Sentinel-2 NDWI(Green/SWIR2)

Overview
Extent
    Quasi Global (83 degrees N, 56 degrees S latitude)
Spatial Resolution
    10m
Data Source(s)
    European Space Agency (ESA)
Science Partner

Description

The Sentinel program is composed of two satellites (Sentinel 2A, 2B) and was developed to monitor land surface changes in vegetation, the environment, and land cover. Sentinel-2 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. Sentinel-2 datasets are available for Sentinel 2A, 2B, and composite of 2A/2B using top of atmosphere or at surface reflectance data.

Landsat Normalized Difference Water Index (NDWI) (Green/SWIR2) is a water index which provides information on open water extent. This product typically ranges from -1 to 0.25 where water is typically above 0.04 (Özelkan 2020). This product is useful for identifying open water to use in estimating water surface area or removal through masking.

Landsat NDWI (Green/SWIR2) is the normalized difference between the green and short wave near infrared 1 (SWIR2) bands following the equation (Green-SWIR2)/(Green+SWIR2). Water reflects Green and absorbs SWIR2 electromagnetic radiation while vegetation and soil absorbs Green and reflects SWIR2 electromagnetic radiation (Xu 2006). The result is a high normalized difference (ND) over water and a low ND over land with high contrast.

Bands Used:
Green: 0.560 μm (S2A) / 0.559 μm (S2B)
Short Wave Infrared 2 (SWIR2): 2.2024 μm (S2A) / 2.1857 μm (S2B)

Technical Information

Feature
Detail
Extent
Quasi Global (83 degrees N, 56 degrees S latitude)
Period of Record
2015-present for 2A; 2017-present for 2B
Spatial Resolution
10m
Temporal Resolution
2-3 days (at mid latitudes), 5-10 days (at equator)
Data Summaries
max, min, mean, median, anomalies, trend and statistical significance, spatial and temporal aggregations, time series
Data Source(s)
European Space Agency (ESA)
Data Formats
raster (geotiff), raster tile (tile ID), time series (.csv, .xls, .json, .geojson)
Sources

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.

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

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