Sharmistha Swain, geography Ph.D. candidate, will defend her dissertation, “Evaluating vegetation response to water stress using close-range and satellite remote sensing,” at 8 a.m. Thursday, May 17 in 228 Hardin Hall. Her advisors are Sunil Narumalani and Brian Wardlow.
Abstract
During the last century, almost all parts of the contiguous U.S. had experienced several prolonged drought events with considerable impacts on the agricultural economy and environment. With changing climates, the drought events are expected to be more severe, longer, and widespread in many parts of the world. Understanding vegetation response to water stress using remote sensing technologies will enhance our ability to detect and monitor drought. This dissertation research evaluates the response of vegetation to drought-related water stress at the leaf, canopy, and regional scales using close-range and satellite based reflectance and/or thermal data. At the leaf level, a crop water stress index-based model was developed using high spatial resolution thermal imageries to estimate water content in soybean leaves. The model showed a higher accuracy in leaf water content estimation as compared to water content estimated using the raw leaf temperature. At the canopy level, multi-year close-range reflectance based vegetation indices (VIs) data were correlated with soil moisture measured at four depths of corn and soybean root zone. Results indicated that corn VIs were significantly related to soil moisture at deeper depths and kept the soil moisture memory for a relatively longer period of time compared to those of soybeans. At the regional scale, Terra-MODIS Land Surface Temperature (LST) and NDVI products were used to detect drought-induced stress on cropland and grassland cover types across the state of Nebraska. Results showed that the majority of the land cover sites experienced statistically significant increase in daytime and nighttime LST and statistically significant decrease in NDVI during the drought-year growing season as compared to the non-drought year. The findings of this dissertation research will contribute toward the development of more robust tools for monitoring drought stress on vegetation.