A water stress index that quantifies relative water content at the leaf level. The ratio of 970nm to 900nm reflectance is sensitive to water absorption features and provides information about plant water status.

Used in crop monitoring, and water detection.

When to use

  • Permanent and seasonal water body delineation
  • Flood mapping and emergency response
  • Wetland inventory and change detection
  • Reservoir and lake water level monitoring
  • Coastal shoreline change analysis
  • Plant water content assessment
  • Water stress detection

Limitations

  • Dark surfaces (shadows, asphalt, dark soils) can produce false positives
  • Suspended sediments and algae alter spectral response in shallow water
  • Mixed pixels at water boundaries reduce edge accuracy
  • Atmospheric correction quality directly impacts threshold selection
  • Sun glint over open water can saturate sensors and bias values

What the values mean

-1 Definitely not water
-0.3 Dry / built-up surface
0 Possible moisture / wet soil
0.3 Open water
0.6 Deep / clear water
Surface typeTypical PWI
Built-up, asphalt-0.5 to -0.2
Bare soil, vegetation-0.2 to 0
Wet soil, flooded fields0 to 0.3
Open water, lakes0.3 to 0.7

General Formula

nir_900 900
nir_970 970

Sensor-Specific Formulas

Most-used sensors — click to show code below

SensorProviderFormulaBand Mapping

Code Examples

pwi_generic.py

PWI vs other water indices

IndexNameHow it differs
LSWILand Surface Water IndexAlternative water index — different band combination
LWVI-1Leaf Water Vegetation Index 1Alternative water index — different band combination
LWVI-2Leaf Water Vegetation Index 2Alternative water index — different band combination
MNDWIModified Normalized Difference Water IndexRefined formulation for specific conditions

Related Water Indices

References

Peñuelas et al. (1993). The reflectance at the 950–970 nm region as an indicator of plant water status.
Datt (1999). Remote Sensing of Water Content in Eucalyptus Leaves.
Ceccato et al. (2002). Designing a spectral index to estimate vegetation water content from remote sensing data.

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