assessing fire fuel moisture. Sometimes confused with Gao's NDWI — the community increasingly uses "NDMI" for the vegetation moisture variant.
How It Works
NDMI = (NIR − SWIR) / (NIR + SWIR). On Sentinel-2: (B8 − B11) / (B8 + B11). NIR reflectance depends on leaf structure, while SWIR is strongly influenced by water content. Well-hydrated vegetation produces values of 0.2–0.6+, while stressed vegetation approaches zero or negative.
Key Facts
- Formula: (NIR − SWIR) / (NIR + SWIR)
- Originally published by Bo-Cai Gao (1996) as "NDWI" — renamed NDMI to avoid confusion.
- Healthy vegetation typically falls between 0.2 and 0.6.
- Sentinel-2 bands: B8 (NIR, 10 m) and B11 (SWIR-1, 20 m).
Applications
Drought Monitoring
Detecting early vegetation water stress before visible wilting occurs.
Fire Risk Assessment
Estimating live fuel moisture content to predict wildfire potential.
Irrigation Management
Identifying under-irrigated or waterlogged zones within fields.
Forest Disturbance Detection
Mapping areas affected by insect infestations or disease.
Limitations & Considerations
Cannot directly assess soil moisture beneath closed canopy. Saturates in very dense, well-watered vegetation. Resolution mismatch between B8 (10 m) and B11 (20 m) on Sentinel-2.
History & Background
Proposed by Bo-Cai Gao in 1996. Wilson et al. (2002) introduced the NDMI naming. Now a standard product from USGS, ESA, and major geospatial platforms.
Analyze NDMI data with LYRASENSE
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