Remote Sensing of Urban Vegetation during Drought in Southern California

Plants can respond to drought events in a variety of ways, including adjustments in physiological processes and changes in canopy structure. Quantifying these changes over large spatial domains and through time can be challenging, especially with variable vegetation cover types. During 2012-2016, California experienced one of the most severe droughts in its modern history, with limited precipitation and exceptionally high temperatures over an extended time period. Urban vegetation, such as trees and turfgrass lawns, provides many ecosystem services for people living in cities, such as cooling through shading and evapotranspiration, but these benefits may be difficult to maintain through extreme drought, especially in water-limited cities. Therefore, it is critical to understand how drought response in vegetation may vary across urban landscapes. In this dissertation, I used remote sensing time series to quantify how urban vegetation responded to drought in Santa Barbara and Los Angeles, California. In Chapter 1, I examined drought response in turfgrass and across nineteen urban tree species in the city of Santa Barbara using data from repeat flights of the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) and AVIRIS-Next Generation (AVIRIS-NG). I compared many spectral indicators that may be expected to change within plant canopies during drought. Compared with data from before the drought in 2011, all tree species and turfgrass had four or more spectral indicators with significantly lower mean values (p < 0.05) during the drought in 2014, and evidence of recovery was observed for some species in 2017, after the drought had ended. Based on the spectral indicators, turfgrass cover senesced in the middle of the drought but recovered soon after the drought ended. Nearly all tree species showed significant canopy changes in the middle of the drought, but in comparison to turfgrass, most tree species did not fully recover after the drought ended. In Chapter 2, I evaluated how drought manifests seasonally and interannually during 2010-2019 across dominant types of trees and grass in the Santa Barbara area using Landsat and AVIRIS imagery. I compared the condition of dominant types of trees and grasses as they changed throughout the year using the Normalized Difference Vegetation Index (NDVI), difference in vegetation land surface temperature from impervious surfaces (∆LST), and equivalent water thickness (EWT). NDVI was lower and ΔLST was closer to zero during drought years but they were seasonally correlated for only some vegetation types. Changes in EWT revealed seasonal adjustments by vegetation that were not readily apparent in the NDVI time series. I also assessed the correlations of NDVI and LST with the Standardized Precipitation Evapotranspiration Index (SPEI) to test the effects of drought length and severity on vegetation. NDVI and ΔLST were most strongly correlated with SPEI during summer for most vegetation types, except for annual grass NDVI (winter). Annual grass was correlated with SPEI at spans ≤12 months, whereas trees and turfgrass were correlated with SPEI at spans >12 months in addition to seasonal time spans. In Chapter 3, I assessed annual changes in fractional cover of trees, turfgrass, non-photosynthetic vegetation (NPV; e.g., senesced grass, plant litter), and non-vegetated urban surfaces across the Los Angeles metropolitan area during 2013-2018 using AVIRIS imagery. During the drought time series from 2013 to 2018, mean turfgrass cover decreased and NPV cover increased, but tree cover did not show a strong trend with drought until 2018. The interior valleys of the study area (San Gabriel and San Fernando) consistently lost more turfgrass than coastal areas, and the San Gabriel Valley had strong losses of total vegetation cover (tree + turfgrass + NPV) overall. I also used datasets of median household income from census tracts and of typical non-drought outdoor water use from postal carrier routes to compare the magnitude and timing of different vegetation cover type changes at different income and water use levels. There were larger absolute changes in vegetation cover in higher income and higher water use areas, likely due to the higher baseline of mean vegetation cover in these areas. Once normalized for their mean values, the magnitude of changes often became more similar across different income and water use levels, but not always, with lower income and water use areas showing greater relative changes for trees. Overall, this dissertation quantifies drought responses across different urban vegetation types during a severe, long-term drought event at an array of spatial and temporal scales, providing implications for vegetation sustainability planning in cities with frequent droughts