Dataset associated with "Temporal Variations of NDVI and LAI and Interactions with Hydroclimatic Variables in a Large and Agro-Ecologically Diverse Region" - Ukasha, Muhammad; Ramirez, Jorge A.; Niemann, Jeffrey D. (Colorado State University. Libraries, 2021)
Satellite based vegetation indices are increasingly used to characterize seasonal and interannual variations in vegetation as well as vegetation’s response to hydroclimatic variability. However, differences in the behavior of vegetation indices are not well understood over large spatial extents (e.g., 0.5° or larger). We hypothesize that normalized difference vegetation index (NDVI) and leaf area index (LAI) can exhibit different behaviors due to different relationships with hydroclimatic variables. To test this hypothesis, observations of monthly precipitation, discharge, temperature, vapor pressure deficit, evapotranspiration, and total water storage anomalies (TWSA) are processed for the combined Sacramento and San Joaquin river basins in California for 13 water years (October 2002-September 2015). Estimates of NDVI and LAI are obtained for the same period from MODerate resolution Imaging Spectroradiometer (MODIS). The seasonal cycle of NDVI peaks 2-3 months earlier than LAI. The seasonal variation in NDVI follows the seasonality of TWSA (i.e. water availability) whereas the seasonal cycle of LAI follows the seasonality in mean temperature and vapor pressure deficit (i.e. atmospheric water demand). Cross-correlation analyses of NDVI and LAI with the hydroclimatic variables show that LAI is more strongly correlated with most of the hydroclimatic variables considered.
It contains the dataset used to produce Figure 2 in the manuscript and to estimate relationships of hydroclimatic variables with vegetation indices. Each variable is a monthly regional average (for combined Sacramento and San Joaquin river basins, California) and spans from October 2002 to September 2015. These regional averages have been estimated using different datasets which are cited in the manuscript. Description of dataset is as follows: 1. Dataset 1: Regional averages of monthly hydroclimatic and vegetation anomalies; 2. Dataset 2: Mean and standard deviations of monthly hydroclimatic and vegetation anomalies; 3. Dataset 3: Prewhitened time series of monthly hydroclimatic and vegetation anomalies; 4. Dataset 4: Prewhitened-detrended time series monthly hydroclimatic and vegetation anomalies; 5. Dataset 5: Annual time series of regional hydroclimatic and vegetation anomalies. See supplementary information provided with the manuscript for more information.
Department of Civil and Environmental Engineering