MODIS Derived Vegetation Index for Drought Detection on the San Carlos Apache Reservation

Zhuoting Wu, Miguel Velasco, Jason McVay, Barry Middleton, John Vogel, Dennis Dye, (doi: 10.23953/cloud.ijarsg.44)


A variety of vegetation indices derived from remotely sensed data have been used to assess vegetation conditions, enabling the identification of drought occurrences as well as the evaluation of drought impacts. Moderate Resolution Imaging Spectroradiometer (MODIS) Terra 8-day composite data were used to compute the Modified Soil Adjusted Vegetation Index II (MSAVI2) of four dominant vegetation types over a 13-year period (2002 – 2014) on the San Carlos Apache Reservation in Arizona, US. MSAVI2 anomalies were used to identify adverse impacts of drought on vegetation, characterized as mean MSAVI2 below the 13-year average. In terms of interannual variability, we found similar responses between grassland and shrubland, and between woodland and forest vegetation types. We compared MSAVI2 for specific vegetation types with precipitation data at the same time step, and found a lag time of roughly two months for the peak MSAVI2 values following precipitation in a given year. All vegetation types responded to summer monsoon rainfall, while shrubland and annual herbaceous vegetation also displayed a brief spring growing season following winter snowmelt. MSAVI2 values of shrublands corresponded well with precipitation variability both for summer rainfall and winter snowfall, and can be potentially used as a drought indicator on the San Carlos Apache Reservation given its wide geographic distribution. We demonstrated that moderate temporal frequency satellite-based MSAVI2 can provide drought monitoring to inform land management decisions, especially on vegetated tribal land areas where in situ precipitation data are limited.


Drought; Modified Soil Adjusted Vegetation Index II (MSAVI2); MODIS; Precipitation; Vegetation Index Anomaly

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