MODIS NDWI (SWIR1/GREEN)

Overview
Extent
    Global
Spatial Resolution
    500m-1000m
Data Source(s)
    National Aeronautics and Space Administration (NASA)
Science Partner

Description

The MODIS sensors aboard the twin satellites Aqua and Terra provide global coverage of earth’s surface every 1 to 2 days. MODIS’s spatial, spectral, and temporal resolution allow for imagery to be utilized for regional monitoring of vegetation, land surface temperature, and the environment. MODIS data is available for Terra (daily, 8 day, or 16 day composites), Aqua (daily, 8 day, or 16 day composites), and composite of Terra/Aqua 16 day using 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): 1.628-1.652 μm
Green: 0.545-0.565 μm

Technical Information

Feature
Detail
Extent
Global
Period of Record
2000-present
Spatial Resolution
500-1000m
Temporal Resolution
Daily
Data Summaries
max, min, mean, median, anomalies, trend and statistical significance, spatial and temporal aggregations, time series
Data Source(s)
National Aeronautics and Space Administration (NASA)
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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