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Crop Agriculture

Normalized Difference Drought Index (NDDI)

Related page:  Crop Water Content Mapping   Live Fuel Moisture Content 

Free Landsat imagery can be used along with free GIS software (or other GIS Software, such as ArcGIS) to map drought characteristics. Gu et al (2007) developed the Normalized Difference Drought Index (NDDI) which can be used (as can the Normalized Difference Water Index [NDWI], solely) to assess drought, and is written as:

Where, NDVI = ([NIR - red] / [NIR + red]) and NDWI = ([NIR - SWIR] / [NIR + SWIR]); NIR = near infrared and SWIR = short wave infrared

Also see Bajgain et al (2015) for more satellite drought assessment information and the following website (outside page) for NDDI information:

Images transition every 4 seconds (or click arrows or dots); description appears below graphic

Symbology for above graphics: all slides except NDDI are symbolized continuously from ± 2 standard deviations from the mean; NDDI is classification based mainly on Gu at al. (2007).

Gu et al. (2007) and Renza et al. (2010) found NDDI to be a superior drought indicator when compared to other indices (see articles below). Graphics below are of an area with agriculture and fire-prone mountains in central Washington state, USA. 

The index is relatively new and was initially applied to grassland of the central Great Plains in the United States by Gu et al. (2007) using MODIS; they found MODIS-based NDDI is a superior indicator of drought than solely NDVI, NDWI, or by applying the difference between NDVI and NDWI. Renza et al. (2010) applied the index using Landsat in Spain for different vegetation and had favorable results compared to other indices when sensing drought condition, including solely NDVI or NDWI (as was also the case with Gu et al.). (See links to articles below.) NDDI takes advantage of the fact NDVI senses plant matter and NDWI senses plant moisture. 



Gu et. al. 2007. A five-year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central Great Plains of the United States (pdf)

Renza et al.  2010.  Drought estimation maps by means of multidate Landsat fused images (pdf)