A PCA-OLS Model for Assessing the Impact of Surface Biophysical Parameters on Land Surface Temperature Variations

Analysis of land surface temperature (LST) spatiotemporal variations and characterization of the factors affecting these variations are of great importance in various environmental studies and applications. The aim of this study is to propose an integrated model for characterizing LST spatiotemporal variations and for assessing the impact of surface biophysical parameters on the LST variations. For this purpose, a case study was conducted in Babol City, Iran, during the period of 1985 to 2018. We used 122 images of Landsat 5, 7, and 8, and products of water vapor (MOD07) and daily LST (MOD11A1) from the MODIS sensor of the Terra satellite, as well as soil and air temperature and relative humidity data measured at the local meteorological station over 112 dates for the study. First, a single-channel algorithm was applied to estimate LST, while various spectral indices were computed to represent surface biophysical parameters, which included the normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), normalized difference water index (NDWI), normalized difference built-up index (NDBI), albedo, brightness, greenness, and wetness from tasseled cap transformation. Next, a principal component analysis (PCA) was conducted to determine the degree of LST variation and the surface biophysical parameters in the temporal dimension at the pixel scale based on Landsat imagery. Finally, the relationship between the first component of the PCA of LST and each surface biophysical parameter was investigated by using the ordinary least squares (OLS) regression with both regional and local optimizations. The results indicated that among the surface biophysical parameters, variations of NDBI, wetness, and greenness had the highest impact on the LST variations with a correlation coefficient of 0.75, −0.70, and −0.44, and RMSE of 0.71, 1.03, and 1.06, respectively. The impact of NDBI, wetness, and greenness varied geographically, but their variations accounted for 43%, 38%, and 19% of the LST variation, respectively. Furthermore, the correlation coefficient and RMSE between the observed LST variation and modeled LST variation, based on the most influential biophysical factors (NDBI, wetness, and greenness) yielded 0.85 and 1.06 for the regional approach and 0.93 and 0.26 for the local approach, respectively. The results of this study indicated the use of an integrated PCA–OLS model was effective for modeling of various environmental parameters and their relationship with LST. In addition, the PCA–OLS with the local optimization was found to be more efficient than the one with the regional optimization

Response of a Rocky Mountain forest system to a shifting disturbance regime, The

2019 Fall.Includes bibliographical references.Climate change is likely to drive widespread forest declines and transitions as temperatures shift beyond historic ranges of variability. Warming temperatures and shifting precipitation patterns may lead to increasing disturbances from wildfire, insect outbreaks, drought, and extreme weather events, which may greatly accelerate rates of ecosystem change. However, the role of disturbance in shaping forest response to climate change is not well understood. Better understanding the impacts of changing disturbance patterns on forest decline and recovery will allow us to better predict how forest ecosystems may adapt to a warming world. Severe wildfires and bark beetle outbreaks are currently affecting large areas of forest throughout western North America, and increasing disturbance size and severity will have uncertain impacts on forest persistence. The goal of my dissertation was to investigate the factors shaping disturbance response in a region of the San Juan Mountains, Colorado, which has undergone impacts from a high-severity spruce beetle outbreak and wildfire in the last 15 years. I conducted three separate studies in the burn area of the West Fork Complex wildfire, which burned in 2013, and in surrounding beetle-affected spruce-fir forests. The goals of each study were to 1) assess whether the severity of spruce beetle outbreaks occurring before wildfire resulted in compounded disturbance interactions affecting vegetation recovery, 2) determine how the severity of each disturbance type influenced fine-scale below-canopy temperature patterns across the landscape, and 3) assess how conifer seedling regeneration densities were influenced by effects of disturbance severity on seed dispersal, temperature, and vegetation structure. I found that disturbances influenced seedling regeneration and ecosystem resilience through several mechanisms. First, pre-fire beetle outbreak severity was negatively correlated with post-fire vegetation cover, indicating that the combined disturbances were inhibiting regeneration beyond what may have been expected with fire alone. Second, disturbances had significant effects on below-canopy temperatures, with burned areas ~0.5 °C warmer than unburned forest areas and differences in overnight minimum temperatures resulting from loss of live canopy in unburned, beetle-killed forests. Third, the large fire size and high severity resulted in very little spruce seed dispersal or conifer regeneration in most of the burned area, while spruce regeneration in unburned forest was negatively correlated with increasing overstory mortality from the spruce beetle. My results indicate that disturbance is playing an important role in determining the future trajectory of the forest in my study area. The West Fork Complex fire has caused a severe ecosystem transformation, has increased landscape exposure to warming temperatures, and is preventing forest re-establishment as a result of a lack of seed sources. The spruce beetle outbreak has not resulted in such a severe transformation, but is possibly leading to reduced forest resilience by reducing spruce seedling re-establishment and by altering fuel structures to make forests more prone to high soil burn severity if fire follows within ~10 years. Warming of below-canopy microclimates is not exacerbated by spruce beetle outbreak, and is rather partially offset by cooling of overnight temperatures. These findings provide insights into how forest responses to climate change may be shaped by disturbance processes, which are occurring with increasing severity and frequency worldwide