The Vegetation Drought Response Index (VegDRI): A New Drought Monitoring Approach for Vegetation

Remote sensing has proven useful for large-area vegetation monitoring given the synoptic coverage, high temporal repeat cycle, and continuous, moderate resolution observations of satellite-based sensors. In particular, time-series normalized difference vegetation index (NDVI) data from the global imager, the Advanced Very High Resolution Radiometer (AVHRR), has been widely used for vegetation and ecosystem monitoring (Tucker et al., 1985; Reed et al., 1994; Jakubauskas et al., 2002). Analysis of time-series NDVI data and NDVI-derived metrics have been an effective means for identifying vegetation condition anomalies (e.g., apparent declines in vegetation health). Operational efforts such as the Green Report (http://www.kars.ku.edu/products/greenreport.shtml), RangeView (http://rangeview.arizona.edu/), and the U.S. Forest Service’s Wildland Fire Assessment System (http://www.wfas.net/content/view/30/47/) provide NDVI-derived products that describe the percentage or deviation of current vegetation conditions from the normal conditions expressed historically in the NDVI data. The Vegetation Condition Index (VCI) (Kogan, 1990), which is based on a transformation of the AVHRR NDVI data, and the Temperature Condition Index (TCI), which is calculated from AVHRR’s thermal data (Kogan, 1995), are operationally produced and have been commonly used for national- to global-scale drought monitoring (Liu and Kogan, 1996; Kogan, 1997; Unganai and Kogan, 1998). Although these numerous operational products have been useful for vegetation monitoring, they are limited for effectively characterizing the impact of drought on vegetation because the anomalies caused by drought stress cannot be discriminated from anomalies produced by other environmental causes of vegetation stress (e.g., flooding, fire, pest infestation, and hail damage) and anthropogenic drivers (e.g., land cover/land use conversion). Additional information is required to discriminate the drought-impacted areas from locations where the vegetation is being influenced by these other environmental and anthropogenic factors.