Overview
In remote sensing, ''ratio image'' or ''spectral rationing'' are enhancement techniques in which a raster pixel from one spectral band is divided by the corresponding value in another band. Both the indexes above share this same functional form; the choice of bands used is what makes them appropriate for a specific purpose. If looking to monitor vegetation in drought affected areas, then it is advisable to use NDWI index proposed by Gao utilizing NIR and SWIR. The SWIR reflectance in this index reflects changes in both the vegetation water content and the spongy mesophyll structure in vegetation canopies. The NIR reflectance is affected by leaf internal structure and leaf dry matter content, but not by water content. The combination of the NIR with the SWIR removes variations induced by leaf internal structure and leaf dry matter content, improving the accuracy in retrieving the vegetation water content. NDWI concept as formulated by Gao combining reflectance of NIR and SWIR is more common and has wider range of application. It can be used for exploring water content at single leaf level as well as canopy/satellite level. The range of application of NDWI (Gao, 1996) spreads from agricultural monitoring for crop irrigation and pasture management to forest monitoring for assessing fire risk and live fuel moisture particularly relevant in the context of climate change. Different SWIR bands can be used to characterize the water absorption in generalized form of NDWI as shown in eq. 1. Two major water absorption features in SWIR spectral region are centered near ''1450 nm'' and ''1950 nm'' while two minor absorption features are centered near ''970'' and ''1200 nm'' in a living vegetation spectrum.Interpretation
Visual or digital interpretation of the output image/raster created is similar to NDVI: * -1 to 0 - Bright surface with no vegetation or water content * +1 - represent water content For the second variant of the NDWI, another threshold can also be found in {{Cite journal, doi = 10.3390/rs5073544, doi-access = free, title = Using the Normalized Difference Water Index (NDWI) within a Geographic Information System to Detect Swimming Pools for Mosquito Abatement: A Practical Approach, year = 2013, last1 = McFeeters, first1 = Stuart, journal = Remote Sensing, volume = 5, issue = 7, pages = 3544–3561, bibcode = 2013RemS....5.3544M that avoids creating false alarms in urban areas: * < 0.3 - Non-water * >= 0.3 - Water.External links
* https://edo.jrc.ec.europa.eu/documents/factsheets/factsheet_ndwi.pdf (NDWI for crop monitoring: index by Gao, 1996) * https://developers.google.com/earth-engine/datasets/catalog/MODIS_MYD09GA_006_NDWI (MODIS NDWI calculation) * https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C01_T1_32DAY_NDWI (Landsat NDWI calculation) * http://deltas.usgs.gov/fm/data/data_ndwi.aspx (regarding the McFeeters index for water bodies) * http://space4water.org/taxonomy/term/1246 (Modification of the McFeeters index for improved detection of water bodies)References