Evaluating Temperature Vegetation Dryness Index (TVDI) Using Various Vegetation Indices in Multiple Spatial Resolutions

As a key variable in many land surface processes and an important input for most land surface models, soil moisture is very difficult to measure on a consistent and spatially comprehensive basis. The traditional in-situ measurements are time-consuming and difficult to extrapolate to larger areas. The remote microwave methods are not appropriate if the research focus is on small spatial scales and high temporal frequency measurements. In contrast, optical passive sensors can provide high temporal and spatial resolution information and be used to calculate spectral indices to provide some measure of soil moisture status. Temperature Vegetation Dryness Index (TVDI) is one of the spectral indices that have been proved to highly correlate with the near-surface soil moisture. TVDI calculated from Pathfinder, AVHRR and MODIS shows a strong relationship with soil moisture, but few studies have been done using finer spatial resolution data such as Landsat and ASTER data. This research uses MODIS data, with its moderate resolution, and fine resolution ASTER and Landsat data to calculate TVDI by parameterizing the vegetation index and surface temperature space from optical passive sensors' reflectance and surface temperature products. While the Normalized Difference Vegetation Index (NDVI) is often used to establish TDVI, NDVI becomes saturated when biomass is high and therefore it can have difficulties in detecting change in dense vegetation. Therefore, to evaluate this effect, various vegetation indices with different sensitivities to surface cover are used to generate TVDI in this research. In-situ surface soil moisture data collected in both the Neponset River Watershed and in the Greater Boston Area (GBA) using a portable soil moisture impedance probe are used to evaluate the TVDI patterns. The urban to rural gradient of soil moisture status is also studied along two transects radiating out from downtown Boston. The soil moisture data from these transects was collected as part of the Boston Ultra-Ex project focused on the CO² metabolism of greater Boston.