Landsat NDWI (SWIR1/Green)

Overview
Extent
    Global
Spatial Resolution
    30m
Data Source(s)
    LANDSAT
Science Partner

Description

The Landsat program provides the longest continuous record of satellite earth observations. Landsat spatial, spectral, and temporal resolutions allow for imagery to be processed at sufficient spatial and temporal detail that is optimal for field scale land surface monitoring, management, and research. Landsat data is available for Landsat 5, 7, 8, and composites of 4/5/7/8 using top of atmosphere or at surface reflectance data.

Normalized Difference Water Index (NDWI) (SWIR1/Green) is a water index which provides information on the extent of small turbid ponds (Lacaux 2007) or larger water bodies. This product typically ranges from -0.25 to 1 where water is typically below 0 (Özelkan 2020).

NDWI (SWIR1/Green) is the normalized difference between the short wave near infrared 1 (SWIR1) and green bands following the equation (SWIR1-Green)/(SWIR1+Green) (Lacaux 2007; Allen et al., 2014). Water reflects Green and absorbs SWIR1 electromagnetic radiation while vegetation and soil absorbs Green and reflects SWIR1 electromagnetic radiation (Xu 2006). The result is a low NDWI over water and a high NDWI over land with high contrast.

Bands Used:
Short Wave Infrared 1 (SWIR1): 1.55-1.75 μm
Green: 0.52-0.60 μm

Technical Information

Feature
Detail
Extent
Global
Period of Record
1984-present
Spatial Resolution
30m
Temporal Resolution
8-16 days
Data Summaries
max, min, mean, median, anomalies, trend and statistical significance, spatial and temporal aggregations, time series
Data Source(s)
U.S. Geological Survey
Data Formats
raster (geotiff), raster tile (tile ID), time series (.csv, .xls, .json, .geojson)
Sources

Allen, R., Trezza, R., Tasumi, M., & Kjaersgaard, J. (2014). METRIC: Mapping Evapotranspiration at High Resolution Using Internalized Calibration Applications Manual for Landsat Satellite Imagery. V, 3.

Lacaux, J. P., Tourre, Y. M., Vignolles, C., Ndione, J. A., & Lafaye, M. (2007). Classification of ponds from high-spatial resolution remote sensing: Application to Rift Valley Fever epidemics in Senegal. Remote Sensing of Environment, 106(1), 66-74.

Özelkan, E. (2020). Water body detection analysis using NDWI indices derived from Landsat-8 OLI. Polish Journal of Environmental Studies, 29(2), 1759-1769.

Xu, H. (2006). Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. International journal of remote sensing, 27(14), 3025-3033.

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